ISSTA 2019
Mon 15 - Fri 19 July 2019 Beijing, China
Thu 18 Jul 2019 14:22 - 14:45 at Grand Ballroom - Testing and Machine Learning Chair(s): Hongyu Zhang

Modern anomaly detection systems increasingly rely on machine learning to detect issues in the behaviour of the protected systems. While these solutions are flexible and effective, they can be vulnerable to new kinds of deceptions, known as training attacks. These attacks exploit the live learning mechanism of these systems by progressively injecting small portions of abnormal data. Although, at a given time, the injected data are harmless, they seamlessly swift the learned states to a point where harmful data can pass unnoticed. In this paper, we focus on the systematic testing of these attacks in the context of intrusion detection systems (IDS). We propose a search-based approach to tests IDS by making training attacks. Going a step further, we also propose searching for countermeasures, learning from the successful attacks and thereby increasing the resilience of the tested IDS. We evaluate our approach on a denial-of-service attack detection scenario and a dataset recording the network traffic of a real-world system. Our experiments show that our search-based attack scheme generates successful attacks bypassing the current state-of-the-art defences. We also show that our approach is capable of generating attack patterns for all configuration states of the studied IDS and that it is capable of providing appropriate countermeasures. By co-evolving our attack and defence mechanisms we succeeded at improving the defence of the IDS under test by making it resilient to 49 out of 50 independently generated attacks.

Conference Day
Thu 18 Jul

Displayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change

14:00 - 15:30
Testing and Machine LearningTechnical Papers at Grand Ballroom
Chair(s): Hongyu ZhangThe University of Newcastle
14:00
22m
Talk
DeepHunter: A Coverage-Guided Fuzz Testing Framework for Deep Neural Networks
Technical Papers
Xiaofei XieNanyang Technological University, Lei MaKyushu University, Felix Juefei-XuCarnegie Mellon University, Minhui Xue, Hongxu ChenNanyang Technological University, Yang LiuNanyang Technological University, Singapore, Jianjun ZhaoKyushu University, Bo LiUIUC, Jianxiong YinNVIDIA AI Tech Centre, Simon SeeNVIDIA AI Tech Centre
14:22
22m
Talk
Search-based Test and Improvement of Machine-Learning-Based Anomaly Detection SystemsArtifacts ReusableArtifacts Functional
Technical Papers
Maxime CordySnT, University of Luxembourg, Steve Mullerunaffiliated, Mike PapadakisUniversity of Luxembourg, Yves Le TraonUniversity of Luxembourg
14:45
22m
Talk
DeepFL: Integrating Multiple Fault Diagnosis Dimensions for Deep Fault LocalizationArtifacts ReusableDistinguished Paper AwardsArtifacts Functional
Technical Papers
Xia LiUniversity of Texas at Dallas, USA, Wei LiSouthern University of Science and Technology, Yuqun ZhangSouthern University of Science and Technology, Lingming Zhang
15:07
22m
Talk
Codebase-Adaptive Detection of Security-Relevant MethodsArtifacts Functional
Technical Papers
Goran PiskachevFraunhofer IEM, Lisa Nguyen Quang DoPaderborn University, Eric BoddenHeinz Nixdorf Institut, Paderborn University and Fraunhofer IEM
DOI Pre-print Media Attached File Attached