In an era where fintech startups like Revolut and Wise have gained significant traction in the international payments space, HSBC Holdings Plc, the multinational banking behemoth, is preparing to launch its own game-changing app called Zing. With a focus on offering cheap foreign exchange services, Zing aims to directly challenge the dominance of these fintech giants and grab a share of the fast-growing market. This article explores the key features of Zing, its global ambitions, and the potential impact it could have on the banking industry.
The Emergence of Zing
HSBC’s Zing app is set to debut in the UK, targeting affluent consumers seeking cost-effective foreign exchange solutions. However, the bank has ambitious plans to expand its services to other markets, including Asia, the Middle East, and EU countries. With its imminent availability on Apple’s App Store and Google Play, Zing will be accessible to both HSBC customers and non-customers alike, showcasing the bank’s determination to “attack” the retail payments market on a global scale.
Nuno Matos, CEO of HSBC’s global wealth and personal banking business, highlights the app’s user-friendly nature, stating that it will take just three minutes for new users to sign up. This ease of access, coupled with competitive forex offerings, positions Zing as a formidable contender in the international payments landscape.
HSBC’s Motivation for Launching Zing
As one of the largest banks in the world, HSBC is already a prominent player in conventional banking. However, the rise of fintech startups has presented an opportunity for the bank to tap into the flourishing foreign exchange market. Revolut and Wise, with their millions of retail customers, have demonstrated the potential for exponential growth in this space. By leveraging its extensive network and financial resources, HSBC aims to challenge these smaller players and position itself as a global platform for international payments.
HSBC’s existing product, Global Money, offers fee-free currency services to its customers. Since its launch in 2020, Global Money has attracted hundreds of thousands of users and processed transactions worth approximately $11 billion in 2022. With the introduction of Zing, HSBC hopes to not only retain its customer base but also entice non-customers to explore its broader range of banking services.
The Competitive Landscape
As HSBC prepares to enter the international payments market, it faces stiff competition from established fintech players. Wise, which recently went public, experienced significant growth in 2021, with its stock surging over 50%. Revolut, boasting over 26 million users, expects its revenue to increase by almost 70% in 2023, reaching $2 billion. These success stories underscore the popularity of fintech solutions and the growing preference for digital banking experiences.
Zing’s Unique Value Proposition
Zing’s value proposition lies in its ability to provide low-cost international payments with the backing of HSBC’s global network. By offering a comprehensive range of services, Zing aims to attract users who may eventually become loyal HSBC customers. Matos emphasizes the app’s appeal to internationally mobile clients, aligning with HSBC’s strategic objective of becoming the leading financial institution for this customer segment.
The Potential of Zing
HSBC’s foray into the international payments market with Zing represents a bold move for the bank. By venturing beyond its traditional customer base, HSBC aims to capitalize on the growing contingent of consumers who share similar characteristics and preferences. With its global ambitions, Zing has the potential to disrupt the industry and position HSBC as a significant player in the digital banking space.
Expert Opinions and Market Outlook
According to TipRanks, HSBC stock has a Moderate Buy consensus rating, indicating positive sentiment from analysts. The forecasted HSBC Holdings share price suggests a potential upside of 26.4% from current levels. This outlook reflects the market’s confidence in HSBC’s strategic initiatives, including the launch of Zing and its commitment to capturing a share of the international payments market.
Customer Satisfaction and Adoption of A2A Payments
Zing’s impending launch comes at a time when consumers increasingly favor account-to-account (A2A) payment solutions. According to a study conducted by PYMNTS Intelligence and AWS, 84% of users reported high satisfaction levels with their preferred A2A payment platforms. The seamless payment experience and integration within established ecosystems contribute to this positive sentiment, fostering loyalty and trust among users.
Conclusion
HSBC’s Zing app is poised to revolutionize the international payments landscape by offering affordable foreign exchange services to a wide range of customers. With its global ambitions, user-friendly interface, and the backing of HSBC’s extensive network, Zing has the potential to challenge established fintech players and position HSBC as a dominant force in the digital banking space. As the app launches in the UK and expands to other markets, it will be fascinating to witness its impact and the extent to which it disrupts the industry.
In our digital age, where cyber threats loom large, Digital Immune Systems (DIS) are like superheroes for software, shielding it from bugs and security threats. This powerful approach not only makes software resilient but also ensures a seamless user experience. Let’s dive into what DIS is all about, why it matters, and how you can strengthen your software’s immune system.
Digital Immune System Decoded: DIS is like a shield, swiftly protecting software from bugs and security breaches. Its goal is clear: make applications resilient, reduce business risks, and, most importantly, keep users happy. By 2025, organizations investing in DIS are expected to cut downtime by 80%, a testament to its crucial role in keeping operations smooth.
Essential Components of DIS:
Observability: Transparent systems are resilient. Observability means real-time monitoring, catching and fixing issues on the fly, making user experiences better.
AI-Augmented Testing: Let AI handle testing independently, identifying issues early without human intervention.
Chaos Engineering: Controlled disruptions in testing, preparing teams for real-world challenges.
Auto-Remediation: Applications that can fix themselves, ensuring uninterrupted service without human help.
Application Security: Safeguarding the software supply chain with security measures and strong version control.
Site Reliability Engineering (SRE): Balancing speed and stability for a fantastic user experience.
Why DIS Matters for Software: DIS not only reduces business risks but also boosts software quality. Real-time threat detection, continuous monitoring, and meeting security requirements ensure a proactive defense against cyber threats.
