A Certificateless Group Authenticated Key Agreement Protocol for Secure Communication in Untrusted UAV Networks. / Semal, Benjamin; Markantonakis, Konstantinos; Akram, Raja Naeem.

2018. Paper presented at The 37th DASC Digital Avionics Systems Conference, London, United Kingdom.

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Abstract

Smart cities are increasingly relying on information and communication technologies to cope with today’s challenges, including increasing population, heterogeneous economic growth, and environmental legislation hardening. The use of Unmanned Aerial Vehicles (UAVs) generates a growing interest in coping with such challenges, along with new business opportunities. As a result, it is expected to see the number of drone-based applications to rise at a very fast pace, entailing new cybersecurity risks to emerge. In this paper, we propose to tackle the problem of secure communication among untrusting parties with a certificatelessgroup authenticated key agreement (CL-GAKA) scheme. The intent is to enable confidentiality, message integrity, and authenticity in UAV-to-UAV communication. Provisioning untrusted UAV networks with trusted communication will provide ground for further research and applications, such as collaborative cybersecurity deterrence, network extension using trusted relay nodes, collaborative mission exercise in time-critical applications, or anonymous communication for user privacy. Moreover, in order to fill the gap of technology awareness, we provide an implementation and demonstrate that the generation of a session key between two users can be performed in approximately 600ms on a Raspberry Pi 3 Model B+ system-on-chip (1.4GHz Cortex- A53). Finally, the protocol is formally evaluated with the Scyther tool.
Original languageEnglish
StateAccepted/In press - 15 Aug 2018
EventThe 37th DASC Digital Avionics Systems Conference - London, United Kingdom
Duration: 23 Sep 201827 Sep 2018

Conference

ConferenceThe 37th DASC Digital Avionics Systems Conference
CountryUnited Kingdom
CityLondon
Period23/09/1827/09/18
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 31383551