Machine learning

Machine learning

How we created machine learning module and why we decided to refuse neural networks preferred to classical algorithms, what attacks are detected using Levenshtein distance and how the accuracy of the attack detection is reached.

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Using Nemesida WAF in IDS mode

Using Nemesida WAF in IDS mode

The Nemesida WAF software can work in IDS mode, which uses the principle of traffic mirroring. This makes it possible to train the Nemesida AI system before running Nemesida WAF in the standard mode (IPS), to check the system performance, to monitor the attacks of the web application in the passive mode.

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Signature analyse

Signature analyse

Despite the rapid development of technology, most of the attacks are detected by the signature method, and the accuracy of all methods built on the basis of signature analysis depends on how well the signatures are written.

Virtual patching

Virtual patching

Virtual patching is a mechanism that excludes the possibility of using the vulnerability in software and does not require changes to the source code of the software. This mechanism is implemented in the security layer, which performs analysis and filtering of incoming traffic.

Nemesida AI

Nemesida AI

Using the module Nemesida AI allows you to minimize false positives, improve accuracy of attacks on web application and develop new attack vectors on the web application, taking into account a set of signs of attack and a precedent base.

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