Linking Digital Immunity to Software Quality: Automated testing and continuous monitoring, integral to DIS, ensure fast and top-quality software releases. The aim is to make software immune to bugs and vulnerabilities right from the start, ensuring efficiency and performance.
Achieving a Healthy Digital Immune System: Automate code changes, increase testing coverage, and leverage technology like APIs. Sauce Labs, with its testing solutions, helps identify risks quickly and securely.
In a Nutshell: In our digital-heavy world, DIS is your software’s superhero. Investing in a robust digital immune system protects your digital assets, ensures smooth operations, delights users, and fortifies software quality.
Opinion: This insightful information about Digital Immunity brilliantly demystifies the complex world of software development, making the concept accessible and highlighting its pivotal role in safeguarding against cyber threats. The clear breakdown of key components and their real-world significance, coupled with practical tips for achieving a robust Digital Immune System, empowers you with actionable insights. In a landscape where digital security is paramount, this piece not only underscores the importance of DIS but also serves as a valuable guide for organizations aiming to fortify their software against evolving threats.
Questions for Readers: How do you think Digital Immune Systems will evolve as our digital world keeps growing, and what extra steps would you recommend for safeguarding software development against new threats?
AI is a powerful technology that can be used for both good and evil purposes. On the one hand, AI can help detect and prevent fraud by analyzing data and identifying patterns that may indicate fraudulent activity⁵⁶⁷. On the other hand, AI can also be used to facilitate fraudulent activities, such as generating fake or misleading information, or automating scams or other fraudulent schemes¹²³⁴.
Some of the benefits of using AI for fraud detection and prevention are:
Speed and efficiency: AI can process large amounts of data and perform tasks quickly, which makes it a potentially useful tool for detecting fraud in real time⁵.
Anonymity: AI can help protect the identity and privacy of the users and the organizations from fraudsters, by using encryption, authentication, and biometrics⁶.
Evasion of detection: AI can help avoid false positives and false negatives, by using machine learning algorithms that can learn from data and improve their accuracy over time⁷.
Some of the challenges of using AI for fraud detection and prevention are:
Data quality and availability: AI relies on data to learn and perform its tasks, but the data may not be reliable, complete, or accessible, which can affect the performance and validity of the AI models⁵.
Ethical and legal issues: AI may raise ethical and legal concerns, such as privacy, security, accountability, transparency, and fairness, which may require regulation and oversight⁶.
Adversarial attacks: AI may be vulnerable to adversarial attacks, where fraudsters can manipulate the data or the AI models to deceive or evade the AI systems⁷.
Some of the ways that AI can be used to facilitate fraudulent activities are:
Generating fake or misleading information: AI can create fake websites, social media accounts, or other online content that is designed to deceive or mislead people. This could include generating fake reviews or manipulating online ratings to mislead consumers¹.
Automating scams: AI can automate scams or fraudulent schemes, such as by sending out mass emails or text messages that are designed to trick people into revealing sensitive information or sending money².
Spoofing phone numbers or email addresses: AI can create fake phone numbers or email addresses that are designed to deceive people into thinking they are communicating with a legitimate entity².
Voice cloning: AI can replicate a person’s voice after listening to them speak for only a few seconds, which can be used to impersonate someone or bypass voice biometric systems².
My view on AI used in frauds and scams is that AI is a double-edged sword that can be used for both good and evil purposes. AI has the potential to improve the security and efficiency of fraud detection and prevention, but it also poses new risks and challenges that need to be addressed. I think that AI should be used responsibly and ethically, with proper regulation and oversight, to ensure that it is not abused or misused for fraudulent activities. I also think that users and organizations should be aware of the potential threats and take appropriate measures to protect themselves from fraud, whether it involves AI or other technologies.
Source: (1) How AI And Machine Learning Help Detect And Prevent Fraud – Forbes. https://www.forbes.com/sites/forbestechcouncil/2023/11/01/how-ai-and-machine-learning-help-detect-and-prevent-fraud/. (2) How AI Used in Fraud Detection? Benefits, Techniques, Use cases. https://www.knowledgehut.com/blog/data-science/ai-fraud-detection. (3) Artificial Intelligence – How it’s used to detect financial fraud. https://www.fraud.com/post/artificial-intelligence. (4) AI Fraud: The Hidden Dangers of Machine Learning-Based Scams. https://www.acfeinsights.com/acfe-insights/2023/1/6/ai-and-fraud. (5) Experts say AI scams are on the rise as criminals use voice cloning …. https://www.abc.net.au/news/2023-04-12/artificial-intelligence-ai-scams-voice-cloning-phishing-chatgpt/102064086. (6) Growing AI-powered fraud highlights the need for advanced fraud detection. https://blog.sift.com/growing-ai-powered-fraud-highlights-the-need-for-advanced-fraud-detection/. (7) The Rise of AI in Phishing Scams: How Scammers Use It and How We Can …. https://fightcybercrime.org/blog/the-rise-of-ai-in-phishing-scams-how-scammers-use-it-and-how-we-can-fight-back/. (8) AI-Powered Fraud Protection Strategies for Banks. https://fintechmagazine.com/articles/how-ai-can-protect-against-bank-fraud-scams.
The statement “There is no privacy in the new technological age” reflects a sentiment often associated with the rapid advancements in technology and the increased digital interconnectedness prevalent in modern society. Several factors contribute to this perception:
1. Ubiquitous Data Collection: In today’s digital landscape, massive amounts of data are constantly generated, collected, and stored by various entities, including tech companies, social media platforms, governments, and more. This data collection occurs through online activities, such as browsing habits, social media interactions, location tracking, and purchases, creating extensive digital footprints for individuals.
