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The Impact of AI and ML on Cybersecurity
Machine learning and artificial intelligence (AI) are evolving as a new trend in cybersecurity—enabling applications to learn and adapt through experience. It emulates human cognition i.e. learning based on experience and patterns, rather than by cause and effect. Advancements in machine learning allow machines to teach themselves how to build models for pattern recognition. Over the past few years, there has been a tremendous rise in AI and ML technologies for organizations. Among these, most can be attributed to advancements in computing power and the evolution of paradigms like distributed computing, big data and cloud computing. Organizations today are beginning to adapt AI to bolster cybersecurity and deliver advanced protection against sophisticated hackers. With AI security experts can automate complex processes for detecting attacks and reacting to breaches. AI and ML enabled data deception solutions can automatically analyze, detect, and defend advanced attacks by proactively identifying the attackers.
ML and AI are capable enough to deliver an arsenal of knowledge and a blueprint for their human operators to work from. Harnessing technology like ML and AI in cybersecurity allow operators to reverse engineer attacks and make improvements to their systems, allowing operators from simply working in reactive mode to every incident, and instead let them figure out how to address and prevent them from happening again. Organizations are also adopting AI-based cybersecurity technology for accelerating incident detection. This results in a better and efficient job of correlating, curating, and enriching high-intensity security alerts.