Security News > 2016 > April > AI system predicts cyber attacks using input from human experts (Help Net Security)

Today’s security systems usually fall into one of two categories: man or machine. So-called “analyst-driven solutions” rely on rules created by human experts and therefore miss any attacks that don’t match the rules. Meanwhile, today’s machine-learning approaches rely on “anomaly detection,” which tends to trigger false positives that both create distrust of the system and end up having to be investigated by humans, anyway. But what if there was a solution that could merge those … More →
News URL
http://feedproxy.google.com/~r/HelpNetSecurity/~3/l34TTYNvfjU/
Related news
- AI-Powered SaaS Security: Keeping Pace with an Expanding Attack Surface (source)
- MINJA sneak attack poisons AI models for other chatbot users (source)
- How AI and automation are reshaping security leadership (source)
- New ‘Rules File Backdoor’ Attack Lets Hackers Inject Malicious Code via AI Code Editors (source)
- Enterprises walk a tightrope between AI innovation and security (source)
- ⚡ THN Weekly Recap: GitHub Supply Chain Attack, AI Malware, BYOVD Tactics, and More (source)
- AI agents swarm Microsoft Security Copilot (source)
- How AI agents could undermine computing infrastructure security (source)
- After Detecting 30B Phishing Attempts, Microsoft Adds Even More AI to Its Security Copilot (source)
- Week in review: Chrome sandbox escape 0-day fixed, Microsoft adds new AI agents to Security Copilot (source)