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Journal of Cryptographic Engineering - Call for Papers: Machine Learning Techniques in Side-channel Attacks

Guest Editors
* Debdeep Mukhopadhyay, Indian Institute of Technology, Kharagpur, India, debdeep.mukhopadhyay@gmail.com 
* Stjepan Picek, Radboud University, The Netherlands, picek.stjepan@gmail.com 


In side-channel analysis (SCA), the attacker exploits weaknesses in the physical implementations of cryptographic algorithms. In the last decade, profiling SCA based on machine learning proved very successful in breaking cryptographic implementations in various settings. Still, despite all the successful results, there are many open questions. With all the diverse strategies and techniques in machine learning-based side-channel analysis, it is not obvious how effective and efficient are the different approaches and how they compare to each other.


In addition, it is hard to identify the primary challenges as they are typically device-or threat model-specific. The goal of the special issue is to help increase the awareness about machine learning-based SCA and gather researchers’ latest results in this challenging domain. Considering the above challenges, the scope of this Special Issue of Springer JCEN deals with the following topics (but not limited to):

  • Machine/deep learning-based side-channel attacks
  • Dataset design and analysis
  • Novel countermeasures against machine/deep learning-based SCA
  • Machine/deep learning-based SCA for reverse-engineering, hardware detection
  • Novel applications of machine/deep learning in SCA
  • Explainability of machine/deep learning in SCA
  • Comparisons with non-machine learning-based SCA
  • Survey and Systematization-of-Knowledge papers

Submission Guidelines
All original manuscripts or revisions to the journal of Cryptographic Engineering (JCEN) must be submitted online. Please be sure to read the submission guidelines before submitting: https://www.springer.com/journal/13389/submission-guidelines 

To submit, go to the journal home page: https://www.springer.com/journal/13389 (this opens in a new tab) and select “Submit Manuscript.” When submitting, on the details tab, select the "Special Issue on Machine Learning Techniques in Side-channel Attacks" to ensure that the article is considered for this special issue. Authors must also mention the same in their submission cover letter.


Submitted articles must not have been previously published or currently submitted for publication elsewhere. For previously published conference papers, it is required that submissions to the special issue have at least 40% new content. Submissions that do not meet this requirement will be rejected.
 

Important Dates

Open to submissions: June 29th, 2022

Submission deadline: October 1, 2022

Revision: January 3, 2023

2nd revision: March 3, 2023

Acceptance notification: June 4, 2023

Online Publication: mid-July 2023

Peer review policy

The Journal of Cryptographic Engineering adheres to the standard Peer Review Policy, Process and Guidance (this opens in a new tab) as outlined by Springer under Editorial Policies (this opens in a new tab) in the Information for Journal Authors (this opens in a new tab) web page.

  • All special issue papers must be prepared in accordance with the Journal guidelines: https://www.springer.com/journal/13389/submission-guidelines.
  • Submitted papers should present original, unpublished work, relevant to one of the topics of the special issue. All manuscripts will be subject to the Journal’s rigorous peer review policy, by at least two independent reviewers. 
  • This evaluation will cover the following aspects, but will not be limited to: relevance, significance of contribution to the field, technical quality, scholarship, and quality of presentation. 

Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue.  All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least two independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process.

Before submitting, it is also recommended that you visit the following webpages to familiarize yourself with various aspects of the editor role: Springer Nature Code of Conduct (this opens in a new tab) and  Springer Nature publishing and editorial policies (this opens in a new tab).


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