2. Surveillance Technologies: Surveillance technologies, including CCTV cameras, facial recognition systems, and data tracking tools, are increasingly prevalent in public spaces and online platforms. This widespread surveillance raises concerns about the erosion of personal privacy as individuals may be continuously monitored without their explicit consent.
3. Data Breaches and Hacks: Despite efforts to secure data, data breaches and cyberattacks remain persistent threats. Incidents involving the unauthorized access to personal information, credit card details, or sensitive data highlight the vulnerabilities of digital systems, potentially compromising individuals’ privacy and security.
4. Algorithmic Profiling and Predictive Analytics: Advanced algorithms analyze vast amounts of data to create detailed profiles and predict behaviors. While these technologies can offer personalized services, they also raise concerns about the invasion of privacy by creating highly targeted and potentially intrusive advertising or influencing individual decisions without their explicit consent.
5. Lack of Transparent Policies: There’s often a lack of transparency regarding how organizations handle and utilize collected data. Users might not fully comprehend the extent to which their information is collected, shared, or sold to third parties, leading to concerns about a lack of control over personal data.
However, it’s essential to note that efforts are being made globally to address these concerns. Regulations such as the General Data Protection Regulation (GDPR) in the EU and the California Consumer Privacy Act (CCPA) in the United States aim to enhance data protection and privacy rights for individuals. These regulations impose guidelines and restrictions on how organizations collect, store, and process personal data.
While the statement might convey the pervasive challenges regarding privacy in the digital age, ongoing discussions, regulations, and technological advancements also seek to address and mitigate these issues, aiming to establish a better balance between technological innovation and individual privacy rights.
The idea that “having no privacy in the technological age” has advantages might seem counterintuitive given the importance of privacy in safeguarding personal information and autonomy. However, in specific contexts, the lack of privacy or increased transparency can potentially offer certain advantages:
1. Enhanced Security and Safety: In some instances, increased transparency or reduced privacy can contribute to enhanced security. For example, in public spaces or high-security environments, surveillance cameras and monitoring systems may deter criminal activities, improve public safety, and assist in investigations.
2. Personalized Services: Some individuals might appreciate reduced privacy in exchange for personalized services. When companies have access to a user’s data and preferences, they can tailor products, services, and recommendations to better suit individual needs and preferences.
3. Improved Healthcare and Research: In the healthcare sector, access to aggregated and anonymized data from large populations can contribute to medical research, drug development, and the improvement of healthcare services. Analyzing anonymized health data on a large scale can lead to significant advancements in disease prevention and treatment.
4. Transparency and Accountability: Increased transparency in certain areas, such as government operations or corporate practices, can lead to greater accountability. Public access to certain information can hold institutions accountable for their actions, encouraging ethical behavior and reducing corruption.
5. Social Connectivity and Collaboration: Social media platforms and interconnected technologies have created an environment where individuals can connect, collaborate, and share information globally. This interconnectedness can foster community building, knowledge sharing, and social activism.
However, while these points might highlight potential benefits, they come with significant caveats. Balancing the advantages of reduced privacy with ethical considerations, individual rights, and the potential for misuse of personal information remains a crucial challenge. Additionally, these potential advantages need to be weighed against the risks of potential abuses, breaches, manipulation, and the erosion of personal autonomy.
Striking a balance between the benefits of transparency or reduced privacy and the protection of individual rights and privacy remains a complex and ongoing societal challenge in the technological age. Many discussions and regulations aim to address these issues while harnessing the advantages that technology can offer.
Prompts used: “please elaborate on this statement “There is no privacy in the new technological age. “” “any advantages of having no privacy in the technological age?”
Emerging technologies are changing the way we live, work, and communicate. One such technology is 5G, the fifth generation of cellular network technology. 5G promises to revolutionize our communication by providing faster speeds, lower latency, and more reliable connectivity. However, like any new technology, 5G has its pros and cons. In this blog post, I will discuss the advantages and disadvantages of 5G technology.
Advantages of 5G Technology
Greater Transmission Speed: One of the most significant advantages of 5G technology is its greater transmission speed. The 5G network spectrum includes the millimeter-wave band, which is expected to be 100 times faster than Fourth Generation (4G) networks with transmission speeds up to 10 Gbps. This inevitably leads to faster transmission of images and videos. A high-resolution video that would normally take a long time to download can now be done in the blink of an eye using the 5G technology.
Lower Latency: Latency refers to the time interval between an order being received and the given instruction being executed. In 5G technology, the delay time is around 4-5 milliseconds (ms) and can be reduced to 1 ms, i.e., ten times less than the latency of 4G technology. This makes it possible for us to watch high-speed virtual reality videos with no interruptions. Due to this particular feature of 5G technology, it can be extremely helpful in fields other than IT, like medicine and construction fields.
Increased Connectivity: Since the 5G network uses more spectrum, it allows connection with a greater number of devices, a hundred times increase in traffic capacity, to be precise. This increased connectivity will enable more devices to connect to the internet simultaneously without any lag or delay.
Better Coverage: Anybody who has tried to get decent cellular service at a crowded concert or sports event knows that it can often be a challenge. Thousands of mobile phones competing for the same cellular service can overwhelm even the best Fourth Generation (4G)/Long-Term Evolution (LTE) networks. However, with 5G, more connectivity can be provided to these areas with lower latency and expanded access for larger groups who may need it.
