Advanced Studies of Symmetry/Asymmetry in Cybersecurity

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 3395

Special Issue Editors

Dr. Konglin Zhu
E-Mail Website
Guest Editor
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
Interests: federal learning; edge computing; vehicle networking
Dr. Pengcheng Wang
E-Mail Website
Guest Editor
School of Cyber Science and Technology, Beihang University, Beijing 100191, China
Interests: information security

Special Issue Information

Dear Colleagues,

Cybersecurity has become a critical concern for individuals, organizations, and governments. As technology advances and becomes more sophisticated, the need for effective cybersecurity measures has intensified. One approach that has gained significant attention in the field of cybersecurity is the concept of symmetry and asymmetry; the incorporation of both is deemed essential for developing effective defense strategies against modern threats. While symmetry focuses on building robust security measures, asymmetry allows defenders to leverage their advantages over attackers. By adopting a balanced and comprehensive approach, cybersecurity professionals can enhance their ability to protect individuals, organizations, and governments from cyber threats.

The aim of this Special Issue is to publish articles on the recent advancements in this field, spread across a universe of applications such as industry, robotics, traffic, autonomous vehicle, and blockchain, as well as in fundamental and theoretical forms.

Dr. Konglin Zhu
Dr. Pengcheng Wang
Guest Editors

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. Symmetry is an international peer-reviewed open access monthly 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.

Published Papers (4 papers)

