liflab / pattern-detection-lab

A study of pattern detection strategies using runtime verification

A study of pattern detection strategies using runtime verification

• Author: Sylvain Hallé
• Veresion: 1.1
• 2023-01-18

Summary

Integrating security in the development and operation of information systems is the cornerstone of SecDevOps. From an operational perspective, one of the key activities for achieving such an integration is the detection of incidents (such as intrusions), especially in an automated manner. However, one of the stumbling blocks of an automated approach to intrusion detection is the management of the large volume of information typically produced by this type of solution. Existing works on the topic have concentrated on the reduction of volume by increasing the precision of the detection approach, thus lowering the rate of false alarms. However, another, less explored possibility is to reduce the volume of evidence gathered for each alarm raised.

This lab explores the concept of intrusion detection from the angle of complex event processing. It provides a formalization of the notion of pattern matching in a sequence of events produced by an arbitrary system, by framing the task as a runtime monitoring problem. It then focuses on the topic of incident reporting, and proposes a technique to automatically extract relevant elements of a stream that explain the occurrence of an intrusion.

The current repository contains a benchmark that compares different detection strategies by running them on synthetically-generated event streams for various incident patterns. Among the elements that are measured, the number of events reported for each pattern match and the total computation time are considered. This data is compiled and reported in various tables and plots.

The lab produces data that is reported in the following book chapter:

• S. Hallé. (2023). A Stream-Based Approach to Intrusion Detection. Notes on Software Engineering Methods and Security in a DevOps Environment, Springer Lecture Notes on Computer Science, to appear in June 2023.

Instructions on using this repository

This repository contains an instance of LabPal, an environment for running experiments on a computer and collecting their results in a user-friendly way. The author of this archive has set up a set of experiments, which typically involve running scripts on input data, processing their results and displaying them in tables and plots. LabPal is a library that wraps around these experiments and displays them in an easy-to-use web interface. The principle behind LabPal is that all the necessary code, libraries and input data should be bundled within a single self-contained JAR file, such that anyone can download and easily reproduce someone else's experiments.

All the plots and other data values mentioned in the aforementioned publication are automatically generated by the execution of this lab. The lab also provides additional tables and plots that could not fit into the manuscript. Detailed instructions can be found on the LabPal website, [https://liflab.github.io/labpal]

Building the benchmark

First make sure you have the following installed:

• The Java Development Kit (JDK) to compile. The lab is developed to comply with Java version 11; it is probably safe to use any later version.
• Ant to automate the compilation and build process

Dependencies

In order to run, the lab requires the following Java libraries, all of which are open source and publicly available:

• Version 0.10.8 of the BeepBeep event stream processing engine
• The Fsm, Ltl and Provenance palettes of the January 2023 pre-compiled bundle (i.e. fsm.jar, ltl.jar and provenance.jar)
• Version 0.3 of the Synthia data structure generator
• Version 2.99-beta 1 of the LabPal experimental environment

You can use the Ant script to automatically download any libraries missing from your system by typing:

ant download-deps

This will put the missing JAR files in the Source/dep folder in the project's root.

Compiling

Once these steps have been taken care of, compile the sources by simply typing:

ant

This will produce a file called pattern-detection-lab.jar in the folder. This file is runnable and self-contained. It should be able to reproduce all the experimental results that are presented in the aforementioned publication.

Running LabPal

If you want to see any plots associated to the experiments, you need to have GnuPlot installed and available from the command line by typing gnuplot.

To start the lab and use its web interface, type at the command line:

java -jar pattern-detection-lab.jar --autostart

You should see something like this:

LabPal 2.99 - A versatile environment for running experiments
(C) 2014-2022 Laboratoire d'informatique formelle
Université du Québec à Chicoutimi, Canada
Please visit http://localhost:21212/index to run this lab
Hit Ctrl+C in this window to stop

Open your web browser, and type http://localhost:21212/index in the address bar. This should lead you to the main page of LabPal's web control panel. (Note that the machine running LabPal does not need to have a web browser. You can open a browser in another machine, and replace localhost by the IP address of the former.)

Using the web interface

A detailed explanation on the use of the LabPal web interface can be found in this YouTube video: https://www.youtube.com/watch?v=5uL7i6SytyM. A lab is made of a set of experiments, each corresponding to a specific set of instructions that runs and generates a subset of all the benchmark's results. Results from experiments are collected and processed into various auto-generated tables and plots.

The lab is instructed to immediately start running all the expermients it contains. You can follow the progress of these experiments by going to the Status page and refreshing it periodically. At any point, you can look at the results of the experiments that have run so far. You can do so by:

• Going to the Plots (5th button in the top menu) or the Tables (6th button) page and see the plots and tables created for this lab being updated in real time
• Going back to the list of experiments, clicking on one of them and getting the detailed description and data points that this experiment has generated

Once the assistant is done, you can export any of the plots and tables to a file, or the raw data points by using the Export button in the Status page.

Comparing results from the paper

An interesting feature of LabPal, described in this other YouTube video (https://www.youtube.com/watch?v=StXflS52h4s), is that it exports its results directly into a research paper. If you look at the PDF of the paper, you will see that the plots and some other elements in the text are hyperlinks. These links can be used to fetch the corresponding plot or data element inside the running LabPal instance.

For example, locate Table 1 and hover your mouse over one of the cells. You should see that each cell is actually a hyperlink with a text like "T18.1.2". Copy that link, and then go to the LabPal console in the browser and click on the "Find" button (rightmost button in the top bar). Paste the corresponding text in the search bar and click on "Find". You should be taken directly to the page that corresponds to Table 1 in the paper, where the corresponding cell is highlighted, and visually compare the value contained in the paper with the one from the lab. (Make sure that the lab has finished running before making this comparison, otherwise what you will see is a partial plot with whatever results have been generated so far.)

Note that the values presented in the lab are re-computed from scratch on the host machine when the lab is executed. Thus it is normal that some values (for example, execution time) differ from those in the paper.

Disclaimer

The LabPal library was written by Sylvain Hallé, Professor at Université du Québec à Chicoutimi, Canada. However, the experiments contained in this specific lab instance and the results they produce are the sole responsibility of their author.