Cyber Security Systems: Emerging Technologies for a Secure Future

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 (29 February 2024) | Viewed by 1681

Special Issue Editors


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Guest Editor
College of Control Science and Engineering, China University of Petroleum (East China), Qingdao 266580, China
Interests: crowdsensing; edge computing; AI security
Special Issues, Collections and Topics in MDPI journals
School of Cybersecurity, Northwestern Polytechnical University, Xi’an 710072, China
Interests: Internet of Things; cyber security; federated learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The ubiquity of interconnected systems, driven by the proliferation of the Internet of Things (IoT) and cloud computing, has heightened the vulnerability of digital infrastructures to an array of cyber threats. The dynamic nature of technological innovation, while facilitating unprecedented connectivity and efficiency, has also inadvertently introduced exploitable weaknesses. Sophisticated cyber attacks, ranging from data breaches and ransomware to identity theft, capitalize on these vulnerabilities to compromise the confidentiality, integrity, and availability of digital assets. The escalating magnitude and diversity of cyber threats underscore the exigency of addressing the underlying reasons for their emergence.

In light of the escalating cyber threat landscape, the need to institute robust cyber security systems is unequivocal. Moreover, as the digital landscape extends to encompass critical infrastructure, healthcare, finance, and beyond, the deployment of advanced encryption protocols and robust authentication mechanisms becomes imperative to ensure the resilience of essential services. To cultivate a secure digital milieu and ensure the preservation of information integrity, user privacy, and societal stability, the construction of a comprehensive cyber security system has become of paramount significance in countering contemporary cyber threats.

This Special Issue aims to attract a collection of outstanding technical research and papers which cover a wide range of cyber security systems, providing a platform for the exchange of groundbreaking ideas, innovative methodologies, and empirical insights.

This Special Issue will focus on (but is not limited to) the following topics:

  • Next-generation threat detection and mitigation;
  • Secure software solutions;
  • Data privacy and encryption;
  • Network security;
  • Artificial intelligence for security;
  • IoT security;
  • Cloud and edge security;
  • Cybersecurity in critical infrastructure;
  • Blockchain solutions for cyber security and trust.

Prof. Dr. Honglong Chen
Dr. Libin Yang
Guest Editors

Manuscript Submission Information

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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

  • threat detection
  • secure software
  • data privacy and encryption
  • network security
  • AI for security
  • IoT security
  • cloud and edge security
  • cybersecurity in critical infrastructure
  • blockchain

Published Papers (2 papers)

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Research

12 pages, 1386 KiB  
Article
Privacy Protection Based on Special Identifiers of Intersection Base Computing Technology
by Ping Zhang, Tengfei Ma, Qing Zhang, Ji Zhang and Jiechang Wang
Appl. Sci. 2024, 14(2), 813; https://doi.org/10.3390/app14020813 - 18 Jan 2024
Viewed by 595
Abstract
Private Set Intersection Cardinality (PSI-CA) and Private Set Union Cardinality (PSU-CA) are two cryptographic primitives whereby two or more parties are able to obtain the cardinalities of the intersection and the union of their respective private sets, and the privacy of their sets [...] Read more.
Private Set Intersection Cardinality (PSI-CA) and Private Set Union Cardinality (PSU-CA) are two cryptographic primitives whereby two or more parties are able to obtain the cardinalities of the intersection and the union of their respective private sets, and the privacy of their sets is preserved. In this paper, we propose a new privacy protection intersection cardinality protocol, which can quickly deal with set inequality and asymmetry problems and can obtain 100% correct results, and, in terms of efficiency, we are much faster than using the polynomial method. Our protocol adopts the Paillier addition homomorphic encryption scheme and applies the identifier guidance technology, using identifier determination, to the semi-homomorphic encryption ciphertext environment, excluding a large number of different options and quickly finding the base of the intersection of two sides. Full article
(This article belongs to the Special Issue Cyber Security Systems: Emerging Technologies for a Secure Future)
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20 pages, 1475 KiB  
Article
CanaryExp: A Canary-Sensitive Automatic Exploitability Evaluation Solution for Vulnerabilities in Binary Programs
by Hui Huang, Yuliang Lu, Kailong Zhu and Jun Zhao
Appl. Sci. 2023, 13(23), 12556; https://doi.org/10.3390/app132312556 - 21 Nov 2023
Viewed by 751
Abstract
We propose CanaryExp, an exploitability evaluation solution for vulnerabilities among binary programs protected by StackGuard. CanaryExp devises three novel techniques, namely canary leakage proof of concept generation, canary leaking analysis time exploitation, and dynamic canary-relocation-based exploitability evaluation. The canary leakage proof of concept [...] Read more.
We propose CanaryExp, an exploitability evaluation solution for vulnerabilities among binary programs protected by StackGuard. CanaryExp devises three novel techniques, namely canary leakage proof of concept generation, canary leaking analysis time exploitation, and dynamic canary-relocation-based exploitability evaluation. The canary leakage proof of concept input generation mechanism first traces the target program’s execution, transforming the execution state into some canary leaking state, from which some canary leaking input is derived. This input can be deemed as proof that some vulnerability that can lead to canary leakage exists. The canary leaking analysis time exploit generation then performs incremental analysis based on the canary leaking input, crafting analysis time exploit that can complete vulnerability exploitation in the analysis time environment. Based on the analysis time exploit, the dynamic canary-relocation-based exploitability evaluation component collects the necessary metadata, on which an exploitation session is automatically constructed that can not only leak the runtime canary and relocate it in the input stream but also evaluate the exploitability of the desired vulnerability. Using a benchmark containing six test programs, eight challenges from some network challenging events and four real-world applications, we demonstrate that CanaryExp can generate canary leaking samples more effectively than existing test case generation methods and automatically evaluate the exploitability for vulnerabilities among programs where the StackGuard protection mechanism is deployed. Full article
(This article belongs to the Special Issue Cyber Security Systems: Emerging Technologies for a Secure Future)
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