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While machine learning (ML) is revolutionizing many industries including cybersecurity, it also has a dark side that often goes unaddressed.
With benefits come potential risks too. Who would have ever thought that hackers could use machine learning for hacking too? Well, looks like they can, and here’s how.
Due to its path-breaking innovation, ML has become one of the hottest buzzwords in the last few years. The ability to make machines learn from past experiences without being explicitly programmed helps ML gain everyone’s attention. ML has disrupted various industries, including healthcare, retail, and manufacturing, with its incredible features. However, every technology comes with its own set of drawbacks that experts should identify and resolve at the earliest. One of the significant applications of ML is in the field of cybersecurity. While on one handm, ML is helping overcome various security related vulnerabilities, on the other hand it is assisting hackers too. Read on to know how ML can defeat cyber threats and at the the same time how hackers can use ML for hacking.
ML’s ability to learn in real-time helps companies to analyze any suspicious activity in their security network and resolve it proactively. With its self-learning feature, ML can learn from its past mistakes or past data breaches and predict similar vulnerabilities for future, helping companies to reduce the time they invest in remediation. Furthermore, ML can process large swarms of datasets - structured or unstructured - and detect anomalies in real-time, if any. Thanks to ML for making systems and software self-learn and for assisting humans in crucial decision-making. So, it's certainly true that ML overcomes cyber frauds, but that it helps hackers as well, is a fact that cannot be denied too.
It is quite ironic how hackers benefit themselves with ML, whereas the technology was aimed at detecting and protecting businesses from such threats. So, is there a secret friendship flourishing between ML and hackers that we are unaware of? Yes, there is.
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