29,664 research outputs found
Towards Securing Peer-to-peer SIP in the MANET Context: Existing Work and Perspectives
The Session Initiation Protocol (SIP) is a key building block of many social applications, including VoIP communication and instant messaging. In its original architecture, SIP heavily relies on servers such as proxies and registrars. Mobile Ad hoc NETworks (MANETs) are networks comprised of mobile devices that communicate over wireless links, such as tactical radio networks or vehicular networks. In such networks, no fixed infrastructure exists and server-based solutions need to be redesigned to work in a peer-to-peer fashion. We survey existing proposals for the implementation of SIP over such MANETs and analyze their security issues. We then discuss potential solutions and their suitability in the MANET context
A survey on pseudonym changing strategies for Vehicular Ad-Hoc Networks
The initial phase of the deployment of Vehicular Ad-Hoc Networks (VANETs) has
begun and many research challenges still need to be addressed. Location privacy
continues to be in the top of these challenges. Indeed, both of academia and
industry agreed to apply the pseudonym changing approach as a solution to
protect the location privacy of VANETs'users. However, due to the pseudonyms
linking attack, a simple changing of pseudonym shown to be inefficient to
provide the required protection. For this reason, many pseudonym changing
strategies have been suggested to provide an effective pseudonym changing.
Unfortunately, the development of an effective pseudonym changing strategy for
VANETs is still an open issue. In this paper, we present a comprehensive survey
and classification of pseudonym changing strategies. We then discuss and
compare them with respect to some relevant criteria. Finally, we highlight some
current researches, and open issues and give some future directions
Emerging privacy challenges and approaches in CAV systems
The growth of Internet-connected devices, Internet-enabled services and Internet of Things systems continues at a rapid pace, and their application to transport systems is heralded as game-changing. Numerous developing CAV (Connected and Autonomous Vehicle) functions, such as traffic planning, optimisation, management, safety-critical and cooperative autonomous driving applications, rely on data from various sources. The efficacy of these functions is highly dependent on the dimensionality, amount and accuracy of the data being shared. It holds, in general, that the greater the amount of data available, the greater the efficacy of the function. However, much of this data is privacy-sensitive, including personal, commercial and research data. Location data and its correlation with identity and temporal data can help infer other personal information, such as home/work locations, age, job, behavioural features, habits, social relationships. This work categorises the emerging privacy challenges and solutions for CAV systems and identifies the knowledge gap for future research, which will minimise and mitigate privacy concerns without hampering the efficacy of the functions
- …