使用默克尔树在OppNets中建立信任关系

Asma'a Ahmad, Majeed Alajeely, R. Doss
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引用次数: 5

摘要

机会网络(OppNets)面临着各种各样的攻击,其中包括丢包攻击。OppNets面临的安全挑战是有效、安全地转发数据,并保证数据的无丢失传输。由于OppNets固有的特性,包括频繁的分区、长时间的延迟和间歇性的连接,安全性和信任度在研究中越来越受欢迎。针对选择性丢包攻击,提出了一种有效的恶意路径和恶意节点检测技术。在我们的算法中,我们使用Merkle树哈希技术开发了一个可靠的检测机制。恶意路径检测结果用于目标节点对每条路径建立信任,然后使用节点建立的信任值来检测恶意节点。仿真结果表明,该技术能够准确地检测出恶意路径。结果还表明,随着仿真时间的增加,中间节点与目的节点建立信任的时间增加,节点检测精度也随之提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Establishing trust relationships in OppNets using Merkle trees
Opportunistic Networks (OppNets) are exposed to a variety of attacks, among them are packet dropping attacks. The security challenges in OppNets is to effectively and securely forward data and guarantee their delivery without any loss. Security and trust in OppNets have gained popularity in research because of their inherent features, including frequent partitions, long delays and intermittent connectivity. This paper presents an efficient malicious path and malicious node detection technique against selective packet dropping attacks. In our algorithm we have developed a solid detection mechanism using the Merkle tree hashing technique. The result of malicious path detection is used to build trust by destination nodes for each path, the built trust value of nodes is then used to detect malicious nodes. Simulation results show that the technique accurately detects malicious paths. The results also show that with the increase of simulation time, node detection accuracy also increases as intermediate nodes have more time to establish trust with destination nodes.
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