Internet of Things (IoT) device software frequently handles sensitive data. This software has to be resistant to faults to prevent leakage and ensure data privacy and security. Source code hardening is a common way to make software fault-tolerant. However, the effectiveness and performance impact of a chosen hardening technique are not always obvious. Moreover, it becomes increasingly difficult to predict potential attack vectors and implement proper countermeasures. To assist in this task, we developed Chaos Duck, an automatic tool for IoT software fault-tolerance analysis. Chaos Duck emulates various fault types and provides statistics on their impact on software security and stability. We present a case study in which we use Chaos Duck to compare five software hardening techniques applied to the PRESENT block cipher implementation. We show that some simple hardening techniques may improve fault-tolerance, while others can instead reduce overall security and introduce new vulnerabilities. Our contributions are twofold: we offer a software fault-tolerance analysis tool to IoT developers seeking to make their software secure and robust, and we shed light on the efficiency of various hardening techniques.

Fault injection is widely used as a method to evaluate the robustness and security of a system against many kinds of faults and attacks. Recent works have considered many ways to demonstrate security risks and viable attacks using fault injection, and some have also proposed countermeasures. However, no general and formal definition of fault injection or countermeasure has been provided that can be used to reason about such attacks. This leaves significant results in this area to be ad-hoc and without broad applicability. This paper presents formal definitions of both fault injection on an arbitrary system and what an effective countermeasure is. These definitions are used to prove that fault injection attacks cannot in general be prevented (by any countermeasure). An example is presented that demonstrates how to construct an effective countermeasure for a specific fault injection that parallels some well known approaches. Further extensions to account for probabilistic behaviour and systems with time are also presented. These definitions and results demonstrate formal proofs about the security and defences of systems in ways that can be used, thus yielding a broadly applicable approach that can formalise fault injections and countermeasures in the future.

Future-generation healthcare systems will be highly distributed, combining centralised hospital systems with decentralised home-, work-and environment-based monitoring and diagnostics systems. These will reduce costs and injury-related risks whilst both improving quality of service, and reducing the response time for diagnostics and treatments made available to patients. To make this vision possible, medical data must be accessed and shared over a variety of mediums including untrusted networks. In this paper, we present the design and initial implementation of the SERUMS tool-chain for accessing, storing, communicating and analysing highly confidential medical data in a safe, secure and privacy-preserving way. In addition, we describe a data fabrication framework for generating large volumes of synthetic but realistic data, that is used in the design and evaluation of the tool-chain. We demonstrate the present version of our technique on a use case derived from the Edinburgh Cancer Centre, NHS Lothian, where information about the effects of chemotherapy treatments on cancer patients is collected from different distributed databases, analysed and adapted to improve ongoing treatments.

Application requirements evolve over time and the underlying protocols need to adapt. Most transport protocols evolve by negotiating protocol extensions during the handshake. Experience with TCP shows that this leads to delays of several years or more to widely deploy standardized extensions. In this paper, we revisit the extensibility paradigm of transport protocols.

Summary Fault injection has increasingly been used both to attack software applications and to test system robustness. Detecting fault injection vulnerabilities has been approached with a variety of different but limited methods. This paper proposes an extension of a recently published general model checking based process to detect fault injection vulnerabilities in binaries. This new extension makes the general process scalable to real‐world implementations, which is demonstrated by detecting vulnerabilities in different cryptographic implementations.

The largest botnet distributed denial of service attacks in history have been executed by devices controlled by the Mirai botnet trojan. To prevent Mirai from spreading, this paper presents and evaluates techniques to classify binary samples as Mirai based on their syntactic and behavioral properties. Syntactic malware detection is shown to have a good detection rate and no false positives, but to be very easy to circumvent. Behavioral malware detection is resistant to simple obfuscation and has better detection rate than syntactic detection, while keeping false positives to zero. This paper demonstrates these results, and concludes by showing how to combine syntactic and behavioral analysis techniques for the detection of Mirai.

Abstract Traditional combinatory logic uses combinators S and K to represent all Turing-computable functions on natural numbers, but there are Turing-computable functions on the combinators themselves that cannot be so represented, because they access internal structure in ways that S and K cannot. Much of this expressive power is captured by adding a factorisation combinator F. The resulting SF-calculus is structure complete, in that it supports all pattern-matching functions whose patterns are in normal form, including a function that decides structural equality of arbitrary normal forms. A general characterisation of the structure complete, confluent combinatory calculi is given along with some examples. These are able to represent all their Turing-computable functions whose domain is limited to normal forms. The combinator F can be typed using an existential type to represent internal type information.