Cyber Attacks: Threats and Security Solutions

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (15 March 2024) | Viewed by 1250

Special Issue Editor


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Guest Editor
Department of Computer Science, The University of Missouri, Columbia, MO 63121, USA
Interests: cyber security; data sciences
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

At present, the world is connect through cyber networks and cyber-crime is observed at a very high rate. The security of industrial plants and safe financial transactions are minimum requirements for security and privacy. Additionally, intrusion, data poisoning, and port bombarding are common issues in the cyber-world. Cyber-attackers can be hired these days for a small compensation and can target anyone to disturb the running system. These attack can be country-specific or issue-specific with the aim of hitting a target. Cyber-attacks were at an all-time high even during the pandemic, continuing this trend today. The capability to detect, stop and defend against such crimes and fraud is a challenge and the law must support for agencies in the pursuit of cyber-attackers.

Prof. Dr. Ankit Chaudhary
Guest Editor

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Keywords

  • detection and analysis of advanced cyber-attacks, techniques, and procedures
  • malware analysis
  • analytic techniques for the detection and analysis of cyber-crime
  • application of machine-learning tools and techniques in cyber-crime
  • theories and models for the detection and analysis of advanced persistent threats
  • automated and smart tools for the collection, preservation, and analysis of digital evidence
  • cyber-law and policies
  • threat intelligence techniques for reacting to advanced intrusion campaigns
  • applying machine learning tools and techniques for malware analysis and fighting against cyber-crimes
  • intelligent forensic tools, techniques, and procedures for cloud, mobile, and data-center forensics
  • intelligent analysis of different types of data collected from different layers of network security solutions
  • intelligent methods to manage, share, and receive logs and data relevant to a variety of adversary groups
  • interpretation of cyber data utilizing intelligent data analysis techniques
  • infer intelligence of existing cyber security data generated using different monitoring and defense solutions
  • automated and intelligent methods for adversary profiling

Published Papers (2 papers)

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Research

15 pages, 267 KiB  
Article
Advanced Algorithmic Approaches for Scam Profile Detection on Instagram
by Biodoumoye George Bokolo and Qingzhong Liu
Electronics 2024, 13(8), 1571; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics13081571 - 19 Apr 2024
Viewed by 367
Abstract
Social media platforms like Instagram have become a haven for online scams, employing various deceptive tactics to exploit unsuspecting users. This paper investigates advanced algorithmic approaches to combat this growing threat. We explore various machine learning models for scam profile detection on Instagram. [...] Read more.
Social media platforms like Instagram have become a haven for online scams, employing various deceptive tactics to exploit unsuspecting users. This paper investigates advanced algorithmic approaches to combat this growing threat. We explore various machine learning models for scam profile detection on Instagram. Our methodology involves collecting a comprehensive dataset from a trusted source and meticulously preprocessing the data for analysis. We then evaluate the effectiveness of a suite of machine learning algorithms, including decision trees, logistic regression, SVMs, and other ensemble methods. Each model’s performance is measured using established metrics like accuracy, precision, recall, and F1-scores. Our findings indicate that ensemble methods, particularly random forest, XGBoost, and gradient boosting, outperform other models, achieving accuracy of 90%. The insights garnered from this study contribute significantly to the body of knowledge in social media forensics, offering practical implications for the development of automated tools to combat online deception. Full article
(This article belongs to the Special Issue Cyber Attacks: Threats and Security Solutions)
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17 pages, 462 KiB  
Article
Multi-Dimensional Moving Target Defense Method Based on Adaptive Simulated Annealing Genetic Algorithm
by Hanyi Xu, Guozhen Cheng, Xiaohan Yang, Wenyan Liu, Dacheng Zhou and Wei Guo
Electronics 2024, 13(3), 487; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics13030487 - 24 Jan 2024
Viewed by 574
Abstract
Due to the fine-grained splitting of microservices and frequent communication between microservices, the exposed attack surface of microservices has exploded, facilitating the lateral movement of attackers between microservices. To solve this problem, a multi-dimensional moving target defense method based on an adaptive simulated [...] Read more.
Due to the fine-grained splitting of microservices and frequent communication between microservices, the exposed attack surface of microservices has exploded, facilitating the lateral movement of attackers between microservices. To solve this problem, a multi-dimensional moving target defense method based on an adaptive simulated annealing genetic algorithm (MD2RS) is proposed. Firstly, according to the characteristics of microservices in the cloud, a microservice attack graph is proposed to quantify the attack scenario of microservices in the cloud so as to conveniently and intuitively observe the vulnerability of microservices in the cloud and the dependency relationship between microservices. Secondly, the security gain and resource cost are quantified for the key nodes selected by measuring the degree of dependence of each node according to the degree centrality. Finally, the Adaptive Simulated Annealing Genetic Algorithm (ASAGA) is used to solve the optimal security configuration information of the moving target defense, that is, the combination of the number of copies of the multi-copy deployment and the rotation cycle of the dynamic rotation of microservices, in order to quickly evaluate the security risks of microservices and optimize the security policy. Experiments show that the defense return rate of MD2RS is 85.95% higher than that of the mainstream methods, and the experimental results are conducive to applying this method to the dynamic defense of microservices in the cloud. Full article
(This article belongs to the Special Issue Cyber Attacks: Threats and Security Solutions)
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