Improved Communication: With its low latency and high speed, 5G is expected to enable faster and more efficient communication between people and devices. It will also provide ubiquitous connectivity to many more devices.
Disadvantages of 5G Technology
Costly: We need skilled engineers to install and maintain a 5G network. Additionally, the equipment required for a 5G network is costly, resulting in increased costs for arrangement and maintenance phases. Not to forget that 5G smartphones are costly too.
Development: The 5G technology is still under development, resulting in investing more time before it is fully operational without any issues such as security and privacy of the user.
Environmental Degradation: For establishing a 5G network, more towers and energy will be required for proper functioning, which will result in the degradation of forest land and resources, adding another cause to global warming.
Radiations: To establish a 5G network we require switching from Fourth Generation (4G) to Fifth Generation (5G) network which means both networks will operate together causing more radiation that will have long-lasting consequences on humans and wildlife.
Dangerous for Wildlife: Some studies have found that there are certain insects that absorb high frequencies used in Fourth Generation (4G) or Fifth Generation (5G) networks.
In conclusion, emerging technologies like 5G have their pros and cons. While they offer significant advantages like greater transmission speed, lower latency, increased connectivity, better coverage, and improved communication; they also pose significant risks like being costly, under development, environmental degradation due to increased towers and energy requirements for proper functioning; radiation causing long-lasting consequences on humans and wildlife; being dangerous for wildlife.
I decided to do more research about this topic rather than use AI-generated text. Bing AI was helpful with providing guidance to my research, however, it was less thorough when being asked prompts such as, “What speeds can new 5G technology perform at as compared to old 3G technology we had years ago?”. I didn’t necessarily agree with every article and the points that were being driven. Some argue that the rapid deployment of 5G infrastructure may pose environmental concerns due to increased energy consumption and electronic waste. Additionally, there are privacy and security concerns related to the vast amount of data transmitted through 5G networks, raising questions about data protection and surveillance. There are many mixed opinions about this topic and it is hard to trust a single source and outline where biases lay.
In recent years, large language models have made significant strides in their conversational and research capabilities, providing vast knowledge on almost any topic. However, this progress has raised concerns about the security of these technologies. Jailbreaking, as it is called, is a method of exploiting large AI knowledge unrestrictedly. It is achieved by prompting specific commands that trigger the AI to answer without regard to its built-in security measures. Jailbreak prompts can range from straightforward commands to more abstract narratives designed to coax the chatbot into bypassing its constraints. The overall goal is to find specific language that convinces the AI to unleash its full, uncensored potential.
jailbroken chatgbt
As AI systems like ChatGPT continue to advance, there is growing concern that techniques to bypass their safety features may become more prevalent. However, a focus on responsible innovation and enhancing safeguards could help mitigate potential risks.
Organizations like OpenAI are already taking proactive measures to enhance the security of their chatbots. They conduct red team exercises to identify vulnerabilities, enforce access controls, and diligently monitor for malicious activity. The OWASP Top 10 for Large Language Model Applications project aims to educate developers, designers, architects, managers, and organizations about the potential security risks when deploying and managing Large Language Models (LLMs). The project provides a list of the top 10 most critical vulnerabilities often seen in LLM applications, highlighting their potential impact, ease of exploitation, and prevalence in real-world applications. Examples of vulnerabilities include prompt injections, data leakage, inadequate sandboxing, and unauthorized code execution, among others. The goal is to raise awareness of these vulnerabilities, suggest remediation strategies, and ultimately improve the security posture of LLM applications .
In conclusion, while the potential risks of large language models are real, responsible innovation and enhanced safeguards can help mitigate these risks. Organizations like OpenAI and OWASP are already taking proactive measures to enhance the security of their chatbots, and it is essential that others follow suit to ensure the safe and responsible deployment of these powerful technologies.
Cryptocurrency payments startup Ramp Network, based in Poland and London, has recently secured an impressive $70 million in fresh investment, defying the challenging fundraising landscape and the turmoil in the crypto industry. This Series B funding round, co-led by Mubadala Capital from the UAE and Korelya Capital from France, follows their successful $53 million Series A round less than a year ago. It stands as one of the largest funding rounds in the history of the Polish startup ecosystem.
What is Ramp Network?
Ramp Network provides a solution that allows clients, such as crypto wallets, exchanges, NFT marketplaces, and gaming companies, to seamlessly integrate crypto payment infrastructure into their existing systems. This integration enables users to purchase crypto assets without the need to switch between multiple applications. Ramp Network supports major payment methods like debit and credit cards, bank transfers, Apple Pay, and Google Pay, making it accessible to users in over 150 countries.
Navigating a Bearish Market
At a time when the global crypto market experienced a significant downturn, with a two-thirds decrease in value due to inflation and a bleak economic outlook, Ramp Network has managed to thrive. In 2022 alone, the platform witnessed a staggering 240% increase in transaction volumes compared to the previous year. Additionally, the total number of unique users has surged by over 600%. This remarkable growth sets Ramp Network apart from its competitors and demonstrates its resilience in the face of challenging market conditions.
Strategic Investments
Ramp Network’s Series B funding round attracted prominent investors from across the globe. Mubadala Capital, an Emirati venture capitalist, and Korelya Capital, a French venture capitalist, led the round. Furthermore, existing investor Balderton Capital, a UK-based venture capitalist, and Polish VC Cogito Capital also participated in the funding. The investments not only validate the potential of Ramp Network but also provide the necessary capital to further develop and expand its innovative crypto payment infrastructure.
