Cybersecurity Teams can Interpret Data with AI Tools
Hacking has reached a new level today. Many define cybersecurity as a cat-and-mouse game on a regular basis. Hackers and cybercriminals have always been one or two steps ahead of law enforcement as the latter continually pursue the ever-advancing plans of the former to commit data theft, property damage, or other security infringements — often spotting breaches long after such knowledge is helpful. The cybersecurity cat is still slower and therefore unable to anticipate the next move of the mouse. And capturing the cybercriminal mouse evades. So how can cybersecurity predict the next move of the cybercriminal? As hackers become smarter and much more determined, a crucial part of the solution will be artificial intelligence.
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AI has just entered fields such as healthcare, assembly, education, and cybersecurity as of now. For the existing digital world, cybersecurity is the main concern, and there are still vulnerabilities regarding the effect of AI. Similarly, corporations, as well as government sectors, are trying to ace AI and Machine Learning for information security and open new doors in the specific field. In the cybersecurity state, the rise of e-commerce and the switch to a mobile-first society plays an important role. Fraudsters shift their attacks to other vectors on a daily basis, making modeling attacks and attacking behaviors almost difficult for security teams. AI teaches bots to be more human-like with the rise of AI. Mobile bot farms where bots seem to be more human-like on several thousands of devices are just one excellent illustration–making differentiating between real users and non-users and people versus bots more difficult. Read More…
