Security News > 2016 > April > AI system predicts cyber attacks using input from human experts (Help Net Security)
2016-04-19 12:50
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
- Microsoft Fixes AI, Cloud, and ERP Security Flaws; One Exploited in Active Attacks (source)
- Update your OpenWrt router! Security issue made supply chain attack possible (source)
- CERT-UA Warns of Phishing Attacks Targeting Ukraine’s Defense and Security Force (source)
- CrowdStrike Survey Highlights Security Challenges in AI Adoption (source)
- Cross-Domain Attacks: A Growing Threat to Modern Security and How to Combat Them (source)
- New AI Jailbreak Method 'Bad Likert Judge' Boosts Attack Success Rates by Over 60% (source)
- Preventing the next ransomware attack with help from AI (source)
- How AI and ML are transforming digital banking security (source)
- Patch Tuesday: January 2025 Security Update Patches Exploited Elevation of Privilege Attacks (source)
- Balancing usability and security in the fight against identity-based attacks (source)