The Path Ahead for Ramp Network
Szymon Sypniewicz, co-founder and CEO of Ramp Network, envisions making the platform even more accessible to a wider audience through the Series B funding. He plans to enter local markets and enable local payment methods, particularly focusing on Latin America and Asia. These regions have witnessed explosive crypto adoption and represent Ramp Network’s next strategic targets. The company also intends to continue hiring and invest in the further enhancement of its product line.
“We’re fully committed to our vision of making Web3 a reality for everyone. We recognize that a bear market is a builder’s market, and we’re in it for the long haul,” affirms Sypniewicz.
The Significance of Ramp Network in the Crypto World
Ramp Network’s ability to thrive during a challenging economic downturn highlights its pivotal role in the cryptocurrency ecosystem. Often compared to Stripe, a market-leading tool for e-commerce, Ramp Network aims to benefit from the growing trend of traditional companies embracing Web3. Web3 refers to the next generation of blockchain-powered businesses that prioritize decentralization and democratize ownership, in contrast to centralized platforms like Facebook and YouTube. This shift presents a significant opportunity, and Ramp Network is poised to capitalize on it, unlocking the industry’s vast potential.
Conclusion
Ramp Network’s recent funding success solidifies its position as a frontrunner in the crypto payments space. With its innovative infrastructure, the platform has enabled seamless integration of crypto payments for various businesses. Despite the bearish market conditions and the challenges faced by the crypto industry, Ramp Network has demonstrated remarkable growth and resilience. As it expands into local markets and continues to enhance its product line, Ramp Network is well-positioned to drive the adoption of cryptocurrencies and contribute to the realization of a decentralized Web3 future.
Cloud security is a collection of procedures and technology designed to address external and internal threats to business security. Organizations need cloud security as they move toward their digital transformation strategy and incorporate cloud-based tools and services as part of their infrastructure.
The terms digital transformation and cloud migration have been used regularly in enterprise settings over recent years. While both phrases can mean different things to different organizations, each is driven by a common denominator: the need for change.
As enterprises embrace these concepts and move toward optimizing their operational approach, new challenges arise when balancing productivity levels and security. While more modern technologies help organizations advance capabilities outside the confines of on-premise infrastructure, transitioning primarily to cloud-based environments can have several implications if not done securely.
Striking the right balance requires an understanding of how modern-day enterprises can benefit from the use of interconnected cloud technologies while deploying the best cloud security practices.
What is cloud computing?
The “cloud” or, more specifically, “cloud computing” refers to the process of accessing resources, software, and databases over the Internet and outside the confines of local hardware restrictions. This technology gives organizations flexibility when scaling their operations by offloading a portion, or majority, of their infrastructure management to third-party hosting providers.
The most common and widely adopted cloud computing services are:
IaaS (Infrastructure-as-a-Service): A hybrid approach, where organizations can manage some of their data and applications on-premise while relying on cloud providers to manage servers, hardware, networking, virtualization, and storage needs.
PaaS (Platform-as-a-Service): Gives organizations the ability to streamline their application development and delivery by providing a custom application framework that automatically manages operating systems, software updates, storage, and supporting infrastructure in the cloud.
SaaS (Software-as-a-Service): Cloud-based software hosted online and typically available on a subscription basis. Third-party providers manage all potential technical issues, such as data, middleware, servers, and storage, minimizing IT resource expenditures and streamlining maintenance and support functions.
Why is cloud security important?
In modern-day enterprises, there has been a growing transition to cloud-based environments and IaaS, Paas, or SaaS computing models. The dynamic nature of infrastructure management, especially in scaling applications and services, can bring a number of challenges to enterprises when adequately resourcing their departments. These as-a-service models give organizations the ability to offload many of the time-consuming, IT-related tasks.
As companies continue to migrate to the cloud, understanding the security requirements for keeping data safe has become critical. While third-party cloud computing providers may take on the management of this infrastructure, the responsibility of data asset security and accountability doesn’t necessarily shift along with it.
By default, most cloud providers follow best security practices and take active steps to protect the integrity of their servers. However, organizations need to make their own considerations when protecting data, applications, and workloads running on the cloud.
Security threats have become more advanced as the digital landscape continues to evolve. These threats explicitly target cloud computing providers due to an organization’s overall lack of visibility in data access and movement. Without taking active steps to improve their cloud security, organizations can face significant governance and compliance risks when managing client information, regardless of where it is stored.
Cloud security should be an important topic of discussion regardless of the size of your enterprise. Cloud infrastructure supports nearly all aspects of modern computing in all industries and across multiple verticals.
However, successful cloud adoption is dependent on putting in place adequate countermeasures to defend against modern-day cyberattacks. Regardless of whether your organization operates in a public, private, or hybrid cloud environment, cloud security solutions and best practices are a necessity when ensuring business continuity.
What are some cloud security challenges?
Lack of visibility It’s easy to lose track of how your data is being accessed and by whom, since many cloud services are accessed outside of corporate networks and through third parties.
Multitenancy Public cloud environments house multiple client infrastructures under the same umbrella, so it’s possible your hosted services can get compromised by malicious attackers as collateral damage when targeting other businesses.
Access management and shadow IT While enterprises may be able to successfully manage and restrict access points across on-premises systems, administering these same levels of restrictions can be challenging in cloud environments. This can be dangerous for organizations that don’t deploy bring-your-own device (BYOD) policies and allow unfiltered access to cloud services from any device or geolocation.
