Biblio

Implantable medical devices (IMDs) typically rely on proprietary protocols to wirelessly communicate with external device programmers. In this paper, we fully reverse engineer the proprietary protocol between a device programmer and a widely used commercial neurostimulator from one of the leading IMD manufacturers. For the reverse engineering, we follow a black-box approach and use inexpensive hardware equipment. We document the message format and the protocol state-machine, and show that the transmissions sent over the air are neither encrypted nor authenticated. Furthermore, we conduct several software radio-based attacks that could compromise the safety and privacy of patients, and investigate the feasibility of performing these attacks in real scenarios. Motivated by our findings, we propose a security architecture that allows for secure data exchange between the device programmer and the neurostimulator. It relies on using a patient»s physiological signal for generating a symmetric key in the neurostimulator, and transporting this key from the neurostimulator to the device programmer through a secret out-of-band (OOB) channel. Our solution allows the device programmer and the neurostimulator to agree on a symmetric session key without these devices needing to share any prior secrets; offers an effective and practical balance between security and permissive access in emergencies; requires only minor hardware changes in the devices; adds minimal computation and communication overhead; and provides forward and backward security. Finally, we implement a proof-of-concept of our solution.

The aim of this paper is to find cellular automata (CA) rules that are used to describe S-boxes with good cryptographic properties and low implementation cost. Up to now, CA rules have been used in several ciphers to define an S-box, but in all those ciphers, the same CA rule is used. This CA rule is best known as the one defining the Keccak $\chi$ transformation. Since there exists no straightforward method for constructing CA rules that define S-boxes with good cryptographic/implementation properties, we use a special kind of heuristics for that – Genetic Programming (GP). Although it is not possible to theoretically prove the efficiency of such a method, our experimental results show that GP is able to find a large number of CA rules that define good S-boxes in a relatively easy way. We focus on the 4 x 4 and 5 x 5 sizes and we implement the S-boxes in hardware to examine implementation properties like latency, area, and power. Particularly interesting is the internal encoding of the solutions in the considered heuristics using combinatorial circuits; this makes it easy to approximate S-box implementation properties like latency and area a priori.