Thesis On Intrusion Detection System

Thesis On Intrusion Detection System-81
For the tunable IDS game, we show that the distribution utility always uses an optimal configuration with non-zero false alarm probability.

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While attacks on any system cannot be fully prevented forever, real-time detection of the attacks are critical to defend the systems in an effective manner.

Limited research exists on efficient intrusion detection systems suitable for Io T environment.

This master thesis presents a SCADA Intrusion Detection System Test Framework that can be used to simulate SCADA traffic and detect malicious network activity.

The framework uses a signature-based approach and utilize two different IDS engines, Suricata and Snort.

In our framework, a fraction of customers are fraudulent - they consume same average quantity of electricity but report less by strategically manipulating their consumption data.

We consider two sources of information incompleteness: first, the distribution utility does not know the identity of fraudulent customers but only knows the fraction of these consumers, and second, the distribution utility does not know the actual theft level but only knows its distribution.

In the first model, the distribution utility probabilistically chooses to use IDS with a default (fixed) configuration.

In the second model, the distribution utility can configure/tune the IDS to achieve an optimal operating point (i.e.

We first consider situation in which only the first source of information incompleteness is present, i.e., the distribution utility has complete information about the actual theft level.

We present two simultaneous game models, which have same assumption about customer preferences and fraud, but differ in the way in which the distribution utility operates the IDS.

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