Signature-based Intrusion Detection with Data Mining and Machine Learning.

Abstract

One of the issues surrounding information security that we face today is cyber threats. Every website we navigate or internet-connected application we use is exposed to risks that affect sensitive data that is stored or manipulated. Companies providing software solutions are challenged to ensure the security of their offerings and comply with laws that require them to protect the handling of sensitive data. Compliance with data security or confidential information requirements will not only allow compliance with the mentioned laws but also instill confidence in the customers for whom a specific solution is developed or provided, or for the
specific audience it targets. With many cyber threats, we need to assess the entire cycle in which cyber-attacks materialize. In particular, this work focuses on analyzing a possible way to contribute to the security of systems regarding the early stages of a cyber-attack: Research and information gathering and gaining access. Specifically, the implementation of Signature-Based Intrusion Detection Systems will be analyzed, using Data Mining and Machine Learning.