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Home»BLOCKCHAIN NEWS»Leveraging AI to Strengthen Cybersecurity Measures: 3 Key Strategies
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Leveraging AI to Strengthen Cybersecurity Measures: 3 Key Strategies

By Crypto FlexsSeptember 8, 20243 Mins Read
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Leveraging AI to Strengthen Cybersecurity Measures: 3 Key Strategies
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Caroline Bishop
September 6, 2024 15:46

Learn how AI is solving cybersecurity challenges with rapid ingestion, data protection, and enhanced access control, according to the NVIDIA blog.





As generative AI continues to transform the enterprise, it also brings with it unique cybersecurity challenges. According to the NVIDIA blog, AI itself can be a critical tool in addressing these risks, creating a flywheel of progress in cybersecurity.

AI guardrails prevent rapid injections

Generative AI services are vulnerable to malicious prompts designed to disrupt the underlying language model or gain unauthorized data access. Direct injections can overwrite system prompts, while indirect injections manipulate input from external sources. AI guardrails, which act as safety barriers, can prevent such prompt injections by keeping AI applications on track and on topic. NVIDIA’s NeMo Guardrails software is one such solution that allows developers to enhance the reliability, safety, and security of generative AI services.

AI detects and protects sensitive data

Large-scale language models (LLMs) can sometimes expose sensitive information in their responses. Multi-factor authentication and increasingly complex credentials have expanded the scope of what is considered sensitive data. To mitigate this risk, it is essential to remove or hide sensitive information from AI training data. Given the massive datasets involved, AI models are more effective than humans at ensuring data cleanliness. NVIDIA’s Morpheus framework enables enterprises to build AI models and accelerated pipelines that detect and protect sensitive information on corporate networks.

AI can help strengthen access control

Hackers can exploit LLM to gain unauthorized access to organizational assets. Implementing security design principles such as granting only the least privilege and continuously evaluating privileges can limit this risk. AI can also support access control using a separate inline model trained to detect privilege escalation based on the output of LLM.

Start your journey to cybersecurity AI

There is no single solution to cybersecurity. It requires evolving countermeasures and responses. Organizations that effectively use the latest tools and technologies are better prepared to protect AI systems. As organizations become more comfortable with AI, it is important to deploy AI for meaningful use cases. NVIDIA and its partners provide full-stack solutions in AI, cybersecurity, and cybersecurity AI.

In the future, the relationship between AI and cybersecurity will become increasingly symbiotic, creating a virtuous cycle where each reinforces the other. Ultimately, users will trust AI as another form of automation. For more information about NVIDIA’s cybersecurity AI platform and its applications, visit the NVIDIA blog.

Image source: Shutterstock


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