# A Trust-Based Model for Secure Routing against RPL Attacks in Internet of Things
## 2 Related Work
### State-of-the-Art  
IoT security has been worked upon continuously with the advent of smart devices. Numerous security techniques and solutions, including machine learning/deep learning [24], IDS-based, and trust-based [25; 26; 27; 28] are proposed for IoT routing and network security. For addressing RPL attacks, existing mitigation techniques are typically based on either combining procedures in RPL or modifications in current RPL, for example, revising Objective Function (OF). A trust-based method, SecTrust [14], is proposed for secure communication in IoT. By specifying its own OF, the proposed method is incorporated with RPL, thus establishing a new trust-aware and secure RPL routing protocol. Network efficiency and packet loss rate are assessed, including Sybil and Rank attacks detection. Trust evaluation, based on fuzzy logic, allows only trusted nodes to communicate through the threshold-based advertisement of trust with each other. Although their work in detecting and isolating attacker nodes is promising, its success against colluding attacks is not analysed. In addition, some of their conventions are relevant only to the static scenarios, such as smart home, and do not involve mobility-based parameters in trust computation or analysis. Similarly, a SecTrust revision is proposed [29] for the evaluation of Blackhole attacks using testbed. Moreover, the results are evaluated only for static topology. Furthermore, mobile nodes, power usage, and End-to-End delay are not analysed. For the IoT, a trust model based on multiple dimensions is proposed by [16] in which Quality of Service (QoS), Quality of P2P Communication (QPC), and contextual knowledge are incorporated. The model is embedded into RPL, and for Sybil, Blackhole, and Rank attacks, the results are evaluated. In contrast to default RPL objective functions, such as OF0 and MRHOF, the results show major improvements for average energy consumption, packet loss ratio, E2E delays, and parent change frequency. However, for practical situations involving attacks in mobile environments, the assessment is not sufficient. In comparison, mobile sink and its effects are not studied. Moreover, the authors' focus is neither on how their model and trust metrics calculations are integrated into RPL nor how the attacks are detected with embedding trust [15]. In [30], a trust-aware model is proposed based on Random Forest and subjective logic for identification of sinkhole attack in RPL. Another trust-based IDS for RPL is proposed in [31] for solving the fabricated parent change vulnerabilities in RPL. Similarly, a trust-based authentication scheme is proposed [32] for mitigating the Rank, Sybil, Blackhole, and Man-in-the-Middle attacks. Ref. [33] presented a lightweight countermeasure against DODAG Information Solicitation (DIS) attack based on adaptively adjusted thresholds. Similarly, ref. [34] presented a load balancing mechanism to mitigate DIS flooding attacks. Ref. [35] introduced a new attack in RPL named Dropped Destination Advertisement Object (DDAO) and a distributed lightweight IDS to counter this attack. Ref. [36] proposed an Echelon value-based metric for objective function for early detection and isolation of Rank attack. For social IoT, ref. [37] proposed trust-based and optimized RPL-based routing. Similarly, ref. [38] enhanced RPL for candidate parent nodes for mitigating worst parent attack in RPL. A reputation-based RPL protocol is proposed by [39] for detection of Selective Forwarding attack in IoT. A trust-aware and cooperative routing protocol, MRTS, is proposed by [15]. Trust calculation in MRTS is based on adding a new parameter, ETX. Their proposed method is effective in terms of packet delivery ratio, energy, throughput, and node rank change. MRTS uses the IDS approach for attacks detection and isolation. Hence from computational aspect, it requires a hardware security chip embedded in each node [40]. Furthermore, the mobility-based metrics and scenarios are not considered for testing its functionalities under routing attacks.