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Research

22 pages, 564 KiB  
Article
AAHEG: Automatic Advanced Heap Exploit Generation Based on Abstract Syntax Tree
Symmetry 2023, 15(12), 2197; https://doi.org/10.3390/sym15122197 - 14 Dec 2023
Viewed by 847
Abstract
Automatic Exploit Generation (AEG) involves automatically discovering paths in a program that trigger vulnerabilities, thereby generating exploits. While there is considerable research on heap-related vulnerability detection, such as detecting Heap Overflow and Use After Free (UAF) vulnerabilities, among contemporary heap-automated exploit techniques, only [...] Read more.
Automatic Exploit Generation (AEG) involves automatically discovering paths in a program that trigger vulnerabilities, thereby generating exploits. While there is considerable research on heap-related vulnerability detection, such as detecting Heap Overflow and Use After Free (UAF) vulnerabilities, among contemporary heap-automated exploit techniques, only certain automated exploit techniques can hijack program control flow to the shellcode. An important limitation of this approach is that it cannot effectively bypass Linux’s protection mechanisms. To solve this problem, we introduced Automatic Advanced Heap Exploit Generation (AAHEG). It first applies symbolic execution to analyze heap-related primitives in files and then detects potential heap-related vulnerabilities without a source code. After identifying these vulnerabilities, AAHEG builds an exploit abstract syntax tree (AST) to identify one or more successful exploit strategies, such as fast bin attack and Safe-unlink. AAHEG then selects exploitable methods via an abstract syntax tree (AST) and performs final testing to produce the final exploit. AAHEG chose to generate advanced heap-related exploits because the exploits can bypass Linux protections. Basically, AAHEG can automatically detect heap-related vulnerabilities in binaries without source code, build an exploit AST, choose from a variety of advanced heap exploit methods, bypass all Linux protection mechanisms, and generate final file-form exploit based on pwntools which can pass local and remote testing. Experimental results show that AAHEG successfully completed vulnerability detection and exploit generation for 20 Capture The Flag (CTF) binary files, 11 of which have all protection mechanisms enabled. Full article
(This article belongs to the Special Issue Advanced Studies of Symmetry/Asymmetry in Cybersecurity)
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27 pages, 6009 KiB  
Article
Research on Trusted Management of Industrial Internet Identity Analysis Data Based on Blockchain
Symmetry 2023, 15(12), 2102; https://doi.org/10.3390/sym15122102 - 23 Nov 2023
Viewed by 705
Abstract
As an important part of the industrial internet, identity analysis data are growing with the expansion of the field involved in the industrial internet. The management of industrial internet identity analysis data faces many problems, such as complex types, a wide range of [...] Read more.
As an important part of the industrial internet, identity analysis data are growing with the expansion of the field involved in the industrial internet. The management of industrial internet identity analysis data faces many problems, such as complex types, a wide range of information, rapid growth, reduced security, etc. In view of the above problems, a trusted management model of industrial internet identity analysis data based on blockchain is first designed. Meanwhile, the identity analysis data information is analyzed and classified, and industrial data are divided into three levels according to the degree of privacy for hierarchical encryption. Secondly, the “on-chain + off-chain” storage model combining the blockchain main-slave chain and the off-chain database is designed to improve the efficiency of the whole model. Then, a collaborative consensus mechanism suitable for the main-slave multi-chain of the industrial internet is also designed, including slave-chain CIPBFT consensus, inter-chain cross-chain transmission protocol and main chain KZKP consensus. Finally, a prototype system is built to analyze the correctness, security, scalability and consensus efficiency of the model proposed in this study. The results show that the model proposed in this study can be applied to trusted management of data information for industrial internet identity analysis, and also provides an optimized solution for the same problem in fields of the industrial internet. Full article
(This article belongs to the Special Issue Advanced Studies of Symmetry/Asymmetry in Cybersecurity)
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18 pages, 601 KiB  
Article
Private Set Intersection Based on Lightweight Oblivious Key-Value Storage Structure
Symmetry 2023, 15(11), 2083; https://doi.org/10.3390/sym15112083 - 18 Nov 2023
Viewed by 699
Abstract
At this stage, the application of Private Set Intersection (PSI) protocols is essential for smart homes. Oblivious Key-Value Stores (OKVS) can be used to design efficient PSI protocols. Constructing OKVS with a cuckoo hashing graph is a common approach. It increases the number [...] Read more.
At this stage, the application of Private Set Intersection (PSI) protocols is essential for smart homes. Oblivious Key-Value Stores (OKVS) can be used to design efficient PSI protocols. Constructing OKVS with a cuckoo hashing graph is a common approach. It increases the number of hash functions while reducing the possibility of collisions into rings. However, the existing OKVS construction scheme requires a high time overhead, and such an OKVS applied to PSI protocols would also have a high communication overhead. In this paper, we propose a method called 3-Hash Garbled Cuckoo Graph (3H-GCG) for constructing cuckoo hash graphs. Specifically, this method handles hash collisions between different keys more efficiently than existing methods, and it can also be used to construct an OKVS structure with less storage space. Based on the 3H-GCG, we design a PSI protocol using the Vector Oblivious Linear Evaluation (VOLE) and OKVS paradigm, which achieves semi-honest security and malicious security. Extensive experiments demonstrate the effectiveness of our method. When the set size is 218220, our PSI protocol is less computationally intensive than other existing protocols. The experiments also show an increase in the ratio of raw to constructed data of about 7.5%. With the semi-honest security setting, our protocol achieves the fastest runtime with the set size of 218. With malicious security settings, our protocol has about 10% improvement in communication compared with other existing protocols. Full article
(This article belongs to the Special Issue Advanced Studies of Symmetry/Asymmetry in Cybersecurity)
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19 pages, 5679 KiB  
Article
A Secure Trajectory Planning Method for Connected Autonomous Vehicles at Mining Site
Symmetry 2023, 15(11), 1973; https://doi.org/10.3390/sym15111973 - 25 Oct 2023
Viewed by 732
Abstract
Recently, with the assistance of 5G networks and the Internet of Things, specialized applications of autonomous driving to mining sites have been explored, with the goal of realizing the unmanned operation of mining systems and enhancing the safety of the mining industry. After [...] Read more.
Recently, with the assistance of 5G networks and the Internet of Things, specialized applications of autonomous driving to mining sites have been explored, with the goal of realizing the unmanned operation of mining systems and enhancing the safety of the mining industry. After receiving the loading task, the autonomous driving system will generate a feasible trajectory for the mining truck. It requires that the trajectory be generated in advanced within a limited-time high-latency network. In addition, the secure trajectory planning for mining sites involves factors in the complex environment and an unstable network. Thus, a secure trajectory planning method for autonomous trucks at mining sites is proposed. It simplifies the planning by decoupling the planning into front-end path searching and back-end trajectory generation. First, the planner enhances the Hybrid A* search algorithm to find the hauling path within the boundary of the mining site, and then, it post-processes the path with a well-designed symmetric optimization-based method. Then, considering the interaction with other autonomous trucks, a topology-guided search method for secure decision making is proposed, considering the possibility of cybersecurity. The proposed method was validated in real scenarios of the mining environment. The results verify that the planner can generate the secure trajectory under network delay 2.0 s conditions. Full article
(This article belongs to the Special Issue Advanced Studies of Symmetry/Asymmetry in Cybersecurity)
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