Datasets of RT spoofing attacks on MIL-STD-1553 communication traffic.

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ID: 88127
2019
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Abstract
The datasets in this article are produced to evaluate the ability of MIL-STD-1553 intrusion detection systems to detect attacks that emulate normal non-periodical messages, at differing attack occurrence rates. And different data representations. We present three streams of simulated MIL-STD-1553 traffic containing both normal and attack messages corresponding to packets that were injected into the bus by a malicious remote terminal. The implemented attacks emulate normal non-periodical communication so detecting them with a low false positive rate is non-trivial. Each stream is separated into a training set of normal messages and a test set of both normal and attack messages. The test sets differ by the occurrence rate of attack messages (0.01%, 0.10%, and 1.00%). Each stream is also preprocessed into a dataset of message sequences so that it can be used for sequential anomaly detection analysis. The sequential test sets differ by the occurrence rate of attack sequences (0.14%, 1.26%, and 11.01%). All dataset files can be found in Mendeley Data, doi:10.17632/jvgdrmjvs3.3.
Reference Key
yahalom2019datasetsdata Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Yahalom, Ran;Barishev, David;Steren, Alon;Nameri, Yonatan;Roytman, Maxim;Porgador, Angel;Elovici, Yuval;
Journal Data in brief
Year 2019
DOI
10.1016/j.dib.2019.103863
URL
Keywords
Internet of Things security adaptive systems dynamic protection fault detection and diagnosis intelligence for embedded and cyber-physical systems smart sensor networks

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