Leveraging machine learning for an Effective Network Security
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Leveraging machine learning for an Effective Network Security

By Enterprise Networking Mag | Friday, February 15, 2019

network securityMachine learning (ML) tools are now essential of enterprise network security. These solutions use potent algorithms to distinguish between legitimate users and attackers. However, cybercriminals can also use machine learning techniques to find flaws in network defense.

The most significant advantage of machine learning tools is the ability to find out any activity that falls outside the normal scope of operations. These activities can be an indicator of a zero-day attack. Many attackers also use signature-based attacks to evade rules and carry out successful attacks.  In these attack, hackers use a string of code or pattern of actions to enter into a system. Machine learning tools analyze the patterns to detect any known malware in the system. These tools are also very effective in finding new threat patterns and determining the probability that an unknown program is malware.

Network Security Solution companies: Amazing Computer ServiceApex Technology ServicesCheck Point Software Technologies.

Enterprises need to feed their machine learning tools with inputs, interpretations, and classifications to make a stable feedback loop, helping organizations to reduce the number of false positives. This data will allow the tools to analyze a set of characteristics to differentiate between malware and legitimate activity. While the traditional network security solutions use static codes to detect malware, machine learning tools classify a program based on its execution and behavior. This classification helps to spot malware that mutates to change its signature.

Machine learning tools can also build a set of rules based on its observation of network and application. For example, machine learning tools can observe an application to recognize the way it accesses a critical database. This allows the tools to block an action that does not follow the known pattern or abide by the rules. Meanwhile, the attackers have also started using this technology to breach a network defense by determining the rules that anti-malware software uses to identify attacks.

Enterprises should use cloud-based machine learning, advanced clustering, and data mining techniques to identify malware with great agility and efficiency to boost business growth.

Check out: Top Network Security Solution Companies.

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