Artificial Intelligence and Cybersecurity

As AI becomes integral to systems brought into the enterprise ecosystem it is increasingly critical for security teams to know where it is and reduce its risks.

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

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 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.

With today’s large language models, we can create a new type of tool that securely applies the power of AI to an organization’s data.

Telling AI about your cybersecurity issue and asking for a solution can result in the AI telling someone else about your problem. It might take a while to implement a solution, and until then, the AI will “chat” about your issue with everyone who asks for it.

The outcry over Zoom's tweak to its data policy shows how the race to build more powerful AI models creates new pressure to source training data—including by juicing it from users.

It's time to get real about what it takes to set and enforce cybersecurity and resilience standards for AI risk management in the enterprise.

ChatGPT and other generative AI platforms can be productivity boosters but also pose data security risks.

Artificial intelligence in business is on the rise. Keep an eye out for these data security threats to artificial intelligence.

Adversarial attacks present a growing threat to commercial AI and machine learning systems. Fortunately, some solutions exist.

Just the way the deficiency of vitamin and poor hygiene can make the human body fell seriously ill, the deficient access points and lack of hygiene in cyber environments can lead to cyberattacks in the hyper-connected workplaces.

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

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

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."

As the mass adoption and application of AI are fairly new, the security of AI is not yet well understood. Why we must change that — now.

The emergence of generative AI is reshaping cyber risks for organizations - insights from CISOs reveal global concerns regarding new AI advancements and the proactive steps being taken.

Avoiding generative AI security tools due to fear, uncertainty and doubt may be more of a risk than diving headlong into the conversation.

The obsession with all-things generative AI signals a need for business leaders to rethink their security approaches.

New technologies always change the security landscape, but few are likely to have the transformative power of generative AI. As platforms like ChatGPT continue to catch on, CISOs need to understand the unprecedented cybersecurity risks they bring—and what to do about them..

ChatGPT, the dialogue-based AI chatbot capable of understanding natural human language, has become another icon in the disruptor ecosystem.

Artificial intelligence in the form of intelligent automation is challenging consumer trust and safety -- and businesses must respond.

Don’t believe the hype. The promise is that artificial intelligence is the Holy Grail for addressing the issue of how to secure all that data floating around in the cloud. Let’s slow down a bit. It might not solve every single problem.