Intrusion detection system

computer science and engineering

Our project aims to identify various attacks that are taking place on user’s device using Machine Learning. After identifying the type of attacks, various suggestions are provided to user to secure his device against attacks. At the core our project is a Machine Learning project that uses various pre available datasets that are available on the internet and also our custom datasets. After that for suggestion various methods are fetched from internet via an API. Intrusion detection system refers to monitoring of network traffic of a device and alerts the concerned authority when such activity is discovered. It uses input from multiple sources and the uses specific filtering algorithms to differentiate normal activities from malicious ones. An intrusion detection system is used to detect and monitor network traffic and computer data that a typical firewall cannot detect. It is also used to monitor attacks and hacks against susceptible services, data-driven assaults on computers, protocols, application etc. and host-based and network-based attacks including stealing your information, illegal logins, trying to access sensitive file. It can also be placed in front of a server which can be used to monitor attacks like SQL injection etc. An IDS will typically consist of an agent that will collect all the necessary information from the packets and data that are incoming and outgoing, and then analysis engine will detect the signs of intrusion on the system, tree based ids using machine learning.

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