Compliance Regulatory compliance management is oftentimes a source of confusion for enterprises using public or hybrid cloud deployments. Overall accountability for data privacy and security still rests with the enterprise, and heavy reliance on third-party solutions to manage this component can lead to costly compliance issues.
Misconfigurations Misconfigured assets accounted for 86% of breached records in 2019, making the inadvertent insider a key issue for cloud computing environments. Misconfigurations can include leaving default administrative passwords in place, or not creating appropriate privacy settings.
What types of cloud security solutions are available?
Identity and access management (IAM) Identity and access management (IAM) tools and services allow enterprises to deploy policy-driven enforcement protocols for all users attempting to access both on-premises and cloud-based services. The core functionality of IAM is to create digital identities for all users so they can be actively monitored and restricted when necessary during all data interactions
Data loss prevention (DLP) Data loss prevention (DLP) services offer a set of tools and services designed to ensure the security of regulated cloud data. DLP solutions use a combination of remediation alerts, data encryption, and other preventative measures to protect all stored data, whether at rest or in motion.
Security information and event management (SIEM) Security information and event management (SIEM) provides a comprehensive security orchestration solution that automates threat monitoring, detection, and response in cloud-based environments. Using artificial intelligence (AI)-driven technologies to correlate log data across multiple platforms and digital assets, SIEM technology gives IT teams the ability to successfully apply their network security protocols while being able to quickly react to any potential threats.
Business continuity and disaster recovery Regardless of the preventative measures organizations have in place for their on-premise and cloud-based infrastructures, data breaches and disruptive outages can still occur. Enterprises must be able to quickly react to newly discovered vulnerabilities or significant system outages as soon as possible. Disaster recovery solutions are a staple in cloud security and provide organizations with the tools, services, and protocols necessary to expedite the recovery of lost data and resume normal business operations.
An overview of cloud security
Cloud security is a collection of procedures and technology designed to address external and internal threats to business security. Organizations need cloud security as they move toward their digital transformation strategy and incorporate cloud-based tools and services as part of their infrastructure.
The terms digital transformation and cloud migration have been used regularly in enterprise settings over recent years. While both phrases can mean different things to different organizations, each is driven by a common denominator: the need for change.
As enterprises embrace these concepts and move toward optimizing their operational approach, new challenges arise when balancing productivity levels and security. While more modern technologies help organizations advance capabilities outside the confines of on-premise infrastructure, transitioning primarily to cloud-based environments can have several implications if not done securely.
Striking the right balance requires an understanding of how modern-day enterprises can benefit from the use of interconnected cloud technologies while deploying the best cloud security practices. Learn more about cloud security solutions What is cloud computing?
The “cloud” or, more specifically, “cloud computing” refers to the process of accessing resources, software, and databases over the Internet and outside the confines of local hardware restrictions. This technology gives organizations flexibility when scaling their operations by offloading a portion, or majority, of their infrastructure management to third-party hosting providers.
The most common and widely adopted cloud computing services are:
IaaS (Infrastructure-as-a-Service): A hybrid approach, where organizations can manage some of their data and applications on-premise while relying on cloud providers to manage servers, hardware, networking, virtualization, and storage needs.
PaaS (Platform-as-a-Service): Gives organizations the ability to streamline their application development and delivery by providing a custom application framework that automatically manages operating systems, software updates, storage, and supporting infrastructure in the cloud.
SaaS (Software-as-a-Service): Cloud-based software hosted online and typically available on a subscription basis. Third-party providers manage all potential technical issues, such as data, middleware, servers, and storage, minimizing IT resource expenditures and streamlining maintenance and support functions.
Why is cloud security important?
In modern-day enterprises, there has been a growing transition to cloud-based environments and IaaS, Paas, or SaaS computing models. The dynamic nature of infrastructure management, especially in scaling applications and services, can bring a number of challenges to enterprises when adequately resourcing their departments. These as-a-service models give organizations the ability to offload many of the time-consuming, IT-related tasks.
As companies continue to migrate to the cloud, understanding the security requirements for keeping data safe has become critical. While third-party cloud computing providers may take on the management of this infrastructure, the responsibility of data asset security and accountability doesn’t necessarily shift along with it.
By default, most cloud providers follow best security practices and take active steps to protect the integrity of their servers. However, organizations need to make their own considerations when protecting data, applications, and workloads running on the cloud.
Security threats have become more advanced as the digital landscape continues to evolve. These threats explicitly target cloud computing providers due to an organization’s overall lack of visibility in data access and movement. Without taking active steps to improve their cloud security, organizations can face significant governance and compliance risks when managing client information, regardless of where it is stored.
Cloud security should be an important topic of discussion regardless of the size of your enterprise. Cloud infrastructure supports nearly all aspects of modern computing in all industries and across multiple verticals.
However, successful cloud adoption is dependent on putting in place adequate countermeasures to defend against modern-day cyberattacks. Regardless of whether your organization operates in a public, private, or hybrid cloud environment, cloud security solutions and best practices are a necessity when ensuring business continuity.What are some cloud security challenges?
Lack of visibility It’s easy to lose track of how your data is being accessed and by whom, since many cloud services are accessed outside of corporate networks and through third parties.
Multitenancy Public cloud environments house multiple client infrastructures under the same umbrella, so it’s possible your hosted services can get compromised by malicious attackers as collateral damage when targeting other businesses.
Access management and shadow IT While enterprises may be able to successfully manage and restrict access points across on-premises systems, administering these same levels of restrictions can be challenging in cloud environments. This can be dangerous for organizations that don’t deploy bring-your-own device (BYOD) policies and allow unfiltered access to cloud services from any device or geolocation.
