Abstract data machine: Data classifier for reliable embedded systems software

M. Taimoor Khan, Anastasios Fragopoulos, Howard Shrobe, Dimitrios Serpanos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present our ongoing work and formalism of a novel data classification method (Abstract Data Machine) for reliable software systems. Most of the approaches for data classification are based on statistical classification, e.g. machine-learning algorithms that comes with false rates. Another critical problem with such algorithms is that they are not reliable and thus do not ensure any provable assurances. One approach to establish reliability of the algorithms is to classify arbitrary data with an appropriate (pragmatically useful) level of abstraction based on the logical data properties that are amenable to assurances, i.e. a formal proof that data represented by a class indeed respects properties of the class. Furthermore, the formal proofs are fundamental for the security assurance of the applications using the algorithms in general and data security in particular.

Original languageEnglish
Title of host publicationProceedings of the 10th Workshop on Embedded Systems Security, WESS 2015
PublisherAssociation for Computing Machinery, Inc
ISBN (Print)9781450336673
DOIs
Publication statusPublished - 4 Oct 2015
Event10th Workshop on Embedded Systems Security, WESS 2015 - Amsterdam, Netherlands
Duration: 4 Oct 20159 Oct 2015

Other

Other10th Workshop on Embedded Systems Security, WESS 2015
CountryNetherlands
CityAmsterdam
Period4/10/159/10/15

Fingerprint

Embedded systems
Classifiers
Security of data
Learning algorithms
Learning systems

Keywords

  • Abstract Data Machine
  • ARMET
  • AWDRAT

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality
  • Hardware and Architecture

Cite this

Khan, M. T., Fragopoulos, A., Shrobe, H., & Serpanos, D. (2015). Abstract data machine: Data classifier for reliable embedded systems software. In Proceedings of the 10th Workshop on Embedded Systems Security, WESS 2015 [a8] Association for Computing Machinery, Inc. https://doi.org/10.1145/2818362.2818370

Abstract data machine : Data classifier for reliable embedded systems software. / Khan, M. Taimoor; Fragopoulos, Anastasios; Shrobe, Howard; Serpanos, Dimitrios.

Proceedings of the 10th Workshop on Embedded Systems Security, WESS 2015. Association for Computing Machinery, Inc, 2015. a8.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Khan, MT, Fragopoulos, A, Shrobe, H & Serpanos, D 2015, Abstract data machine: Data classifier for reliable embedded systems software. in Proceedings of the 10th Workshop on Embedded Systems Security, WESS 2015., a8, Association for Computing Machinery, Inc, 10th Workshop on Embedded Systems Security, WESS 2015, Amsterdam, Netherlands, 4/10/15. https://doi.org/10.1145/2818362.2818370
Khan MT, Fragopoulos A, Shrobe H, Serpanos D. Abstract data machine: Data classifier for reliable embedded systems software. In Proceedings of the 10th Workshop on Embedded Systems Security, WESS 2015. Association for Computing Machinery, Inc. 2015. a8 https://doi.org/10.1145/2818362.2818370
Khan, M. Taimoor ; Fragopoulos, Anastasios ; Shrobe, Howard ; Serpanos, Dimitrios. / Abstract data machine : Data classifier for reliable embedded systems software. Proceedings of the 10th Workshop on Embedded Systems Security, WESS 2015. Association for Computing Machinery, Inc, 2015.
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