计算机科学
密钥管理
钥匙(锁)
可扩展性
计算机网络
正确性
分布式计算
节点(物理)
弹性(材料科学)
计算机安全
背景(考古学)
密码学
工程类
数据库
古生物学
物理
结构工程
生物
热力学
程序设计语言
作者
Saïd Bettayeb,Mohamed-Lamine Messai,Sofiane Mounine Hemam
出处
期刊:Ad hoc networks
[Elsevier]
日期:2023-10-01
卷期号:149: 103250-103250
被引量:6
标识
DOI:10.1016/j.adhoc.2023.103250
摘要
Information and communication security is a critical concern in the rapid growth of Internet of Things (IoT) networks that need to exchange sensitive data. Therefore, key management is essential to address such networks’ security problems. In this context, several existing research work focuses on key management solutions, which consider the resource-limitation of IoT devices. However, the weaknesses of these solutions are (1) the lack of protection for sensitive parameters during transmission, (2) security and performance metrics’ misbalancing, and (3) the vulnerability to node-compromising attacks. This paper presents a new key management scheme based on pre-distributed vectors to overcome these limits to secure key establishment, refresh, and revocation. Moreover, the network area is divided into subareas, which makes our solution lightweight, flexible, scalable, and resilient to multiple attacks while minimizing communications, computation, and storage overheads on IoT devices. We assess the proposed scheme by using (1) the BAN (Burrows Abadi Needham) formal verification logic, (2) the informal security to demonstrate its resilience against some known attacks, and (3) the performance analysis to prove its correctness. The obtained results show that the proposed scheme is more efficient than other schemes in terms of storage by saving more than 81.84%, communications by 100% during the group-wise key establishment, computation overheads by reducing the number of multiplication operations to 50%, and energy consumption by saving up to 99.99% during the group-wise key establishment phase. Moreover, the results show that our scheme is more resilient against node capture attacks by up to 96.43% during the initialization phase and by more than 9.89% after, making it suitable for use in resource-limited IoT networks.
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