AI, Machine Learning Tools to Fight Cyber-attacks

AI, Machine Learning Tools to Fight Cyber-attacks

Cyber security firms are turning to machine learning tools and artificial intelligence to fight growing number of attacks on networks

F-Secure, a Finland-based internet security firm, said on November 27, 2017, that cyber-security companies have started using machine learning tools and artificial intelligence to reduce growing number of attacks on networks.

The world is rapidly moving towards Internet Of Things and connected devices, deployment of artificial intelligence (AI) has become more important for cyber security firms to study large amount of data to protect networks from infiltration attempts, said by F-Secure’s Security Advisor, Sean Sullivan.

Networks are persistently unprotected to threats such as malware, password breaches, denial of service attacks, and phishing.

Sullivan said, F-Secure Labs receives sample data of around 500,000 files from its customers, including 10,000 malware variants and 60,000 malevolent URLs for protection. It is very difficult to analyze such large amount of data, however artificial intelligence and machine learning tools are helping to fight cyber-attacks.

Andy Patel, a Security Advisor, said that Machine learning tools can be used to detect suspiciousness on the basis of structure or behavior of a file. Patel claimed that behavior models aids them to take appropriate steps to protect their customers from ransomware attacks such as ‘Locky’.

Any unusual behavior of a file is determined by artificial intelligence, which helps to detect threats at an early stage, without causing much damage to the network. However, malwares are designed by humans, who thinks innovatively to evade automated security solutions, therefore, humans are needed who can think creatively to protect networks from attacks.

Patel said, AI and machine learning are at a developing stage and there is a long way to go for widespread adoption of such tools in cyber-security. At present, only big players can afford the development of such systems.

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