Architectural Support for Securing Sensor Networks Against Remote Attacks

Sensor network devices are no less vulnerable to remote attacks, such as malicious worms, than their general purpose computer counterparts, and are presented with unique threats because of the hostile environments sensors are placed in. It is well known that sensor devices place challenging constraints on any attempt to secure them against these attacks, including small performance and power budgets, infrequent patch updates, and long service lives. However, in this paper we demonstrate that security can be built into sensor devices “from the ground up.” In this paper we apply dynamic information flow tracking (DIFT) to sensor devices, where network data is tagged as untrusted and then these tags propagate throughout the system. Our results demonstrate that minor hardware modifications to sensor devices can provide sufficient security guarantees against remote control data attacks. To make these guarantees we address all five dynamic information flow dependency types (copy, computation, load-address, store-address, and control), whereas DIFT schemes for general purpose computers are empirically only able to address the first two. Rigorous testing of eight applications shows that no modifications to existing operating systems, compilers, applications, or binaries is necessary.