Compliance Regulatory compliance management is oftentimes a source of confusion for enterprises using public or hybrid cloud deployments. Overall accountability for data privacy and security still rests with the enterprise, and heavy reliance on third-party solutions to manage this component can lead to costly compliance issues.
Misconfigurations Misconfigured assets accounted for 86% of breached records in 2019, making the inadvertent insider a key issue for cloud computing environments. Misconfigurations can include leaving default administrative passwords in place, or not creating appropriate privacy settings.
What types of cloud security solutions are available?
Identity and access management (IAM) Identity and access management (IAM) tools and services allow enterprises to deploy policy-driven enforcement protocols for all users attempting to access both on-premises and cloud-based services. The core functionality of IAM is to create digital identities for all users so they can be actively monitored and restricted when necessary during all data interactions
Data loss prevention (DLP) Data loss prevention (DLP) services offer a set of tools and services designed to ensure the security of regulated cloud data. DLP solutions use a combination of remediation alerts, data encryption, and other preventative measures to protect all stored data, whether at rest or in motion.
Security information and event management (SIEM) Security information and event management (SIEM) provides a comprehensive security orchestration solution that automates threat monitoring, detection, and response in cloud-based environments. Using artificial intelligence (AI)-driven technologies to correlate log data across multiple platforms and digital assets, SIEM technology gives IT teams the ability to successfully apply their network security protocols while being able to quickly react to any potential threats.
Business continuity and disaster recovery Regardless of the preventative measures organizations have in place for their on-premise and cloud-based infrastructures, data breaches and disruptive outages can still occur. Enterprises must be able to quickly react to newly discovered vulnerabilities or significant system outages as soon as possible. Disaster recovery solutions are a staple in cloud security and provide organizations with the tools, services, and protocols necessary to expedite the recovery of lost data and resume normal business operations.
How should you approach cloud security?
The way to approach cloud security is different for every organization and can be dependent on several variables. However, the National Institute of Standards and Technology (NIST) has made a list of best practices that can be followed to establish a secure and sustainable cloud computing framework.
The NIST has created necessary steps for every organization to self-assess their security preparedness and apply adequate preventative and recovery security measures to their systems. These principles are built on the NIST’s five pillars of a cybersecurity framework: Identify, Protect, Detect, Respond, and Recover.
Another emerging technology in cloud security that supports the execution of NIST’s cybersecurity framework is cloud security posture management (CSPM). CSPM solutions are designed to address a common flaw in many cloud environments – misconfigurations.
Cloud infrastructures that remain misconfigured by enterprises or even cloud providers can lead to several vulnerabilities that significantly increase an organization’s attack surface. CSPM addresses these issues by helping to organize and deploy the core components of cloud security. These include identity and access management (IAM), regulatory compliance management, traffic monitoring, threat response, risk mitigation, and digital asset management.
Overall:
The breakdown of common cloud computing services (IaaS, PaaS, and SaaS) adds clarity, aiding understanding of modern enterprise models. Adeptly addresses challenges, including lack of visibility, multitenancy issues, access management complexities, compliance concerns, and misconfigurations, offering valuable insights for organizations.
The recommended cloud security solutions (IAM, DLP, SIEM, Business Continuity, and Disaster Recovery) provide a comprehensive approach to risk mitigation. The article’s inclusion of NIST principles and the emerging technology CSPM further enriches its content.
In summary, the article serves as a valuable resource for organizations navigating cloud security complexities. Its blend of informative content, practical solutions, and insights into emerging technologies makes it an effective guide.
The war in Ukraine is a stark reminder of the potential for technology to be used for both good and evil. On the one hand, technology is being used to help people in a variety of ways, such as providing humanitarian assistance, connecting loved ones, and documenting war crimes. On the other hand, technology is also being used to harm people, such as carrying out airstrikes, delivering supplies to Russian forces, and spreading disinformation.
How technology is harming people
Drones: Drones are being used to carry out airstrikes on civilian targets, killing and injuring innocent people. For example, in March 2022, a Russian drone strike on a maternity hospital in Mariupol killed three people, including a pregnant woman and her child.
Robots: Robots are being used to clear minefields, defuse explosives, and evacuate civilians. However, there have been reports of robots being used to carry out attacks on civilians. For example, in April 2022, a Russian robot was reported to have opened fire on a group of civilians in Bucha.
Cyberwarfare: Cyberwarfare tactics are being used to disrupt communications, steal data, and launch denial-of-service attacks. These attacks can have a devastating impact on civilians, disrupting access to essential services and causing widespread economic damage. For example, in February 2022, a Russian cyberattack on Ukraine’s banking system caused widespread outages.
How technology is helping people
Humanitarian assistance: Technology is being used to provide humanitarian assistance to people affected by the war. For example, the World Food Programme is using drones to deliver food and other essential supplies to people in besieged areas.
Connecting loved ones: Technology is helping people to connect with loved ones who have been separated by the war. For example, the Red Cross is providing free phone calls and video chats to people who have been displaced by the conflict.
Documenting war crimes: Technology is being used to document war crimes and human rights abuses. For example, the Bellingcat investigative group is using social media footage and other open-source information to identify and track Russian war criminals.
Where tech in this war is heading
The war in Ukraine is driving technological innovation, as both sides are developing new weapons and tactics. For example, Russia is developing new types of drones, including kamikaze drones that can fly into targets and explode. Ukraine is developing new ways to counter Russian drones, such as using electronic warfare systems to disable them.
