A naukri.com initiative
Medium
3w
337
Image Credit: Medium
AI in Cybersecurity: The War on Two Fronts
- AI models in cybersecurity can detect zero-day attacks, lateral movement, and insider threats.
- Automated SOAR platforms enhance incident response by accelerating triage and containment.
- AI assists in threat intelligence by summarizing incidents and digesting open-source intel.
- Predictive analytics are used for proactive threat hunting to identify early-stage indicators of compromise.
- Companies like Google Chronicle, Microsoft Sentinel, and Darktrace leverage AI in cybersecurity.
- Deepfakes and AI-powered techniques are used in hyper-targeted phishing campaigns.
- AI helps threat actors model user behavior to evade detection and launch targeted attacks.
- Recalibrating employee awareness training is recommended to include AI-related modules.
- AI-driven upgrades in software and hardware help in AI-aware cybersecurity measures.
- Continuous red teaming with AI involves simulating adversarial AI scenarios to stress test cybersecurity.
- Challenges include cross-border AI model usage, deepfake mitigation, and ensuring AI decisions are audited.
- Solutions involve deploying AI endpoint agents and ML-based deception technology.
- AI-vs-AI simulations are used to test infrastructure against evolving threats.
- Emphasis on employee training and AI-aware upgrades in cybersecurity are crucial for cyber resilience.
- Threat actors are utilizing AI to not only hack systems but also manipulate human behavior at scale.
- AI explainability clauses and understanding AI decisions are key considerations in cybersecurity measures.
Read Full Article
20 Likes
For uninterrupted reading, download the app