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Implications of generative AI for enterprise security

CIO

The use of AI presents significant issues around sensitive data loss, and compliance. As it stands today, most Generative AI tools do not have concrete data security policies for user-provided data. Large learning models (LLMs) that back these AI tools require storage of that data to intelligently respond to subsequent prompts.

Security 779
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AI & the enterprise: protect your data, protect your enterprise value

CIO

The premise was that enterprises needed to secure their critical data more stringently in the wake of data hacks and emerging AI processes. I wrote, “ It may be even more important for the security team to protect and maintain the integrity of proprietary data to generate true, long-term enterprise value.

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Generative AI: 5 enterprise predictions for AI and security — for 2023, 2024, and beyond

CIO

Zscaler Enterprises will work to secure AI/ML applications to stay ahead of risk Our research also found that as enterprises adopt AI/ML tools, subsequent transactions undergo significant scrutiny. The data privacy and security risks of AI applications themselves Not all AI applications are created equal.

Security 835
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Why Is Data Loss Prevention is Crucial for Business?

Smart Data Collective

Data loss is a serious problem for many businesses. An estimated 94% do not survive a catastrophic data loss. Data loss prevention (DLP) strives to protect your business data from inside or outside compromise. This includes data leakage, data loss , misuse of data, or data compromised by unauthorized parties.

Loss 315
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Sharing Responsibility for Data Security in the Cloud

CIO

As organizations shape the contours of a secure edge-to-cloud strategy, it’s important to align with partners that prioritize both cybersecurity and risk management, with clear boundaries of shared responsibility. The security-shared-responsibility model provides a clear definition of the roles and responsibilities for security.”.

Security 725
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Understanding the security shared responsibility model in an as-a-service world

CIO

As organizations shape the contours of a secure edge-to-cloud strategy, it’s important to align with partners that prioritize both cybersecurity and risk management, with clear boundaries of shared responsibility. The security-shared-responsibility model provides a clear definition of the roles and responsibilities for security.”

Security 596
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Generative AI and the Transformation of Everything

CIO

The implications for enterprise security For most enterprises, the present moment is an educational process. That data leakage is the principal security concern regarding generative AI of enterprises today. Another major concern is copyright infringement and intellectual property (IP). At least, not yet.