Artificial Intelligence & Machine Learning
Real-Time Proactive Cyber Incident Response with Self-Healing and Self-Learning systems
Cyberattacks are coming from everywhere and targeting everything. Millions of new devices are being connected, providing larger attack surfaces for attackers to exploit. Sophisticated attacks are being devised every day to circumvent current security controls. Organizations are spending a lot of time and money in responding to cyber incidents post cyberattack. In this region organizations spend an average of US$6.5 million per incident.
See Also: 4 Key Elements of an ML-Powered NGFW
A forward-thinking approach is crucial. Enterprises should be looking at building systems that are self-learning and have the capability to self-heal itself after a cyberattack.
The session will discuss:
- Self-learning, which means, systems should be equipped to understand their normal and abnormal behavior;
- Self-healing, where the systems should be enriched to be able to roll back to previous good i.e. normal state;
- Incorporating threat intelligence, machine learning, and behavior analysis to proactively identify threats and respond.
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