Automated Cybersecurity

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Prof Brijesh Sharma

As time goes on, it seems that there’s very little left in the world that is purely “analog” anymore. The business world is digital nowadays, and there are many benefits attached to that reality. It is abundantly clear, the future will be machine driven, and central to this future are the super advanced algorithms, which are fueled by the data they are trained on. Every ad you see, every car driving itself, every medical diagnosis provided by a machine will be based on your data and lots of it. Most would argue that companies without these technologies will fail.  

The caveat is that there are inherent risks that come along with the digitization of society, and cybercriminals know it. Now that the IoT has grown and the world is becoming increasingly wireless, we’ve finally reached the point where even small businesses and private citizens are falling victim to data breaches and cyberattacks.

The problem is that as sophisticated as technology and IT security get, malicious actors, are always one step ahead. Organizations are struggling to keep up and adapt to such a harsh digital landscape, while simultaneously recognizing that there’s no doing business outside of the said landscape. This presents a catch-22 that becomes more visible within IT security every day.

Fortunately, the same advanced analytics and machine learning are presenting new opportunities in security fields. These much-needed innovations are bringing a modicum of certainty back to a nebulous arena and proving to be effective instruments. 


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