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  /  Artificial Intelligence   /  ML and AI: Driving Next-Generation Antivirus for Cybersecurity
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ML and AI: Driving Next-Generation Antivirus for Cybersecurity

Global Tech Outlook features how ML and AI are driving next-gen antivirus for cybersecurity

Different types of cyberattacks have been happening in the tech-driven world due to the sudden emergence of the coronavirus pandemic in 2019. The numbers of cyber-criminals are rising as well as their attacks in different companies throughout 2020 and 2021. There is a sudden rise of ransomware, phishing, viruses and many more to steal and blackmail confidential real-time data of companies, clients, and stakeholders. Thus, tech companies have started leveraging disruptive technologies such as ML and AI to drive next-gen antivirus for effective cybersecurity. The smart machine learning algorithms can provide utmost protection to all smart devices against cyberattacks efficiently and effectively. Let’s explore how ML and AI are set to drive next-gen antivirus for cybersecurity.

Cyber-criminals are developing modern techniques for new attacks that are too difficult to track and monitor for the traditional solutions of antivirus software. Companies need to replace traditional antivirus software with ultra-modern antivirus leveraging ML and AI models and algorithms. Next-generation antivirus software can provide cybersecurity against memory-based attacks, PowerShell language, remote log-ins, as well as macro-based attacks. Machine learning algorithms enhance the detection capabilities of systems by building a mathematical model to identify good and bad quality files. The machine learning algorithms can analyze two datasets— malicious files and non-malicious files when there is a cyberattack in any system.

ML can detect new techniques of cyberattacks without depending on the signatures and fingerprints, unlike the conventional method. AI models can be trained with large datasets to detect, differentiate, and identify new malicious patterns in the recent times as well as nearby future. There are multiple ML methods that can design to meet real-life cybersecurity requirements with low false-positive rates as well as increased interpretability like scalable clustering, deep neural network, and many more.

Next-generation antivirus solutions are becoming popular owing to its cybersecurity capacity of different types of attacks through constant monitoring and responding to tactics, techniques, and procedures of cyber-criminals. It also provides endpoint cybersecurity protection for its Cloud-based approach. The next-generation antivirus leverages AI and ML with predictive analytics as well as threat intelligence. It focuses on files, processes, applications, as well as network connections to detect any unusual or unauthorized activity, behaviour or intent. ML and AI are driving next-generation antivirus towards success in multiple companies by responding and remediating as quickly as possible without any delay and loss.

The next-generation antivirus needs a few hours to deploy instead of a few months for its cloud-based approach while reducing the burden of maintaining software, updating signature databases, as well as managing infrastructures. It is popular in the global market for its proactive role owing to its utilization of behavioural AI. It draws a picture of a real-time network environment to identify and block cyberattacks that are personalized with higher risk.

Thus, do not wait for any sudden malicious cyberattacks to happen in the existing system. Companies have already started implementing next-generation antivirus by leveraging AI and ML algorithms for utmost cybersecurity.