This paper introduces an “Indicator of Risk (IoR) Library” that leverages the MITRE ATT&CK for Industrial Control Systems (ICS) knowledge base to support continuous risk monitoring. This allows also making use of variables that are already being monitored to analyse risks in a continuous basis. IoRs broaden the concept of Indicators of Compromise by combining detection strategies with probabilistic inference as a tool for quantifying cyber-security risks. The latest version of the Library has 95 IoRs and has been reviewed by professionals from three major companies and cross-referenced against detection use-cases implemented by other researchers to validate its potential to identify variables for monitoring cyber-risks in ICS.

V2V messaging systems enable vehicles to exchange safety related information with each other and support road safety and traffic efficiency applications. The effectiveness of these applications depends on the correctness of the information reported in the V2V messages. Consequently, the possibility that malicious agents may send false information is a major concern. The physical features of a transmission are relatively difficult to fake, and one of the most effective ways to detect lying is to check for consistency of these features with vehicle position information in the message. In this paper, we propose a message consistency checking scheme whereby a vehicle acting independently can utilise the strength and variability of received signals to estimate the distance from a transmitting vehicle without prior knowledge of the environment (building density, traffic conditions, etc.). The distance estimate can then be used to check the correctness of the reported position. We show through simulation that our RMCSS method can detect false information with an accuracy of about 90% for separation distances less than 100m. We believe this is sufficient for the method to be a valuable adjunct to use of digital signatures to establish trust.

Road safety applications such as intersection collision warning, emergency brake warnings, etc., rely on the periodic broadcast of messages by vehicles and roadside infrastructure. PKI-based approaches ensuring the integrity of messages and the legitimacy of the sender are computationally expensive and result in long messages. Approaches based on hashed key chains such as Timed Efficient Stream Loss-tolerant Authentication (TESLA) offer an alternative solution. Because they use symmetric-key cryptography, the messages are shorter and less expensive to verify. However, they bring their own challenges. This paper focuses on one challenge, the problem of distributing key chain commitments required for message verification. We propose and evaluate two techniques, respectively involving periodic broadcast of commitment keys by the vehicles themselves and selective unicasting by a central V2X Application Server (VAS). We find that the VAS-centric solution has advantages over the vehicle-centric solution and a related solution proposed by other researchers.

Opportunities arising from IoT-enabled applications are significant, but market growth is inhibited by concerns over security and complexity. To address these issues, we propose the ERAMIS methodology, which is based on instantiation of a reference architecture that captures common design features, embodies best practice, incorporates good security properties by design, and makes explicit provision for operational security services and processes.

Abstract This paper presents a comparative analysis of the feasibility studies submitted by six UK cities (London, Birmingham, Manchester, Glasgow, Bristol and Milton Keynes). The datasets were collected during the period of February–March 2017 by exploring their Open Data resources, common visions of their smart programmes and the themes of their projects. The aim of this work is to raise awareness and access of the existing data resources, encourage alignment of data collection and curation among projects with compatible objectives in different cities and to identify the gaps in coverage that are hampering achievement of the cities’ visions. In this research, we distinguish between stored datasets that are accessible via data hubs, and live data that are only accessible via application programming interfaces in real time. Given that our findings are purely based on stored Open Data, we conclude that the Smart City dream will be only achieved in reality, where those involved in Smart Cities-related projects co-operate and share both experiences and resources in order to maximize progress towards the common goal but to minimize duplication of efforts and repetition of the same mistakes.

Information systems exist in every aspect of our life and our society depends on them enormously. Despite this reliance, these systems are often unreliable, prone to errors, and pose vulnerabilities for potential security attacks. We are often faced with a choice between using a valuable (or even an essential) system, which is not fully trustworthy, or else forgoing the services it provides. Developing a trustworthy software system is a challenging task. The system's overall trustworthiness depends on trust relationships that are usually assumed and not properly analysed during the analysis and design of the system. The lack of appropriate analysis of such trust relationships, or the lack of appropriate justification of relevant trust assumptions, usually results in systems that can potentially fail to fully achieve those functionalities that depend on such trust relationships. In this paper, we present a meta-model for a modelling language that allows developers to capture possible trust relationships and to reason about them. The meta-model includes a set of trust based concepts, which support the development of trustworthy systems. A case study from the UK health care sector is used to illustrate the usefulness of the meta-model.

We describe Glosser, a system that supports students in writing essays by 1) scaffolding their reflection with trigger questions, and 2) using text mining techniques to provide content clues that can help answer those questions. A comparison with other computer generated feedback and scorings systems is provided to explain the novelty of the approach. We evaluate the system with Wiki pages produced by postgraduate students as part of their assessment.

Multi-agent software systems can be modeled as complex, dynamic systems in which agent adaptation and interaction occur continuously and concurrently. A genetics inspired view has agent adaptation occurring via the exchange of encoded agent characteristics (genes). An economics inspired view has agent adaptation driven by changes in prices and supply and demand. Interactions of economics and genetics models have a long history in evolutionary computation. This paper describes new work towards a synergistic combination of these views, in agent-based settings. The paper includes a re-statement of Holland's (1992) basic theories in an agent-based context, a discussion of different self-organization principles taken from economics, presentation of results from two agent systems that synergize economics and genetics models, and a discussion of future directions.