AI models are increasing efficiency, but come with new hidden vulnerabilities that can be a struggle to keep up with and safeguard against. The possible Malicious attacks can lead to business disruption and data breaches of highly sensitive data.
Identifying your AI model and its vulnerabilities is crucial. Many...
AI is rapidly transforming industries, but its power comes with a hidden vulnerabilities: traditional security methods struggle to keep pace with the unique threats facing AI models.
Malicious attacks can harm your AI and damage your business.
The biggest challenge? Knowing what AI models you even have. Many...
Forrester senior analyst Tope Olufon discusses how CISOs face the challenge of shadow IT with generative AI. CISOs need to approach AI as they would any other technology, he says. "Create a threat model, not just based on best practices, but for your organization, and then build security for that."
As companies adopt generative AI tools, exfiltration of sensitive data remains a persistent challenge. Andres Andreu, deputy CISO, Hearst, shares insights into the limitations of relying on policies and the crucial role of collaboration with AI providers to mitigate potential data breaches.
In the latest "Proof of Concept," panelists Sam Curry of Zscaler and Heather West of Venable LLP discuss the crucial role of explainability and transparency in artificial intelligence, especially in areas such as healthcare and finance, where AI decisions can significantly affect people's lives.
A data security firm led by a former CA Technologies executive raised $60 million to boost both organic and inorganic expansion around data and compliance. The round will build on the firm's new data hygiene tool as well as its new controls for detecting and tracking model access to sensitive data.
The U.S. healthcare sector needs to closely watch government regulatory and legislative developments involving artificial intelligence, including the European Union AI Act, said Lee Kim, senior principal of cybersecurity and privacy at the Healthcare Information and Management Systems Society.
The rapid rise of artificial intelligence technologies poses new risks. Enterprises using AI must regularly scan for prompt injection attacks, implement transparency in the supply chain and reinforce built-in software controls to serve their company's security needs, Microsoft said.
Onboarding, offboarding, ongoing assessments - there are many ways in which Generative AI can augment human oversight of third-party risk management. Ed Thomas of ProcessUnity shares real-world examples of how enterprises are deploying Gen AI to improve TPRM efficiency.
In the pursuit of flexibility and competitiveness, many organizations have welcomed a diverse ecosystem of consultants, collaborators, vendors, and non-human entities. The challenge lies in effectively managing the identities of these third parties, including service accounts, bots, and smart devices, dispersed across...
Machine learning systems are vulnerable to cyberattacks that could allow hackers to evade security and prompt data leaks, scientists at the National Institute of Standards and Technology warned. There is "no foolproof defense" against some of these attacks, researchers said.
In conjunction with a new report from CyberEd.io, Information Security Media Group asked some of the industry's leading cybersecurity and privacy experts about 10 top trends to watch in 2024. Ransomware, emerging AI technology and nation-state campaigns are among the top threats.
AI holds tremendous promise for both the administrative and clinical sides of healthcare, but obstacles still remain. One of the major hurdles is tied to patient privacy and the sharing of vast amounts of data needed to effectively tune AI models. What are some workarounds?
In the future, deepfake technology will have a significant impact on newer forms of authentication such as voice and facial recognition and pose new challenges to defenders, said Ofer Friedman, chief business development officer at AU10TIX, an Israel-headquartered identity verification company.
As Congress weighs potential legislative and regulatory guardrails for the use of AI in healthcare, issues such as human oversight, privacy and security risk need close attention, said healthcare industry experts who testified during a House Energy and Commerce subcommittee hearing on Wednesday.
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