Wireless Sensor Networks (WSNs), as a key part of the Internet of Things (IoT), allow the representation of the dynamic characteristics of the physical world in the Internet's virtual world. Thus, sensor nodes are henceforth considered as Internet hosts and may act freely as web clients or servers. Undoubtedly, security and end-users privacy issues rise and become more severe in the IoT, due to the asymmetric nature of the communications between sensor nodes and the ordinary Internet hosts. Many solutions propose to use the classical IP-based security protocols for IoT, after adapting them to WSN's constraints by either messages compression or computational-load distribution techniques. In this paper we propose a 6LoWPAN (IPv6 over Low power Wireless Personal Area Networks) compression model for HIP (Host Identity Protocol) header, as well as, an adapted distribution scheme of the computational load in HIP's key agreement process. For an extreme lightweight end-to-end security, we propose to combine both compression and distribution models for HIP in WSNs side, in the IoT. The partial evaluation results show that the proposed protocol, named compressed and distributed HIP (CD-HIP), is more adapted than the standard HIP, while introducing minor header communication overhead.

We deal with privacy problems resulting from the possibility of communication-flow identification and tracking in the currently designed IPv6 Low Power Wireless Personal Area Network (6LoWPAN)-based solutions for the Internet of Things (IoT). We propose a solution that makes it difficult for an attacker to detect that a communication is taking place between a source and a destination entities by disguising the main flow identifying fields in 6LoWPAN packet headers. Our solution is based on the One Time Address (OTA) approach proposed for the traditional Internet, with a focus on low complexity, memory footprint, and energy consumption. We evaluated our solution that we called micro OTA (uOTA) by implementing it on the Cooja simulator and compared it with micro Moving Target IPv6 Defense (uMT6D). Results show that our solution improves communication flow privacy in IoT and outperforms uMT6D in energy consumption, network overhead, latency, and privacy preservation.

Wireless Sensor Networks (WSNs) are widely and successfully employed in various application domains. They are easily deployed to collect valuable information and monitor potential environmental phenomena. However, the special nature of WSNs as well as their severe constraints and resource limitations make them vulnerable to various types of threats. Replay attack, is one example. According to this attack, the adversary intercepts and replays several times the same (old) message leading either to missed alerts or to false alerts. Many solutions have been proposed to mitigate message replay attack. However, all these solutions are of cryptographic natures and consider only external attacks exercising a trivial scenario of replay attack. In fact, the attacker could be a lot smarter, and in this case, it replays only the data field in the message while keeping the remaining fields updated. This novel form of replay attack is much more dangerous and difficult to be detected. We call this attack variant by data replay attack. As sensor nodes may be easily captured and compromised, the worst scenario occurs if data replay attack is performed by an internal intruder. In this paper we propose an efficient intrusion detection framework to overcome data replay attack in WSNs. The proposed intrusion detection system is named DR-IDS (Data Replay Intrusion Detection System). The performance evaluations performed under NS2 simulator show that the proposed solution is sufficiently robust.