Log In Sign Up

A Hybrid Approach for an Interpretable and Explainable Intrusion Detection System

by   Tiago Dias, et al.

Cybersecurity has been a concern for quite a while now. In the latest years, cyberattacks have been increasing in size and complexity, fueled by significant advances in technology. Nowadays, there is an unavoidable necessity of protecting systems and data crucial for business continuity. Hence, many intrusion detection systems have been created in an attempt to mitigate these threats and contribute to a timelier detection. This work proposes an interpretable and explainable hybrid intrusion detection system, which makes use of artificial intelligence methods to achieve better and more long-lasting security. The system combines experts' written rules and dynamic knowledge continuously generated by a decision tree algorithm as new shreds of evidence emerge from network activity.


page 1

page 2

page 3

page 4


Hybrid Model For Intrusion Detection Systems

With the increasing number of new attacks on ever growing network traffi...

Sufficient Reasons for A Zero-Day Intrusion Detection Artificial Immune System

The Internet is the most complex machine humankind has ever built, and h...

Creating an Explainable Intrusion Detection System Using Self Organizing Maps

Modern Artificial Intelligence (AI) enabled Intrusion Detection Systems ...

Deep Down the Rabbit Hole: On References in Networks of Decoy Elements

Deception technology has proven to be a sound approach against threats t...

Autonomic Intrusion Response in Distributed Computing using Big Data

We introduce a method for Intrusion Detection based on the classificatio...

Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response

Artificial Intelligence (AI) has become an integral part of modern-day s...

Machine learning on knowledge graphs for context-aware security monitoring

Machine learning techniques are gaining attention in the context of intr...