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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

Machine learning for security: The case of side-channel attack detection at run-time

Mushtaq, Maria, Akram, Ayaz, Bhatti, Muhammad Khurram, Chaudhry, Maham, Yousaf, Muneeb, Farooq, Umer, Lapotre, Vianney and Gogniat, Guy (2018) Machine learning for security: The case of side-channel attack detection at run-time. In: 2018 25th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 09-12 Dec 2018, Bordeaux, France.

Item Type: Conference or Workshop Item (Paper)
Full text not available from this repository.

More Information

Uncontrolled Keywords: Machine learning Load modeling Hardware Analytical models Side-channel attacks Encryption
Related URLs:
Depositing User: Umer Farooq

Identifiers

Item ID: 16392
URI: http://sure.sunderland.ac.uk/id/eprint/16392
Official URL: https://ieeexplore.ieee.org/abstract/document/8617...

Users with ORCIDS

ORCID for Umer Farooq: ORCID iD orcid.org/0000-0002-5220-4908

Catalogue record

Date Deposited: 15 Aug 2023 08:48
Last Modified: 04 Jun 2025 15:16

Contributors

Author: Umer Farooq ORCID iD
Author: Maria Mushtaq
Author: Ayaz Akram
Author: Muhammad Khurram Bhatti
Author: Maham Chaudhry
Author: Muneeb Yousaf
Author: Vianney Lapotre
Author: Guy Gogniat

University Divisions

Faculty of Business and Technology > School of Computer Science and Engineering

Subjects

Engineering > Electrical Engineering

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