Secure Authentication and Privacy-Preserving Techniques in Vehicular Ad-hoc NETworks (VANETs)

In the last decade, there has been growing interest in Vehicular Ad Hoc NETworks (VANETs). Today car manufacturers have already started to equip vehicles with sophisticated sensors that can provide many assistive features such as front collision avoidance, automatic lane tracking, partial autonomous driving, suggestive lane changing, and so on. Such technological advancements are enabling the adoption of VANETs not only to provide safer and more comfortable driving experience but also provide many other useful services to the driver as well as passengers of a vehicle. However, privacy, authentication and secure message dissemination are some of the main issues that need to be thoroughly addressed and solved for the widespread adoption/deployment of VANETs. Given the importance of these issues, researchers have spent a lot of effort in these areas over the last decade. We present an overview of the following issues that arise in VANETs: privacy, authentication, and secure message dissemination. Then we present a comprehensive review of various solutions proposed in the last 10 years which address these issues. Our survey sheds light on some open issues that need to be addressed in the future

Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Cloud Computing in VANETs (CC-V) has been investigated into two major themes of research including Vehicular Cloud Computing (VCC) and Vehicle using Cloud (VuC). VCC is the realization of autonomous cloud among vehicles to share their abundant resources. VuC is the efficient usage of conventional cloud by on-road vehicles via a reliable Internet connection. Recently, number of advancements have been made to address the issues and challenges in VCC and VuC. This paper qualitatively reviews CC-V with the emphasis on layered architecture, network component, taxonomy, and future challenges. Specifically, a four-layered architecture for CC-V is proposed including perception, co-ordination, artificial intelligence and smart application layers. Three network component of CC-V namely, vehicle, connection and computation are explored with their cooperative roles. A taxonomy for CC-V is presented considering major themes of research in the area including design of architecture, data dissemination, security, and applications. Related literature on each theme are critically investigated with comparative assessment of recent advances. Finally, some open research challenges are identified as future issues. The challenges are the outcome of the critical and qualitative assessment of literature on CC-V

Game Theory Based Privacy Protection for Context-Aware Services

In the era of context-aware services, users are enjoying remarkable services based on data collected from a multitude of users. To receive services, they are at risk of leaking private information from adversaries possibly eavesdropping on the data and/or the un--trusted service platform selling off its data. Malicious adversaries may use leaked information to violate users\u27 privacy in unpredictable ways. To protect users\u27 privacy, many algorithms are proposed to protect users\u27 sensitive information by adding noise, thus causing context-aware service quality loss. Game theory has been utilized as a powerful tool to balance the tradeoff between privacy protection level and service quality. However, most of the existing schemes fail to depict the mutual relationship between any two parties involved: user, platform, and adversary. There is also an oversight to formulate the interaction occurring between multiple users, as well as the interaction between any two attributes. To solve these issues, this dissertation firstly proposes a three-party game framework to formulate the mutual interaction between three parties and study the optimal privacy protection level for context-aware services, thus optimize the service quality. Next, this dissertation extends the framework to a multi-user scenario and proposes a two-layer three-party game framework. This makes the proposed framework more realistic by further exploring the interaction, not only between different parties, but also between users. Finally, we focus on analyzing the impact of long-term time-serial data and the active actions of the platform and adversary. To achieve this objective, we design a three-party Stackelberg game model to help the user to decide whether to update information and the granularity of updated information

Tactful Networking: Humans in the Communication Loop

International audienceThis survey discusses the human-perspective into networking through the Tactful Networking paradigm, whose goal is to add perceptive senses to the network by assigning it with human-like capabilities of observation, interpretation, and reaction to daily-life features and associated entities. To achieve this, knowledge extracted from inherent human behavior in terms of routines, personality, interactions, and others is leveraged, empowering the learning and prediction of user needs to improve QoE and system performance while respecting privacy and fostering new applications and services. Tactful Networking groups solutions from literature and innovative interdisciplinary human aspects studied in other areas. The paradigm is motivated by mobile devices' pervasiveness and increasing presence as a sensor in our daily social activities. With the human element in the foreground, it is essential: (i) to center big data analytics around individuals; (ii) to create suitable incentive mechanisms for user participation; (iii) to design and evaluate both humanaware and system-aware networking solutions; and (iv) to apply prior and innovative techniques to deal with human-behavior sensing and learning. This survey reviews the human aspect in networking solutions through over a decade, followed by discussing the tactful networking impact through literature in behavior analysis and representative examples. This paper also discusses a framework comprising data management, analytics, and privacy for enhancing human raw-data to assist Tactful Networking solutions. Finally, challenges and opportunities for future research are presented

