来源:Journal of Cybersecurity and Privacy 发布时间:2026/11/5 15:29:14
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Journal of Cybersecurity and Privacy文献清单:人工智能网络安全

期刊名:Journal of Cybersecurity and Privacy

期刊主页:https://www.mdpi.com/journal/jcp

生成式人工智能与大模型的快速发展正推动网络安全防护模式从传统规则驱动的被动防御,转向可解释、自适应、智能化的威胁检测、响应与风险治理范式。本专题汇集发表于Journal of Cybersecurity and Privacy的系列研究,系统展现人工智能在安全运营中心自动化(SOC)、开源SIEM威胁检测、深度伪造社会工程攻防、网络钓鱼识别、零信任架构演进等多元场景下的创新探索,覆盖大语言模型与AI智能代理、机器学习威胁识别、可解释安全日志分析、AI区块链融合防护、大模型自身漏洞挖掘等关键技术方向;同时剖析生成式AI给零信任机制带来的侵蚀风险、深度伪造语音攻击的现实危害、企业社会工程防御困境。系列成果融合综述调研、系统原型实现、实证评测等多元研究范式,共同勾勒出人工智能驱动网络安全防御体系,兼顾防御效能、可信任性与风险制衡的未来研究图景。

1. AI-Augmented SOC: A Survey of LLMs and Agents for Security Automation

人工智能增强SOC:安全自动化的llm和代理的调查

http://www.mdpi.com/2624-800X/5/4/95

Srinivas, S.; Kirk, B.; Zendejas, J.; Espino, M.; Boskovich, M.; Bari, A.; Dajani, K.; Alzahrani, N. AI-Augmented SOC: A Survey of LLMs and Agents for Security Automation.J. Cybersecur. Priv.2025, 5, 95.

2. Improving Threat Detection in Wazuh Using Machine Learning Techniques

使用机器学习技术改进Wazuh中的威胁检测

http://www.mdpi.com/2624-800X/5/2/34

Chamkar, S.A.; Zaydi, M.; Maleh, Y.; Gherabi, N. Improving Threat Detection in Wazuh Using Machine Learning Techniques.J. Cybersecur. Priv.2025, 5, 34

3. Partial Fake Speech Attacks in the Real World Using Deepfake Audio

在现实世界中使用Deepfake音频的部分虚假语音攻击

http://www.mdpi.com/2624-800X/5/1/6

Alali, A.; Theodorakopoulos, G. Partial Fake Speech Attacks in the Real World Using Deepfake Audio.J. Cybersecur. Priv.2025, 5, 6.

4. Deepfake-Driven Social Engineering: Threats, Detection Techniques, and Defensive Strategies in Corporate Environments

深度伪造驱动的社会工程:企业环境中的威胁、检测技术与防御策略

http://www.mdpi.com/2624-800X/5/2/18

Pedersen, K.T.; Pepke, L.; Stærmose, T.; Papaioannou, M.; Choudhary, G.; Dragoni, N. Deepfake-Driven Social Engineering: Threats, Detection Techniques, and Defensive Strategies in Corporate Environments.J. Cybersecur. Priv.2025, 5, 18.

5. Applications of Machine Learning in Cyber Security: A Review

机器学习在网络安全中的应用综述

http://www.mdpi.com/2624-800X/4/4/45

Vourganas, I.J.; Michala, A.L. Applications of Machine Learning in Cyber Security: A Review.J. Cybersecur. Priv.2024, 4, 972-992.

6. The Erosion of Cybersecurity Zero-Trust Principles Through Generative AI: A Survey on the Challenges and Future Directions

生成式人工智能对网络安全零信任原则的侵蚀:挑战与未来方向综述

http://www.mdpi.com/2624-800X/5/4/87

Xu, D.; Gondal, I.; Yi, X.; Susnjak, T.; Watters, P.; McIntosh, T.R. The Erosion of Cybersecurity Zero-Trust Principles Through Generative AI: A Survey on the Challenges and Future Directions.J. Cybersecur. Priv.2025, 5, 87.

7. Leveraging Large Language Models for Scalable and Explainable Cybersecurity Log Analysis

利用大型语言模型进行可扩展和可解释的网络安全日志分析

http://www.mdpi.com/2624-800X/5/3/55

Palma, G.; Cecchi, G.; Caronna, M.; Rizzo, A. Leveraging Large Language Models for Scalable and Explainable Cybersecurity Log Analysis.J. Cybersecur. Priv.2025, 5, 55.

8. AI-Blockchain Integration for Real-Time Cybersecurity: System Design and Evaluation

面向实时网络安全的ai -区块链集成:系统设计与评估

http://www.mdpi.com/2624-800X/5/3/59

Goundar, S.; Gondal, I. AI-Blockchain Integration for Real-Time Cybersecurity: System Design and Evaluation.J. Cybersecur. Priv.2025, 5, 59.

9. AI-Driven Phishing Detection: Enhancing Cybersecurity with Reinforcement Learning

人工智能驱动的网络钓鱼检测:通过强化学习增强网络安全

http://www.mdpi.com/2624-800X/5/2/26

Jabbar, H.; Al-Janabi, S. AI-Driven Phishing Detection: Enhancing Cybersecurity with Reinforcement Learning.J. Cybersecur. Priv.2025, 5, 26.

10. Vulnerability Detection in Large Language Models: Addressing Security Concerns

大型语言模型中的漏洞检测:解决安全问题

http://www.mdpi.com/2624-800X/5/3/71

Ben Yaala, S.; Bouallegue, R. Vulnerability Detection in Large Language Models: Addressing Security Concerns.J. Cybersecur. Priv.2025, 5, 71.

期刊介绍

主编:

主编:Prof. Dr. Danda B. Rawat, Howard University, USA

Journal of Cybersecurity and Privacy(ISSN 2624-800X) 是一个国际型开放获取英文学术期刊,旨在为网络安全技术各方面的研究提供一个先进的学术交流平台。期刊研究领域涵盖显示信息、计算机和网络安全、密码学、网络物理系统安全、数字取证等。

2025 Impact Factor:3.8

2025 CiteScore:8.8

Time to First Decision:23.7 Days

Acceptance to Publication:5.6 Days

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