What tech will look like for future wars?
The war in Ukraine is a glimpse into the future of warfare, where technology will play an increasingly important role. In future wars, we can expect to see more use of drones, robots, and cyberwarfare. We may also see the development of new technologies, such as artificial intelligence-powered weapons that can make their own decisions about who to kill.
Other related news
Social media platforms are being used to spread disinformation and propaganda on both sides of the war in Ukraine. Russian and Ukrainian government agencies, as well as independent media outlets and individuals, are using social media to share information about the war. However, some of this information is inaccurate or misleading.
For example, Russian officials have used social media to spread false claims that the Ukrainian government is committing genocide against Russian speakers in Ukraine. Ukrainian officials have also used social media to spread false claims that the Russian military is using chemical weapons in Ukraine.
Both the Russian and Ukrainian militaries are using facial recognition technology to track and identify their opponents. Facial recognition technology can be used to identify individuals in photos and videos, even if they are wearing masks or other disguises.
For example, the Russian military is using facial recognition technology to identify Ukrainian soldiers and civilians who have been captured. The Ukrainian military is using facial recognition technology to identify Russian soldiers who have committed war crimes.
Conclusion
The war in Ukraine is a reminder of the potential for technology to be used for both good and evil. It is important to be aware of how technology is being used in the war, both to harm and to help people. We must also be prepared for the future of warfare, where technology will play an increasingly important role.
I prompted Google Bard by asking it firstly about current events. The wars taking place are very prevalent issues and many articles highlight the technology used. It didn’t take long before this AI engine was able to produce information about the wars and different perspectives on the destructive technologies.
As the world’s leading Internet television network with over 160 million members in over 190 countries, our members enjoy hundreds of millions of hours of content per day, including original series, documentaries and feature films. Of course, all our all-time favourites are right on our hands, and that is where machine learning has taken it’s berth on the podium. This is where we will dive into Machine Learning.
MONEY HEIST(2017)
Machine learning impacts many exciting areas throughout our company. Historically, personalization has been the most well-known area, where machine learning powers our recommendation algorithms. We’re also using machine learning to help shape our catalogue of movies and TV shows by learning characteristics that make content successful. Machine Learning also enables us by giving the freedom to optimize video and audio encoding, adaptive bitrate selection, and our in-house Content Delivery Network.
I believe that using machine learning as a whole can open up a lot of perspectives in our lives, where we need to push forward the state-of-the-art. This means coming up with new ideas and testing them out, be it new models and algorithms or improvements to existing ones.
Operating a large-scale recommendation system is a complex undertaking: it requires high availability and throughput, involves many services and teams, and the environment of the recommender system changes every second. In this we will introduce RecSysOps a set of best practices and lessons that we learned while operating large-scale recommendation systems at Netflix. These practices helped us to keep our system healthy:
1) reducing our firefighting time, 2) focusing on innovations and 3) building trust with our stakeholders.
RecSysOps has four key components: issue detection, issue prediction, issue diagnosis and issue resolution.
Within the four components of RecSysOps, issue detection is the most critical one because it triggers the rest of steps. Lacking a good issue detection setup is like driving a car with your eyes closed.
ALL YOUR FAVOURITE MOVIES AND TV SHOWS RIGHT HERE!
The very first step is to incorporate all the known best practices from related disciplines, as creating recommendation systems includes procedures like software engineering and machine learning, this includes all DevOps and MLOps practices such as unit testing, integration testing, continuous integration, checks on data volume and checks on model metrics.
The second step is to monitor the system end-to-end from your perspective. In a large-scale recommendation system there are many teams that often are involved and from the perspective of an ML team we have both upstream teams (who provide data) and downstream teams (who consume the model).
The third step for getting a comprehensive coverage is to understand your stakeholders’ concerns. The best way to increase the coverage of the issue detection component. In the context of our recommender systems, they have two major perspectives: our members and items.
Detecting production issues quickly is great but it is even better if we can predict those issues and fix them before they are in production. For example, proper cold-starting of an item (e.g. a new movie, show, or game) is important at Netflix because each item only launches once, just like Zara, after the demand is gone then a new product launches.
Once an issue is identified with either one of detection or prediction models, next phase is to find the root cause. The first step in this process is to reproduce the issue in isolation. The next step after reproducing the issue is to figure out if the issue is related to inputs of the ML model or the model itself. Once the root cause of an issue is identified, the next step is to fix the issue. This part is similar to typical software engineering: we can have a short-term hotfix or a long-term solution. Beyond fixing the issue another phase of issue resolution is improving RecSysOps itself. Finally, it is important to make RecSysOps as frictionless as possible. This makes the operations smooth and the system more reliable.
NETFLIX: A BLESSING IN DISGUISE
To conclude In this blog post I introduced RecSysOps with a set of best practices and lessons that we’ve learned at Netflix. I think these patterns are useful to consider for anyone operating a real-world recommendation system to keep it performing well and improve it over time. Overall, putting these aspects together has helped us significantly reduce issues, increased trust with our stakeholders, and allowed us to focus on innovation.
[1] Eric Breck, Shanqing Cai, Eric Nielsen, Michael Salib, and D. Sculley. 2017. The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction. In Proceedings of IEEE Big Data.Google Scholar
[2] Scott M Lundberg and Su-In Lee. 2017. A Unified Approach to Interpreting Model Predictions. In Advances in Neural Information Processing Systems 30, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett(Eds.). Curran Associates, Inc., 4765–4774.
