Kholidy Hisham A
Department of Networks and Computer Security, College of Engineering, State University of New York (SUNY) Polytechnic Institute, Utica, NY 13502, USA.
Sensors (Basel). 2021 Dec 21;22(1):9. doi: 10.3390/s22010009.
Overall, 5G networks are expected to become the backbone of many critical IT applications. With 5G, new tech advancements and innovation are expected; 5G currently operates on software-defined networking. This enables 5G to implement network slicing to meet the unique requirements of every application. As a result, 5G is more flexible and scalable than 4G LTE and previous generations. To avoid the growing risks of hacking, 5G cybersecurity needs some significant improvements. Some security concerns involve the network itself, while others focus on the devices connected to 5G. Both aspects present a risk to consumers, governments, and businesses alike. There is currently no real-time vulnerability assessment framework that specifically addresses 5G Edge networks, with regard to their real-time scalability and dynamic nature. This paper studies the vulnerability assessment in the 5G networks and develops an optimized dynamic method that integrates the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the hexagonal fuzzy numbers to accurately analyze the vulnerabilities in 5G networks. The proposed method considers both the vulnerability and 5G network dynamic factors such as latency and accessibility to find the potential attack graph paths where the attack might propagate in the network and quantifies the attack cost and security level of the network. We test and validate the proposed method using our 5G testbed and we compare the optimized method to the classical TOPSIS and the known vulnerability scanner tool, Nessus.
总体而言，预计5G网络将成为许多关键IT应用的支柱。借助5G，有望实现新的技术进步和创新；5G目前基于软件定义网络运行。这使5G能够实施网络切片以满足每个应用的独特需求。因此，5G比4G LTE及前代网络更灵活、更具可扩展性。为避免日益增长的黑客攻击风险，5G网络安全需要一些重大改进。一些安全问题涉及网络本身，而其他问题则聚焦于连接到5G的设备。这两个方面都给消费者、政府和企业带来风险。目前尚无专门针对5G边缘网络实时可扩展性和动态特性的实时漏洞评估框架。本文研究了5G网络中的漏洞评估，并开发了一种优化的动态方法，该方法将逼近理想解排序法（TOPSIS）与六边形模糊数相结合，以准确分析5G网络中的漏洞。所提出的方法既考虑了漏洞，又考虑了5G网络的动态因素，如延迟和可达性，以找到攻击可能在网络中传播的潜在攻击图路径，并量化攻击成本和网络安全级别。我们使用5G测试平台对所提出的方法进行了测试和验证，并将优化后的方法与经典TOPSIS和已知的漏洞扫描工具Nessus进行了比较。
