Skip to content
naulon
Not checkedNot checked for notices yet.

Benchmark Tests for the Model-Checking-Based IDS Algorithms

Miaolei Deng, Heling Cao, Weijun Zhu and 2 more

IEEE Access · 2019

doi:10.1109/access.2019.2939011 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

A fundamental concern for the security community is to identify the comprehensive comparable performance of various intrusion detection algorithms which are based on the Model Checking (MC) techniques. To address this open issue, we conduct the benchmark tests for the model-checking-based intrusion detection systems algorithms. At first, linear temporal logic, interval temporal logic and real-time attack signature logic are employed respectively to establish formula models for twenty-four types of attacks selected from KDDCUP, i.e., the annual data mining and knowledge discovery competition organized by association for computing machinery. And then, a standard intrusion set, called intrusion set for intrusion detection based on model checking, which is a behavior version of a subset of KDDCUP, is constructed. On the basis of it, detection abilities and efficiency of the intrusion detection algorithms based on model checking the three logics mentioned above are compared exhaustively. The experimental results illustrate the efficiency and abilities of these three algorithms. It is beneficial for selecting the suitable MC-based algorithms in actual deployment of intrusion detection systems.

Abstract licence: CC BY-NC-ND

References24

    24 more references, whose wording the paper’s licence keeps private.

    Reads

    Read by people on this page

    None yet.

    Checked or read by AI through naulon

    None yet.

    A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

    Are you an author?

    Is this your paper?

    Claim it to add your note and be paid when agents cite it. Free.