Fuzzy, Dynamic and Trust Based Routing Protocol for IoT

被引:21
|
作者
Hashemi, Seyyed Yasser [1 ]
Aliee, Fereidoon Shams [1 ]
机构
[1] Shahid Beheshti Univ, Fac Comp Sci & Engn, Tehran, Iran
关键词
FDTM-IoT; FDTM-RPL; Fuzzy logic; Internet of Things; Routing attacks; Trust model; RPL; INTERNET;
D O I
10.1007/s10922-020-09535-y
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Internet of Things (IoT) could be described as the pervasive and global network where real-world entities augmented with computing devices, sensors and actuators are connected to the Internet, enabling them to publish their generated data. Thus, an efficient and secure routing service is required to enable efficient communication of information among IoT nodes. This sophisticated, dynamic, and ultra-large-scale network requires the use of contextual information, attention to security issues and the consideration of service quality to make proper routing decisions. The routing protocol for low-power and lossy networks (RPL) and improved versions of it are experiencing severe performance gaps under network attacks such as BLACKHOLE, SYBIL and RANK. This paper uses the concept of trust as an umbrella to cover countermeasures for addressing the consequences of attacks. Accordingly, a multi-fuzzy, dynamic and hierarchical trust model (FDTM-IoT) is proposed. The main dimensions of this model are contextual information (CI), quality of service (QoS) and quality of P2P communication (QPC). Each dimension also has its own sub-dimensions or criteria. FDTM-IoT is integrated into RPL (FDTM-RPL) as objective function. FDTM-RPL use trust to deal with attacks. In the proposed method, fuzzy logic has been used in trust calculations to consider uncertainty as one of the most important inherent characteristics of trust. The efficiency of FDTM-RPL in various scenarios (including small-scale to large-scale networks, mobile environment as well as different transmission rates and under different attacks) has been compared with standard RPL protocols. FDTM-RPL provides high performance in detecting attacks. Additionally, it improves network performance in a variety of criteria, including end-to-end delay and packet loss rates.
引用
收藏
页码:1248 / 1278
页数:31
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