Biblio

Filters: Author is Markantonakis, K.  [Clear All Filters]
2018-02-02
Akram, R. N., Markantonakis, K., Mayes, K., Habachi, O., Sauveron, D., Steyven, A., Chaumette, S..  2017.  Security, privacy and safety evaluation of dynamic and static fleets of drones. 2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC). :1–12.

Interconnected everyday objects, either via public or private networks, are gradually becoming reality in modern life - often referred to as the Internet of Things (IoT) or Cyber-Physical Systems (CPS). One stand-out example are those systems based on Unmanned Aerial Vehicles (UAVs). Fleets of such vehicles (drones) are prophesied to assume multiple roles from mundane to high-sensitive applications, such as prompt pizza or shopping deliveries to the home, or to deployment on battlefields for battlefield and combat missions. Drones, which we refer to as UAVs in this paper, can operate either individually (solo missions) or as part of a fleet (group missions), with and without constant connection with a base station. The base station acts as the command centre to manage the drones' activities; however, an independent, localised and effective fleet control is necessary, potentially based on swarm intelligence, for several reasons: 1) an increase in the number of drone fleets; 2) fleet size might reach tens of UAVs; 3) making time-critical decisions by such fleets in the wild; 4) potential communication congestion and latency; and 5) in some cases, working in challenging terrains that hinders or mandates limited communication with a control centre, e.g. operations spanning long period of times or military usage of fleets in enemy territory. This self-aware, mission-focused and independent fleet of drones may utilise swarm intelligence for a), air-traffic or flight control management, b) obstacle avoidance, c) self-preservation (while maintaining the mission criteria), d) autonomous collaboration with other fleets in the wild, and e) assuring the security, privacy and safety of physical (drones itself) and virtual (data, software) assets. In this paper, we investigate the challenges faced by fleet of drones and propose a potential course of action on how to overcome them.

2017-11-13
Shepherd, C., Arfaoui, G., Gurulian, I., Lee, R. P., Markantonakis, K., Akram, R. N., Sauveron, D., Conchon, E..  2016.  Secure and Trusted Execution: Past, Present, and Future - A Critical Review in the Context of the Internet of Things and Cyber-Physical Systems. 2016 IEEE Trustcom/BigDataSE/ISPA. :168–177.

Notions like security, trust, and privacy are crucial in the digital environment and in the future, with the advent of technologies like the Internet of Things (IoT) and Cyber-Physical Systems (CPS), their importance is only going to increase. Trust has different definitions, some situations rely on real-world relationships between entities while others depend on robust technologies to gain trust after deployment. In this paper we focus on these robust technologies, their evolution in past decades and their scope in the near future. The evolution of robust trust technologies has involved diverse approaches, as a consequence trust is defined, understood and ascertained differently across heterogeneous domains and technologies. In this paper we look at digital trust technologies from the point of view of security and examine how they are making secure computing an attainable reality. The paper also revisits and analyses the Trusted Platform Module (TPM), Secure Elements (SE), Hypervisors and Virtualisation, Intel TXT, Trusted Execution Environments (TEE) like GlobalPlatform TEE, Intel SGX, along with Host Card Emulation, and Encrypted Execution Environment (E3). In our analysis we focus on these technologies and their application to the emerging domains of the IoT and CPS.

2015-05-01
Akram, R.N., Markantonakis, K., Mayes, K..  2014.  Trusted Platform Module for Smart Cards. New Technologies, Mobility and Security (NTMS), 2014 6th International Conference on. :1-5.

Near Field Communication (NFC)-based mobile phone services offer a lifeline to the under-appreciated multiapplication smart card initiative. The initiative could effectively replace heavy wallets full of smart cards for mundane tasks. However, the issue of the deployment model still lingers on. Possible approaches include, but are not restricted to, the User Centric Smart card Ownership Model (UCOM), GlobalPlatform Consumer Centric Model, and Trusted Service Manager (TSM). In addition, multiapplication smart card architecture can be a GlobalPlatform Trusted Execution Environment (TEE) and/or User Centric Tamper-Resistant Device (UCTD), which provide cross-device security and privacy preservation platforms to their users. In the multiapplication smart card environment, there might not be a prior off-card trusted relationship between a smart card and an application provider. Therefore, as a possible solution to overcome the absence of prior trusted relationships, this paper proposes the concept of Trusted Platform Module (TPM) for smart cards (embedded devices) that can act as a point of reference for establishing the necessary trust between the device and an application provider, and among applications.