Research and standardisation efforts in the fields of Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) are leading towards the adoption of TCP/IP for deployments of networks of severely constrained smart embedded objects. As a result, wireless sensors can now be uniquely identified by an IPv6 address and thus be directly connected to and reachable from the internet. This has a series of advantages but also exposes sensor deployments to new security vulnerabilities. Should a deployment be compromised, post-incident analysis can provide information about the nature of the attack by inspecting the network’s state and traffic during the time period prior, during and after the attack. In this paper we adopt traffic forensic techniques in order to achieve post-hoc detection of attacks against availability in IPv6-based Low-Power Wireless Personal Area Networks. To this end, we first implement an attack which exploits inherent vulnerabilities of the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). Subsequently, we present an automated method to detect and analyse this attack by examining network packet captures.
V. Kumar, G. Oikonomou, T. Tryfonas, D. Page, I. Phillips, "Digital Investigations for IPv6-Based Wireless Sensor Networks", Digital Investigation, Elsevier, 11, Supplement 2(0), pp. S66-S75, 2014 (Fourteenth Annual DFRWS Conference)
Developments in the field of Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) mean that sensor devices can now be uniquely identified using an IPv6 address and, if suitably connected, can be directly reached from the Internet. This has a series of advantages but also introduces new security vulnerabilities and exposes sensor deployments to attack. A compromised Internet host can send malicious information to the system and trigger incorrect actions. Should an attack take place, post-incident analysis can reveal information about the state of the network at the time of the attack and ultimately provide clues about the tools used to implement it, or about the attacker's identity. In this paper we critically assess and analyse information retrieved from a device used for IoT networking, in order to identify the factors which may have contributed to a security breach. To achieve this, we present an approach for the extraction of RAM and flash contents from a sensor node. Subsequently, we analyse extracted network connectivity information and we investigate the possibility of correlating information gathered from multiple devices in order to reconstruct the network topology. Further, we discuss experiments and analyse how much information can be retrieved in different scenarios. Our major contribution is a mechanism for the extraction, analysis and correlation of forensic data for IPv6-based WSN deployments, accompanied by a tool which can analyse RAM dumps from devices running the Contiki Operating System (OS) and powered by 8051-based, 8-bit micro-controllers.
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