Utilizing generative AI and blockchain among Trend Micro’s top five cybersecurity challenges for 2024
Posted: February 2, 2024 8:06 AM Updated: February 2, 2024 8:06 AM
Correction and fact check date: February 2, 2024, 8:06 AM
briefly
Trend Micro has identified five cybersecurity challenges that organizations’ cyber defenses will face in 2024 that require attention.
US cybersecurity company Trend Micro has identified five key security threat trends for 2024, including cloud-native worms, data poisoning of ML/AI systems, supply chain attacks, generative AI-based social engineering scams, and blockchain exploits.
Rapid advances in generative AI have increased the potential for new cyber threats, according to cybersecurity firms. Ransomware continues to see an upward trend as more cybercriminals target data exfiltration. At the same time, supply chains face greater risks from malicious actors.
For example, Sophos, a British cybersecurity solutions provider, released two reports highlighting the integration of AI in cybercrime. In its first report, titled “The Dark Side of AI: Massive Fraud Campaigns Enabled by Generative AI,” Sophos said fraudsters could exploit technologies like ChatGPT to commit widespread fraud in the future while requiring minimal technical expertise. Shows you how.
There is no doubt that the likelihood of malicious actors leveraging generative AI for large-scale fraud is at an all-time high. Trend Micro has identified five cybersecurity challenges that organizations’ cyber defenses will face in 2024 and that will require attention.
Cloud-native worms targeting cloud environments
Cloud-native worms that target cloud environments leverage automation, an important tool for cybercriminals, to spread quickly and wreak havoc within cloud systems. Given the unique vulnerabilities and misconfigurations common in cloud environments, the frequency and severity of these attacks is expected to increase. The interconnected nature of cloud infrastructure provides an ideal breeding ground for these worms to spread, making containment a difficult task for cybersecurity experts.
Data addiction in machine learning and AI systems
Data poisoning represents a potential threat as cybercriminals exploit training data vulnerabilities to compromise AI model integrity. These manipulations greatly amplify the potential impact of cyberattacks by opening up avenues for exfiltration, extortion, and sabotage. Threat actors can disrupt the functionality of ML and AI systems by infiltrating and compromising training data, posing significant risks to organizations that rely on these technologies for critical decision-making processes.
Supply chain attacks on CI/CD systems
Supply chain attacks targeting continuous integration/continuous delivery (CI/CD) systems have emerged as an attractive strategy for cybercriminals due to their broad reach over a wide range of potential victims. By compromising the software development supply chain, attackers can inject malicious code that weakens the entire IT infrastructure, impacting numerous interconnected parties.
Social engineering scams using generative AI
Generative AI-based social engineering scams introduce a new dimension to traditional phishing schemes by leveraging advanced AI algorithms to generate powerful fake messages. Crafted with high reliability, these messages increase the likelihood of successful social engineering attacks, such as business email compromise (BEC). As generative AI technology advances, the potential to create sophisticated audio/video deepfakes further amplifies the threat landscape, challenging cybersecurity professionals to identify and mitigate these attacks.
Blockchain utilization
Blockchain use is not yet widespread, but it is raising increasing concerns as private blockchains gain attention for managing internal financial transactions. Attackers can exploit vulnerabilities within these systems to gain unauthorized access and execute extortion schemes. As organizations increasingly adopt private blockchains for their security benefits, they must remain alert to potential vulnerabilities and implement robust security measures to protect sensitive financial data from exploitation by malicious actors.
As cyber threats become increasingly sophisticated, organizations must focus on protection at all points of the attack lifecycle and implement multidimensional security based on superior threat intelligence.
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About the author
Kumar is an experienced technology journalist specializing in the dynamic intersection of emerging fields including AI/ML, marketing technology, cryptocurrency, blockchain, and NFTs. With over three years of experience in the industry, Kumar has established a proven track record in crafting compelling narratives, conducting insightful interviews, and providing comprehensive insights. Kumar’s expertise lies in producing impactful content, including articles, reports and research publications for prominent industry platforms. With a unique skill at combining technical knowledge and storytelling, Kumar excels at communicating complex technical concepts in a clear and engaging way to diverse audiences.
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Kumar is an experienced technology journalist specializing in the dynamic intersection of emerging fields including AI/ML, marketing technology, cryptocurrency, blockchain, and NFTs. With over three years of experience in the industry, Kumar has established a proven track record in crafting compelling narratives, conducting insightful interviews, and providing comprehensive insights. Kumar’s expertise lies in producing impactful content, including articles, reports and research publications for prominent industry platforms. With a unique skill at combining technical knowledge and storytelling, Kumar excels at communicating complex technical concepts in a clear and engaging way to diverse audiences.