Security News
As organizations handle increasing amounts of data daily, AI offers advanced capabilities that would be harder to achieve with traditional methods. In this Help Net Security video, Tyler Young, CISO at BigID, explores AI's challenges, triumphs, and future in cybersecurity.
To manage an environment of increasing risks and limited resources, healthcare internal audit and compliance departments must align their risk assessments and audit work plans to areas most vital to achieving the strategic goals and business objectives of their organizations, according to Kodiak. To unlock these benefits, healthcare provider organizations need to mitigate a host of risks, such as storing and securing enormous amounts of data that is mostly protected health information, protecting the training data for AI models from malicious actors seeking to introduce bad data, and rooting out bias that can creep into in AI algorithms because of a lack of data for gender, sexual orientation, race and ethnicity.
In nearly every segment of our lives, AI (artificial intelligence) now makes a significant impact: It can deliver better healthcare diagnoses and treatments; detect and reduce the risk of...
All types of cyber threat actor are already using artificial intelligence to varying degrees, UK National Cyber Security Centre's analysts say, and predict that AI "Will almost certainly increase the volume and heighten the impact of cyberattacks over the next two years." Although AI is used by all types of cyber threat actors, it will particularly benefit less-skilled ones, as it will enhance their ability to carry out social engineering attacks and create convincing phishing emails.
AI and ML deserve the hype they get, but the focus can't always be on the glitz. As these advances to deliver real benefits, there's a slew of more mundane actions that have to be taken-and in 2024, this is where we'll see some of the most exciting moves.
The U.K.'s National Cyber Security Centre has released a new study that finds generative AI may increase risks from cyber threats such as ransomware. The report sorted threats by potential for "Uplift" from generative AI and by the types of threat actors: nation-state sponsored, well-organized and less-skilled or opportunistic attackers.
The agency says cybercriminals already use AI for various purposes, and the phenomenon is expected to worsen over the next two years, helping increase the volume and severity of cyberattacks. The NCSC believes that AI will enable inexperienced threat actors, hackers-for-hire, and low-skilled hacktivists to conduct more effective, tailored attacks that would otherwise require significant time, technical knowledge, and operational effort.
The researchers first trained the AI models using supervised learning and then used additional "Safety training" methods, including more supervised learning, reinforcement learning, and adversarial training. If an AI system learned such a deceptive strategy, could we detect it and remove it using current state-of-the-art safety training techniques? To study this question, we construct proof-of-concept examples of deceptive behavior in large language models.
An article published today by the UK National Cyber Security Centre suggests there is a "Realistic possibility" that by 2025, the most sophisticated attackers' tools will improve markedly thanks to AI models informed by data describing successful cyber-hits. At the lower end, cyber criminals who employ social engineering are expected to enjoy a significant boost thanks to the wide-scale uptake of consumer-grade generative AI tools such as ChatGPT, Google Bard, and Microsoft Copilot.
You can find them by searching for OpenAI chatbot warning messages, like: "I'm sorry, I cannot provide a response as it goes against OpenAI's use case policy." I hadn't thought about this before: identifying bots by searching for distinctive bot phrases.