Читать книгу Artificial Intelligence and Data Mining Approaches in Security Frameworks - Группа авторов - Страница 14

AI’s vital job is to offload work from human cyber security engineers presently, to deal with the depth and detail that humans cannot tackle effectively. Advancement in machine learning technology implies that AI applications can also automatically adapt to changes in threats and spot issues as they emerge.

Cyber security needs that AI tools and platforms can help to meet:

Data Extent

People get confused immediately when confronted with huge amounts of log information and cautions delivered by the present frameworks. Simulated intelligence programming running on today’s powerful processors can go through more data in minutes than humans could handle in months. Thus, it can also account for issues and inconsistencies while taking care of enormous volumes of security information.

Threat needles

Cyber threat hunting is a constant proactive search through networks and data sets to detect threats that elude existing computerized tools.

Digital lawbreakers are now inside numerous frameworks, waiting to complete their attacks. They can frequently escape people. But AI can quickly examine different circumstances to detect the threat needles compared to malicious activity.

Optimization of Response

Artificial intelligence can accelerate recognition of certifiable issues, quickly cross-referencing various alerts and sources of security information. The priorities of the incidents to be dealt with will still be the domain of human cyber security experts but they can be further helped by AI systems that will increase speed of recognition and reaction times.

AI arms race

Cyber criminals today are already equipped with advanced AI techniques. AI technology in general can be a boon or a bane. Programmers can easily utilize the most recent tools to launch more sophisticated attacks, each one being more dangerous. It has become an arms race where AI is the main exponent on both sides [2, 3].