Artificial Intelligence and Cybersecurity

The survey of global CEOs from PwC brings to light what global executives aim to achieve with generative AI in the near and long term.

A study revealed most organizations faced evolved cyberattacks, adding to the time and cost needed for remediation.

Zero-trust security runs more effectively with AI and ML. This allows IT teams and organizations to protect their networks properly.

GenAI can help by providing new tools for accurately analyzing cyber risks, streamlining process efficiencies, and helping insurers improve the security of buyers.

A recent study from the National Institute of Standards and Technology (NIST) and their collaborators has exposed the vulnerability of AI and machine learning systems to deliberate manipulation, commonly known as "poisoning."

Organizations must consider the security implications of using ChatGPT, as well as large language model (LLM) and LLM-based apps.

Versa Network’s AI director Sridhar Iyer gives us a deep insight into the benefits of AI to cybersecurity and the skills required to take full advantage.

The next few years will see AI tip the scales back and forth between threat actors and security teams protecting the enterprise. Collaboration with government is key to the tech industry coming out ahead.

AI-enhanced social media attacks are on the rise — that’s why security teams must foster a culture of continuous awareness training and adaptive defenses.

Sophos X-Ops’ exploration of cybercrime forums suggests many threat actors are still skeptical – and wrestling with the same issues and problems as the rest

The endpoint security market is becoming increasingly diverse as vendors incorporate AI, ML and zero trust.

In its plans to implement a White House executive order, CISA aims to strike a balance between promoting AI adoption for national security and defending against its malicious use.

GitHub’s chief security officer says AI won’t replace the need for security teams, but it will greatly enhance their work.

Generative AI has taken the world by storm but there’s still some confusion over its applicability in a cyber security context

Prompt injection, prompt extraction, new phishing schemes, and poisoned models are the most likely risks organizations face when using large language models.

There's growing interest in generative AI Isolation and comparable technologies to keep confidential data out of ChatGPT, Bard and other gen AI sites

The nearly 100-page paper, titled “Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations,” provides a comprehensive overview of the cybersecurity and privacy risks that come with the rapid development of both predictive and generative AI tools over the last few years.

To realize the importance of prioritizing cybersecurity, it’s helpful to understand the cyber risks to AI safety.

LLMs are uniquely positioned to take on the challenge of predicting potential intrusion attempt patterns across endpoints using collected attack data.

Generative AI tools help bad actors easily craft sophisticated attacks. CISOs are investing in AI-native cybersecurity solutions to fight back.

As we stand at the precipice of 2024, the intersection of artificial intelligence (AI) and cybersecurity looms large, with phishing attacks emerging as a focal point of concern. The integration of AI is poised to redefine the threat landscape, introducing unprecedented levels of complexity and stealth to these attacks.

Generative AI holds immense potential for the future of cybersecurity. By harnessing its ability to process and analyze vast amounts of data, it's capable of transforming how we detect, investigate, and respond to cyber threats.

A balance across technological capabilities, ethical practices and regulatory frameworks will be vital.

The integration of large language models into many third-party products and applications present many unknown security and privacy risks. Here’s how to address them.

A software engineer implemented generative AI cybersecurity and shared the pros and cons of integrating LLMs into your cybersecurity product.