Biblio

The advancement in technologies like IoT, device-to-device communication lead to concepts like smart home and smart cities, etc. In smart home architecture, different devices such as home appliances, personal computers, surveillance cameras, etc. are connected to the Internet and enable the user to monitor and control irrespective of time and location. IPv6-enabled 6LoWPAN is a low-power, low-range communication protocol designed and developed for the short-range IoT applications. 6LoWPAN is based on IEEE 802.15.4 protocol and IPv6 network protocol for low range wireless applications. Although 6LoWPAN supports different routing protocols, RPL is the widely used routing protocol for low power and lossy networks. In this work, we have taken an IoT enabled smart home environment, in which 6LoWPAN is used as a communication and RPL as a routing protocol. The performance of this proposed network model is analyzed based on the different performance metrics such as latency, PDR, and throughput. The proposed model is simulated using Cooja simulator running over the Contiki OS. Along with the Cooja simulator, the network analyzer tool Wireshark is used to analyze the network behaviors.

The Internet of Things (IoT) is a concept that allows the networking of various objects of everyday life and communications on the Internet without human interaction. The IoT consists of Low-Power and Lossy Networks (LLN) which for routing use a special protocol called Routing over Low-Power and Lossy Networks (RPL). Due to the resource-constrained nature of RPL networks, they may be exposed to a variety of internal attacks. Neighbor attack and DIS attack are the specific internal attacks at this protocol. This paper presents an anomaly-based lightweight Intrusion Detection System (IDS) based on threshold values for detecting attacks on the RPL protocol. The results of the simulation using Cooja show that the proposed model has a very high True Positive Rate (TPR) and in some cases, it can be 100%, while the False Positive Rate (FPR) is very low. The results show that the proposed model is fully effective in detecting attacks and applicable to large-scale networks.

Internet of Things is attracting a lot of interest in the modern world and has become a part of daily life leading to a large scale of distribution of Low power and Lossy Networks (LLN). For such networks constrained by low power and storage, IETF has proposed RPL an open standard routing protocol. However RPL protocol is exposed to a number of attacks which may degrade the performance and resources of the network leading to incorrect output. In this paper, to address Wormhole and Grayhole attack we propose a light weight Trust based mechanism. The proposed method uses direct trust which is computed based on node properties and Indirect Trust which is based on opinion of the neighboring nodes. The proposed method is energy friendly and does not impose excessive overhead on network traffic.

In Sybil attacks, a physical adversary takes multiple fabricated or stolen identities to maliciously manipulate the network. These attacks are very harmful for Internet of Things (IoT) applications. In this paper we implemented and evaluated the performance of RPL (Routing Protocol for Low-Power and Lossy Networks) routing protocol under mobile sybil attacks, namely SybM, with respect to control overhead, packet delivery and energy consumption. In SybM attacks, Sybil nodes take the advantage of their mobility and the weakness of RPL to handle identity and mobility, to flood the network with fake control messages from different locations. To counter these type of attacks we propose a trust-based intrusion detection system based on RPL.