Cybersecurity has taken centre stage as more and more dialogues appear around the subject with some of the biggest organisations put on the radar and questioned on data breaches. Also, most corporates are now aware of the value of data and the importance of cybersecurity in protecting their business interests. This week’s AI guide covers how artificial intelligence improves and aids cybersecurity practices.
When it comes to training and deployment, the algorithms imbibe increasingly huge data sets. The importance of data privacy will therefore only grow as it relates to AI/machine learning (ML). especially with new regulations expanding upon GDPR, CCPA, HIPAA, etc. Expanding regulatory frameworks are partially why data privacy is one of the most important issues of this decade.
As your organisation plans for AI investments in the future, the following three AI techniques will ensure you stay compliant and secure well into the future.
1. Federated learning
2. Explainable AI (XAI)
AI-based detection systems usually work with uncertainty, they are useful not only to raise alerts when something seems to be wrong but also to give a score on how close a given event is from a cyberattack.
AI has the ability to efficiently analyse and report millions of cyber threats at a much better speed than a human could. Therefore, employing AI and machine learning to detect vulnerabilities significantly enhances human capabilities.
AI can get “smarter” and “learn;” as an AI algorithm continues to search and monitor data, it can improve its understanding of diverse types of potential attacks.
According to a study by PwC and Data Security Council titled “Cyber Security India Market: What lies beneath”, Artificial intelligence (AI) and machine learning (ML) will be powering the ‘cyberwar rooms’ in organisations to help them protect from increasing cyberattacks, as well as detect, predict and respond to the same.
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