Artificial Intelligence and Cybersecurity

AI is ushering in a multitude of opportunities for businesses, but keeping AI on track demands significant work.

In this respect, AI enables us to do more in less time; an enormous benefit to cybersecurity teams struggling with talent shortages.

Recent technological advances in hardware-based cybersecurity enable an “oversight system” to monitor and guarantee the integrity of incoming data and the confidentiality of outgoing data.

a16z General Partner Zane Lackey and Partner Joel de la Garza recently sat down with us to discuss the state of security in 2024. They addressed the top concern for CISOs: the impact of generative AI on enterprise security. Here’s what they had to say about the key considerations for technology adoption and strategie

The only way to fight against AI is with AI – but you must master the basics first

In this episode of the SecurityANGLE, host Shelly Kramer, managing director and principal analyst at theCUBE Research, is joined by analyst, engineer and theCUBE Collective community member Jo Peterson for a conversation about the top four generative artificial intelligence cyber risks that keep CISOs up at night.

Generative AI could be the holy grail of DevSecOps, from writing secure code and documentation to creating tests. But it could be a major point of failure if not used correctly.

Large language models may boost the capabilities of novice hackers but are of little use to threat actors past their salad days, concludes a British governmental evaluation

A proactive, coordinated effort can reduce the chances that manipulations will impact model performance and protect algorithmic integrity.

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

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

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

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.

Security teams should understand their providers' approach to data privacy, transparency, user guidance, and secure design and development.

Experts at the RSA Conference urged cyber professionals to lead the way in securing AI systems today and pave the way for AI to solve huge societal challenges

Meanwhile, 36% were either neutral or disagreed that AI would play an important role in improving their cybersecurity.

Two surveys by tech vendors reveal a significant slowdown in AI adoption as business and IT leaders consider the legal and practical ramifications.

Five ways generative AI can help with the cybersecurity skills shortage — from lowering the bar to entry to improving collaboration.

Threat actors are starting to use artificial intelligence, but too many executives aren't prepared for the risks.

Google Security Engineering and The Carnegie Mellon University Software Engineering Institute in collaboration with OpenAI have sorted through the hype - and done some serious thinking and formal research on developing "better approaches for evaluating LLM cybersecurity" and AI-powered patching: the future of automated vulnerability fixes. This is some great formative framing of the challenges ahead as we collectively sort out the implications of the convergence of generative AI and future cyber capabilities (offensive and defensive).

For AI to reach its full potential across enterprises, it requires an entirely new tech stack, one with security designed to start with software supply chains and model development.

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.

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

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

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.