Kevin Lamshöft, T. Neubert, Christian Krätzer, C. Vielhauer, J. Dittmann
{"title":"Information Hiding in Cyber Physical Systems: Challenges for Embedding, Retrieval and Detection using Sensor Data of the SWAT Dataset","authors":"Kevin Lamshöft, T. Neubert, Christian Krätzer, C. Vielhauer, J. Dittmann","doi":"10.1145/3437880.3460413","DOIUrl":null,"url":null,"abstract":"In this paper, we present an Information Hiding approach that would be suitable for exfiltrating sensible information of Industrial Control Systems (ICS) by leveraging the long-term storage of process data in historian databases. We show how hidden messages can be embedded in sensor measurements as well as retrieved asynchronously by accessing the historian. We evaluate this approach at the example of water-flow and water-level sensors of the Secure Water Treatment (SWAT) dataset from iTrust. To generalize from specific cover channels (sensors and their transmitted data), we reflect upon general challenges that arise in such Information Hiding scenarios creating network covert channels and discuss aspects of cover channel selection and and sender receiver synchronisation as well as temporal aspects such as the potential persistence of hidden messages in Cyber Physical Systems (CPS). For an empirical evaluation we design and implement a covert channel that makes use of different embedding strategies to perform an adaptive approach in regards to the noise in sensor measurements, resulting in dynamic capacity and bandwidth selection to reduce detection probability. The results of this evaluation show that, using such methods, the exfiltration of sensible information in long-term scaled attacks would indeed be possible. Additionally, we present two detection approaches for the introduced hidden channel and carry out an extensive evaluation of our detectors with multiple test data sets and different parameters. We determine a detection accuracy of up to 87.8% on test data at a false positive rate (FPR) of 0%.","PeriodicalId":120300,"journal":{"name":"Proceedings of the 2021 ACM Workshop on Information Hiding and Multimedia Security","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 ACM Workshop on Information Hiding and Multimedia Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3437880.3460413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In this paper, we present an Information Hiding approach that would be suitable for exfiltrating sensible information of Industrial Control Systems (ICS) by leveraging the long-term storage of process data in historian databases. We show how hidden messages can be embedded in sensor measurements as well as retrieved asynchronously by accessing the historian. We evaluate this approach at the example of water-flow and water-level sensors of the Secure Water Treatment (SWAT) dataset from iTrust. To generalize from specific cover channels (sensors and their transmitted data), we reflect upon general challenges that arise in such Information Hiding scenarios creating network covert channels and discuss aspects of cover channel selection and and sender receiver synchronisation as well as temporal aspects such as the potential persistence of hidden messages in Cyber Physical Systems (CPS). For an empirical evaluation we design and implement a covert channel that makes use of different embedding strategies to perform an adaptive approach in regards to the noise in sensor measurements, resulting in dynamic capacity and bandwidth selection to reduce detection probability. The results of this evaluation show that, using such methods, the exfiltration of sensible information in long-term scaled attacks would indeed be possible. Additionally, we present two detection approaches for the introduced hidden channel and carry out an extensive evaluation of our detectors with multiple test data sets and different parameters. We determine a detection accuracy of up to 87.8% on test data at a false positive rate (FPR) of 0%.