In Cybersecurity, systems that can learn and adapt to evolving threats are much more competent than " fine-tuned " systems to identify these threats. Consequently, using artificial intelligence (AI) for cybersecurity provides a compelling use case. Typical security systems like firewalls, antivirus or intrusion detection systems (IDS) can only detect threats they are already familiar with. This leaves enough room for zero-day attacks and other matured forms of malware. A security system that's powered by AI can identify evolving threats and even adjusts its defences to restrict the danger until it can be effectively neutralized.

Cognitive computing, an advanced type of artificial intelligences, leverages various forms of AI, including machine-learning algorithms and deep-learning networks, that get stronger and smarter over time. Watson for Cyber Security, IBM's cognitive AI, learns with each interaction to connect the dots between threats and provide actionable insights. The result: You can respond to threats with greater confidence and speed. Watch the video to see how IBM QRadar Advisor with Watson helps you get a head start in assessing incidents to reduce your cyber risk.

Organizations continue to embrace the Internet of Things (IoT), the cloud, and mobile technology. This has influenced considerable changes in the threat landscape and created more vulnerability points. Cybercriminals are leveraging these new vulnerability points to develop and launch sophisticated, high-volume, multi-dimensional attacks. Such attacks mean that data is at risk, and organizations must analyze potentially malicious files. Using artificial intelligence software, organizations can process large volumes of threat data and adequately prevent and respond to breaches and hacks.