Doing More with Less using AI

In the recent years, security professionals have been struggling to keep a watch on corporate networks for data breaches and cyberattacks. In the recent advent of cyber crimes, myriad of private information from organizations and individuals is being leaked into the dark web, with no defined future of what the information would be used for.    

The compromise of a corporate network could be the gateway to information theft and ransomware attacks to stall the operations of a business and hold it to a ransom. Recent innovations in the field of cybersecurity can prove pivotal in the substantial reduce in the financial cost and liability on cyber professionals, all while working with a small workforce.

With machine learning and artificial intelligence (AI) going hand in hand, predictive analytics can be expected to be a game changer. Predictive analytics enables strong control in the backdrop of constant attacks that often lead to prevention of data breaches or system compromise. AI and machine learning would imply deep learning, Big Data algorithms would work together to perform diversified tasks such as finding anomalies in systems, abnormal traffic, insider behavior anomalies, and other key indicators of breach.   

It is believed that the combination of predictive analysis, AI, and automation can help cybersecurity personnel make use of technological advantages and achieve positive outcomes from minimal efforts. While cybersecurity posture can be strengthened through the trifecta of predictive analytics, AI, and automation, it can also be used to reduce the number of false alarms, thus streamlining cumbersome manual tasks.