Security and Privacy Preservation in Mobile Advertising

Mobile advertising is emerging as a promising advertising strategy, which leverages prescriptive analytics, location-based distribution, and feedback-driven marketing to engage consumers with timely and targeted advertisements. In the current mobile advertising system, a third-party ad broker collects and manages advertisements for merchants who would like to promote their business to mobile users. Based on its large-scale database of user profiles, the ad broker can help the merchants to better reach out to customers with related interests and charges the merchants for ad dissemination services. Recently, mobile advertising technology has dominated the digital advertising industry and has become the main source of income for IT giants. However, there are many security and privacy challenges that may hinder the continuous success of the mobile advertising industry. First, there is a lack of advertising transparency in the current mobile advertising system. For example, mobile users are concerned about the reliability and trustworthiness of the ad dissemination process and advertising review system. Without proper countermeasures, mobile users can install ad-blocking software to filter out irrelevant or even misleading advertisements, which may lower the advertising investments from merchants. Second, as more strict privacy regulations (e.g. European General Data Privacy Regulations) take effect, it is critical to protect mobile users’ personal profiles from illegal sharing and exposure in the mobile advertising system. In this thesis, three security and privacy challenges for the mobile advertising system are identified and addressed with the designs, implementations, and evaluations of a blockchain-based architecture. First, we study the anonymous review system for the mobile advertising industry. When receiving advertisements from a specific merchant (e.g. a nearby restaurant), mobile users are more likely to browse the previous reviews about the merchant for quality-of-service assessments. However, current review systems are known for the lack of system transparency and are subject to many attacks, such as double reviews and deletions of negative reviews. We exploit the tamper-proof nature and the distributed consensus mechanism of the blockchain technology, to design a blockchain-based review system for mobile advertising, where review accumulations are transparent and verifiable to the public. To preserve user review privacy, we further design an anonymous review token generation scheme, where users are encouraged to leave reviews anonymously while still ensuring the review authenticity. We also explore the implementation challenges of the blockchain-based system on an Ethereum testing network and the experimental results demonstrate the application feasibility of the proposed anonymous review system. Second, we investigate the transparency issues for the targeted ad dissemination process. Specifically, we focus on a specific mobile advertising application: vehicular local advertising, where vehicular users send spatial-keyword queries to ad brokers to receive location-aware advertisements. To build a transparent advertising system, the ad brokers are required to provide mobile users with explanations on the ad dissemination process, e.g., why a specific ad is disseminated to a mobile user. However, such transparency explanations are often found incomplete and sometimes even misleading, which may lower the user trust on the advertising system if without proper countermeasures. Therefore, we design an advertising smart contract to efficiently realize a publicly verifiable spatial-keyword query scheme. Instead of directly implementing the spatial-keyword query scheme on the smart contract with prohibitive storage and computation cost, we exploit the on/off-chain computation models to trade the expensive on-chain cost for cheap off-chain cost. With two design strategies: digest-and-verify and divide-then-assemble, the on-chain cost for a single spatial keyword query is reduced to constant regardless of the scale of the spatial-keyword database. Extensive experiments are conducted to provide both on-chain and off-chain benchmarks with a verifiable computation framework. Third, we explore another critical requirement of the mobile advertising system: public accountability enforcement against advertising misconducts, if (1) mobile users receive irrelevant ads, or (2) advertising policies of merchants are not correctly computed in the ad dissemination process. This requires the design of a composite Succinct Non-interactive ARGument (SNARG) system, that can be tailored for different advertising transparency requirements and is efficient for the blockchain implementations. Moreover, pursuing public accountability should also achieve a strict privacy guarantee for the user profile. We also propose an accountability contract which can receive explanation requirements from both mobile users and merchants. To promote prompt on-chain responses, we design an incentive mechanism based on the pre-deposits of involved parties, i.e., ad brokers, mobile users, and merchants. If any advertising misconduct is identified, public accountability can be enforced by confiscating the pre-deposits of the misbehaving party. Comprehensive experiments and analyses are conducted to demonstrate the versatile functionalities and feasibility of the accountability contract. In summary, we have designed, implemented, and evaluated a blockchain-based architecture for security and privacy preservations in the mobile advertising. The designed architecture can not only enhance the transparency and accountability for the mobile advertising system, but has also achieved notably on-chain efficiency and privacy for real-world implementations. The results from the thesis may shed light on the future research and practice of a blockchain-based architecture for the privacy regulation compliance in the mobile advertising

Obfuscation and anonymization methods for locational privacy protection : a systematic literature review

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesThe mobile technology development combined with the business model of a majority of application companies is posing a potential risk to individuals’ privacy. Because the industry default practice is unrestricted data collection. Although, the data collection has virtuous usage in improve services and procedures; it also undermines user’s privacy. For that reason is crucial to learn what is the privacy protection mechanism state-of-art. Privacy protection can be pursued by passing new regulation and developing preserving mechanism. Understanding in what extent the current technology is capable to protect devices or systems is important to drive the advancements in the privacy preserving field, addressing the limits and challenges to deploy mechanism with a reasonable quality of Service-QoS level. This research aims to display and discuss the current privacy preserving schemes, its capabilities, limitations and challenges

Integration of Blockchain and Auction Models: A Survey, Some Applications, and Challenges

In recent years, blockchain has gained widespread attention as an emerging technology for decentralization, transparency, and immutability in advancing online activities over public networks. As an essential market process, auctions have been well studied and applied in many business fields due to their efficiency and contributions to fair trade. Complementary features between blockchain and auction models trigger a great potential for research and innovation. On the one hand, the decentralized nature of blockchain can provide a trustworthy, secure, and cost-effective mechanism to manage the auction process; on the other hand, auction models can be utilized to design incentive and consensus protocols in blockchain architectures. These opportunities have attracted enormous research and innovation activities in both academia and industry; however, there is a lack of an in-depth review of existing solutions and achievements. In this paper, we conduct a comprehensive state-of-the-art survey of these two research topics. We review the existing solutions for integrating blockchain and auction models, with some application-oriented taxonomies generated. Additionally, we highlight some open research challenges and future directions towards integrated blockchain-auction models