Abstract
Recently, a number of results have been published that show how to combine classical cryptanalysis with quantum algorithms, thereby (potentially) achieving considerable speed-ups. We follow this trend but add a novel twist by considering how to utilise side channel leakage in a quantum setting. This is non-trivial because Grover’s algorithm deals with unstructured data, however we are interested in searching through a key space which has structure due to the side channel information. We present a novel variation of a key enumeration algorithm that produces batches of keys that can be efficiently tested using Grover’s algorithm. This results in the first quantum key search that benefits from side channel information.
Original language | English |
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Title of host publication | Selected Areas in Cryptography – SAC 2017 - 24th International Conference, Revised Selected Papers |
Editors | Carlisle Adams, Jan Camenisch |
Publisher | Springer Verlag |
Pages | 407-422 |
Number of pages | 16 |
ISBN (Print) | 9783319725642 |
DOIs | |
Publication status | Published - 2018 |
Event | 24th International Conference on Selected Areas in Cryptography, SAC 2017 - Ottawa, Canada Duration: 16 Aug 2017 → 18 Aug 2017 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 10719 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 24th International Conference on Selected Areas in Cryptography, SAC 2017 |
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Country/Territory | Canada |
City | Ottawa |
Period | 16/08/17 → 18/08/17 |
Bibliographical note
Funding Information:EPSRC Early Career Fellowship EP/L021005/1. Elisabeth Oswald and Dan Martin were in part supported by EPSRC via grant EP/N011635/1 (LADA). No research data was created for this paper.
Publisher Copyright:
© Springer International Publishing AG 2018.
Keywords
- Quantum computation
- Side channel attacks
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science