Women in Cryptography

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 3053

Special Issue Editor


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Guest Editor
Dipartimento di Informatica, Università di Salerno, 84081 Fisciano (SA), Italy
Interests: cryptography; data Security

Special Issue Information

Dear Colleagues,

In the past, cybersecurity was considered a purely male research field, as shown by the gap between the number of women and men involved in both studies and job positions in this area. However, very high levels have been reached by female researchers in the academic field of cryptography.

The Special Issue, “Women in Cryptography”, is part of MDPI’s “Women’s Special Issue Series” and aims to promote, support and encourage the contribution of women from all over the world who focus their research on cryptography.

Contributions to this Issue, in which a woman is either the first author or one of the corresponding authors, can be submitted as original research articles or reviews, and can cover any topic in the field of cryptography. We also encourage submissions from men, especially those related to previous research carried out by women.

Suggested topics include, but are not restricted to:

  • Complexity-theoretic cryptography;
  • Information-theoretic security;
  • Symmetric encryption;
  • Public-key encryption;
  • Digital signatures and message authentication codes;
  • Authentication, identification and access control;
  • Cryptographic protocols.

We look forward to receiving your contributions.

Dr. Barbara Masucci
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cryptography
  • data security
  • provable security
  • information-theoretic security

Published Papers (2 papers)

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Research

13 pages, 436 KiB  
Article
Continuous Entity Authentication in the Internet of Things Scenario
by Alfredo De Santis, Anna Lisa Ferrara, Manuela Flores and Barbara Masucci
Appl. Sci. 2023, 13(10), 5945; https://doi.org/10.3390/app13105945 - 11 May 2023
Cited by 1 | Viewed by 1091
Abstract
In the context of the Internet of Things (IoT), the proliferation of identity spoofing threats has led to the need for the constant entity verification of devices. Recently, a formal framework has been proposed to study resistance to impersonation attacks for One-Message Unilateral [...] Read more.
In the context of the Internet of Things (IoT), the proliferation of identity spoofing threats has led to the need for the constant entity verification of devices. Recently, a formal framework has been proposed to study resistance to impersonation attacks for One-Message Unilateral Entity Authentication (OM-UEA) schemes, in which the prover continuously authenticates itself through the use of a sequence of authentication messages. Given the limited computing power of the parties (particularly the prover) and the often limited bandwidth channel, in the IoT scenario it is desirable to design unilateral entity authentication schemes that require the use of a single message per session and light computations. In this paper, we first show that OM-UEA schemes can be implemented through digital signatures and that a weak form of unforgeability is sufficient to achieve security against active adversaries. We then apply the signature scheme proposed by Yang et al. in ASIACCS 2020 to our framework, resulting in an OM-UEA scheme that requires minimal computational effort and low storage requirements for the prover. Inspired by this last construction, we propose an OM-UEA scheme based on the hardness of the discrete logarithm problem, which further improves the computational performance for the prover. Our findings offer feasible options for implementing secure continuous entity authentication in IoT applications. Full article
(This article belongs to the Special Issue Women in Cryptography)
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13 pages, 40176 KiB  
Article
On Pseudorandomness and Deep Learning: A Case Study
by Zahra Ebadi Ansaroudi, Rocco Zaccagnino and Paolo D’Arco
Appl. Sci. 2023, 13(5), 3372; https://doi.org/10.3390/app13053372 - 06 Mar 2023
Viewed by 1330
Abstract
Pseudorandomness is a crucial property that the designers of cryptographic primitives aim to achieve. It is also a key requirement in the calls for proposals of new primitives, as in the case of block ciphers. Therefore, the assessment of the property is an [...] Read more.
Pseudorandomness is a crucial property that the designers of cryptographic primitives aim to achieve. It is also a key requirement in the calls for proposals of new primitives, as in the case of block ciphers. Therefore, the assessment of the property is an important issue to deal with. Currently, an interesting research line is the understanding of how powerful machine learning methods are in distinguishing pseudorandom objects from truly random objects. Moving along such a research line, in this paper a deep learning-based pseudorandom distinguisher is developed and trained for two well-known lightweight ciphers, Speck and Simon. Specifically, the distinguisher exploits a convolutional Siamese network for distinguishing the outputs of these ciphers from random sequences. Experiments with different instances of Speck and Simon show that the proposed distinguisher highly able to distinguish between the two types of sequences, with an average accuracy of 99.5% for Speck and 99.6% for Simon. Hence, the proposed method could significantly impact the security of these cryptographic primitives and of the applications in which they are used. Full article
(This article belongs to the Special Issue Women in Cryptography)
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