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Cybersecurity Snapshot: 6 Best Practices for Implementing AI Securely and Ethically

Tenable

But how can you ensure you use it securely, responsibly, ethically and in compliance with regulations? Check out best practices, guidelines and tips in this special edition of the Tenable Cybersecurity Snapshot! How can the security team contribute to these efforts? We look at best practices for secure use of AI.

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Prioritizing AI? Don’t shortchange IT fundamentals

CIO

Fundamentals like security, cost control, identity management, container sprawl, data management, and hardware refreshes remain key strategic areas for CIOs to deal with. Data due diligence Generative AI especially has particular implications for data security, Mann says.

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Creating a Security Program with Less Complexity and More Visibility

Palo Alto Networks

Developing a strong security program is like tending a garden. Meanwhile, the same old problems hold defenders back – alert fatigue, improper permissions and inadequate authentication, among others. The greatest misconception about cybersecurity is that programs can catch up overnight with silver-bullet solutions.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning - AI

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. We first delve into the vulnerabilities, threats, and risks that arise from the implementation, deployment, and use of LLM solutions, and provide guidance on how to start innovating with security in mind.

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How to manage cloud exploitation at the edge

CIO

However, this shift requires a thorough understanding of the security implications and how a business can protect its data and applications. As with all technology introductions, it’s important to have clear security policies, tools, processes, and training. Watch on-demand here. How is the cloud being attacked and why?

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Cybersecurity 2030

Haft of the Spear

Discussions about cybersecurity overwhelmingly focus on the recent, which are our responses to the design and engineering decisions of the past. Yet in cybersecurity [1] the path towards a brighter future is rarely discussed. We want things to be “better” but what does that mean? Just as important: better for whom?

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SaaS security: challenges, trends and best practices to follow 

Openxcell

Organizations should assess their cybersecurity posture on all fronts. This article explores what SaaS security is, its challenges, real-life examples, best practices, and trends for SaaS security. First, let’s start with what SaaS security is. What is SaaS security? Why is SaaS security important?

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