4,891 research outputs found
Shortest Path Computation with No Information Leakage
Shortest path computation is one of the most common queries in location-based
services (LBSs). Although particularly useful, such queries raise serious
privacy concerns. Exposing to a (potentially untrusted) LBS the client's
position and her destination may reveal personal information, such as social
habits, health condition, shopping preferences, lifestyle choices, etc. The
only existing method for privacy-preserving shortest path computation follows
the obfuscation paradigm; it prevents the LBS from inferring the source and
destination of the query with a probability higher than a threshold. This
implies, however, that the LBS still deduces some information (albeit not
exact) about the client's location and her destination. In this paper we aim at
strong privacy, where the adversary learns nothing about the shortest path
query. We achieve this via established private information retrieval
techniques, which we treat as black-box building blocks. Experiments on real,
large-scale road networks assess the practicality of our schemes.Comment: VLDB201
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
Implementation of Space-Filling Curves on Spatial Dataset: A Review Paper
Cloud computing is the most recent innovative achievement that everybody ought to know about independent of whether you are a provider or a purchaser of innovative technology. Financial benefits are the essential driver for the Cloud, since it ensures the diminishment of capital utilize and operational utilize. The widespread use of the cloud has lead to the rise of database outsourcing. Privacy and security are the main considerations in the database outsourcing. Most of the conventional approaches provide security to outsourced data either by existing cryptographic techniques or using spatial transformation schemes. Here we propose a system which will implement and compare two space-filling algorithms (Hilbert curve and Gosper curve) on spatial data
CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap
After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in
multimedia search engines, we have identified and analyzed gaps within European research effort during our second year.
In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio-
economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown
of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on
requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the
community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our
Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as
National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core
technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research
challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal
challenges
A Survey on Wireless Security: Technical Challenges, Recent Advances and Future Trends
This paper examines the security vulnerabilities and threats imposed by the
inherent open nature of wireless communications and to devise efficient defense
mechanisms for improving the wireless network security. We first summarize the
security requirements of wireless networks, including their authenticity,
confidentiality, integrity and availability issues. Next, a comprehensive
overview of security attacks encountered in wireless networks is presented in
view of the network protocol architecture, where the potential security threats
are discussed at each protocol layer. We also provide a survey of the existing
security protocols and algorithms that are adopted in the existing wireless
network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term
evolution (LTE) systems. Then, we discuss the state-of-the-art in
physical-layer security, which is an emerging technique of securing the open
communications environment against eavesdropping attacks at the physical layer.
We also introduce the family of various jamming attacks and their
counter-measures, including the constant jammer, intermittent jammer, reactive
jammer, adaptive jammer and intelligent jammer. Additionally, we discuss the
integration of physical-layer security into existing authentication and
cryptography mechanisms for further securing wireless networks. Finally, some
technical challenges which remain unresolved at the time of writing are
summarized and the future trends in wireless security are discussed.Comment: 36 pages. Accepted to Appear in Proceedings of the IEEE, 201
Context Aware Computing for The Internet of Things: A Survey
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
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