AI Is The Future of Cybersecurity

AI Is The Future of Cybersecurity

Can Artificial Intelligence solve all the problems of future? Can AI make it easier to secure and protect sensitive data and classified information? Can AI strengthen cyber security enough not to be breached by hackers and cybercriminals? The answer lies in the exponentially developing technology of machine learning. The evolution of technology has come along with the dangers of cybercrime. Every day there is a new threat for the cyber world and a need to find protection from that threat. Machine learning can ably secure the network by detecting threats at an advanced stage and counter the same.

At times machine learning is considered not to be true AI but its prospected implications for cyber security gives hope to many. In simple words, machine learning process means systems enabled with AI applications automatically learning and improving from their experiences without any outside programming intervention. The tech world is divided into two opinions, some favoring machine learning as future of cyber security and some skeptical of its capabilities.

The scalability and automation capability of machine learning can efficiently analyze large pool of data, correlate simultaneous events and learn to separate a typical from typical behaviors, thus enabling it to detect potential threats even at advance level. Security products having machine learning features can work on zero-trust security model and thus the smallest level of suspicion or dormant threat can be detected and removed. This model can surely surpass human capabilities of a data scientist but the still unexplored areas in research field give it a grey shade to be the best option for cyber security.

Today’s sophisticated cybercriminals are posing persistent threats to the cyber world with new and even more dangerous malware, botnets and viruses than before. The solutions coming with machine learning sounds promising in such a scenario. The abilities of machine learning in endpoint detection, critical response system, adaptive baseline behavior and predictive analysis can secure the perimeters of cyber forts and protect sensitive data. The pattern detection algorithms, advanced analytics, and automated alerting systems make machine learning an effective tool to fight cybercriminals.

Machine learning adroitly addresses the security concerns by analysis of security data, time-series data, log data, contextual data, asset data and data from directories and special purpose applications on the basis of past threats detection array and behavioral analytics reports. Although it addresses some of the concerns of cyber security yet threat detection at an advance stage and intelligent threat response needs more research and developments.

Corporate organizations, governments, and world forums at different levels are fastening their belts and preparing targeted development projects to counter cybercrime and secure the cyber world. Whether it was EU General Data Protection Regulation (GDPR), UN Group on Cybercrime and Cyber Security, UN Congress, security activities by intelligence agencies or collaborated initiatives by big corporate originations for cyber security, AI applications and machine learning are the hope for network security and advance detection of threats.

Cybercrime is among one of the fastest growing transnational crimes as per UN reports and it is adversely impacting individuals’ lives and global businesses. AI and machine learning have tremendous potential to counter the issue and safeguard the cyber world. The problem is equally persistent for small organizations and corporate giants, thus multiple levels of advance security are the need of the hour.

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