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  • Malware Detection with AI

    Published Date : September 21, 2018

    According to an Email Threat Report by intelligence-led security company FireEye, one in every 101 emails in the first half of 2018 had malicious intent. Therefore, having the right level of cyber security has become pertinent to minimise and control damage.

    Here, Artificial intelligence (AI) has been pitched as a potential solution which could learn to detect suspicious behaviour, stop cyber attackers in their tracks, and take some of the workload away from human teams. AI based security approach can allow organisations to confidently protect against today’s malware and predict malware of the future. According to report of Market Research Engine the Artificial Intelligence in Security Market is expected to exceed more than US$ 35 Billion by 2024.

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    In order to identify and foresee new threats of cybercrime, players in this space are constantly studying the evolution of technologies, capabilities and techniques.


    For instance, IBM Research has developed DeepLocker, a new breed of highly targeted and evasive attack tools powered by AI. It is developed to better understand how several existing AI models can be combined with current malware techniques to create a particularly challenging new breed of malware.

    Likewise, New York based Deep Instinct applies artificial intelligence’s deep learning to cyber security to protects against zero-day threats and APT attacks with unmatched accuracy. Deep Instinct safeguards the enterprise’s endpoints and/or any mobile devices against any threat, on any infrastructure, whether or not connected to the network or to the Internet.

    Further, California based Cylance applies artificial intelligence, algorithmic science and machine learning to cyber?. By coupling sophisticated math and machine learning with a unique understanding of a hacker’s mentality, Cylance provides the technology and services to be truly predictive and preventive against advanced threats.

    Similarly, Cambridge based Darktrace uses machine learning and AI algorithms to detect and respond to cyber-threats across diverse digital environments, including cloud and virtualized networks, IoT and industrial control systems. The technology is self-learning and requires no set-up, identifying threats in real time and updating its understanding as the environment changes.

    As malware detection techniques continue to evolve, with time AI will play a greater role. Although today human resources are involved in combating evasive malware, the recent developments in AI will dramatically lessen our reliance on human intervention.

    Credits : Akhil Handa,Pankaj Tadas

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