P6V2G: A Privacy-Preserving V2G Scheme for Two-Way Payments and Reputation

The number of electric vehicles (EVs) is steadily growing. This provides a promising opportunity for balancing the smart grid of the future, because vehicle-to-grid (V2G) systems can utilize the batteries of plugged-in EVs as much needed distributed energy storage: In times of high production and low demand the excess energy in the grid is stored in the EVs’ batteries, while peaks in demand are mitigated by EVs feeding electricity back to the grid. But the data needed for managing individual V2G charging sessions as well as for billing and rewards is of a highly personal and therefore sensitive nature. This causes V2G systems to pose a significant threat to the privacy of their users. Existing cryptographic protocols for this scenario either do not offer adequate privacy protection or fail to provide key features necessary to obtain a practical system. Based on the recent cryptographic toll collection framework P4TC, this work introduces a privacy-preserving but efficient V2G payment and reward system called P6V2G. Our system facilitates two-way transactions in a semi online and post-payment setting. It provides double-spending detection, an integrated reputation system, contingency traceability and blacklisting features, and is portable between EVs. The aforementioned properties are holistically captured within an established cryptographic security framework. In contrast to existing protocols, this formal model of a V2G payment and reward system allows us to assert all properties through a comprehensive formal proof

Authentication Protocols for Internet of Things: A Comprehensive Survey

In this paper, a comprehensive survey of authentication protocols for Internet of Things (IoT) is presented. Specifically more than forty authentication protocols developed for or applied in the context of the IoT are selected and examined in detail. These protocols are categorized based on the target environment: (1) Machine to Machine Communications (M2M), (2) Internet of Vehicles (IoV), (3) Internet of Energy (IoE), and (4) Internet of Sensors (IoS). Threat models, countermeasures, and formal security verification techniques used in authentication protocols for the IoT are presented. In addition a taxonomy and comparison of authentication protocols that are developed for the IoT in terms of network model, specific security goals, main processes, computation complexity, and communication overhead are provided. Based on the current survey, open issues are identified and future research directions are proposed

Application of distributed ledger technology in distribution networks

In the transition to a society with net-zero carbon emissions, high penetration of distributed renewable power generation and large-scale electrification of transportation and heat are driving the conventional distribution network operators (DNOs) to evolve into distribution system operators (DSOs) that manage distribution networks in a more active and flexible way. As a radical decentralized data management technology, distributed ledger technology (DLT) has the potential to support a trustworthy digital infrastructure facilitating the DNO–DSO transition. Based on a comprehensive review of worldwide research and practice, as well as the engagement of relevant industrial experts, the application of DLT in distribution networks is identified and analyzed in this article. The DLT features and DSO needs are first summarized, and the mapping relationship between them is identified. Detailed DSO functions are identified and classified into five categories (i.e.“, planning”, “operation”, “market”, “asset”, and “connection”) with the potential of applying DLT to various DSO functions assessed. Finally, the development of seven key DSO functions with high DLT potential is analyzed and discussed from the technical, legal, and social perspectives, including peer-to-peer energy trading, flexibility market facilitation, electric vehicle charging, network pricing, distributed generation register, data access, and investment planning

Security and Privacy for Mobile Social Networks

With the ever-increasing demands of people's social interactions, traditional online social networking applications are being shifted to the mobile ones, enabling users' social networking and interactions anywhere anytime. Due to the portability and pervasiveness of mobile devices, such as smartphones, wearable devices and tablets, Mobile Social Network (MSN), as a promising social network platform, has become increasingly popular and brought immense benefits. In MSN, users can easily discover and chat with social friends in the vicinity even without the Internet; vehicle drivers and passengers can exchange traffic information, videos or images with other vehicles on the road; customers in a shopping mall can share sale information and recommend it to their friends. With MSNs, massive opportunities are created to facilitate people's social interactions and enlarge the inherent social circle. However, the flourish of MSNs also hinges upon fully understanding and managing the challenges, such as security threats and privacy leakage. Security and privacy concerns rise as the boom of MSN applications comes up, but few users have paid adequate attentions to protect their privacy-sensitive information from disclosing. First of all, to initiate social interactions, users sometimes exchange their social interests or preferences with each other (including strangers in the vicinity) without sufficient protections. As such, some private information may be inferred from the exchanged social interests by attackers and untrusted users. Secondly, some malicious attackers might forge fake identities or false contents, such as spam and advertisements, to disrupt MSNs or mislead other users. These attackers could even collude and launch a series of security threats to MSNs. In addition, massive social network data are usually stored in untrusted cloud servers, where data confidentiality, authentication, access control and privacy are of paramount importance. Last but not least, the trade-off between data availability and privacy should be taken into account when the data are stored, queried and processed for various MSN applications. Therefore, novel security and privacy techniques become essential for MSN to provide sufficient and adjustable protections. In this thesis, we focus on security and privacy for MSNs. Based on the MSN architecture and emerging applications, we first investigate security and privacy requirements for MSNs and introduce several challenging issues, i.e., spam, misbehaviors and privacy leakage. To tackle these problems, we propose efficient security and privacy preservation schemes for MSNs. Specifically, the main contributions of this thesis can be three-fold. Firstly, to address the issues of spam in autonomous MSNs, we propose a personalized fine-grained spam filtering scheme (PIF), which exploits social characteristics during data delivery. The PIF allows users to create personalized filters according to their social interests, and enables social friends to hold these filters, discarding the unwanted data before delivery. We also design privacy-preserving coarse-grained and fine-grained filtering mechanisms in the PIF to not only enable the filtering but also prevent users' private information included in the filters from disclosing to untrusted entities. Secondly, to detect misbehaviors during MSN data sharing, we propose a social-based mobile Sybil detection scheme (SMSD). The SMSD detects Sybil attackers by differentiating the abnormal pseudonym changing and contact behaviors, since Sybil attackers frequently or rapidly change their pseudonyms to cheat legitimate users. As the volume of contact data from users keeps increasing, the SMSD utilizes local cloud servers to store and process the users' contact data such that the burden of mobile users is alleviated. The SMSD also detects the collusion attacks and prevents user's data from malicious modification when employing the untrusted local cloud server for the detection. Thirdly, to achieve the trade-off between privacy and data availability, we investigate a centralized social network application, which exploits social network to enhance human-to-human infection analysis. We integrate social network data and health data to jointly analyze the instantaneous infectivity during human-to-human contact, and propose a novel privacy-preserving infection analysis approach (PIA). The PIA enables the collaboration among different cloud servers (i.e., social network cloud server and health cloud server). It employs a privacy-preserving data query method based on conditional oblivious transfer to enable data sharing and prevent data from disclosing to untrusted entities. A privacy-preserving classification-based infection analysis method is also proposed to enable the health cloud server to infer infection spread but preserve privacy simultaneously. Finally, we summarize the thesis and share several open research directions in MSNs. The developed security solutions and research results in this thesis should provide a useful step towards better understanding and implementing secure and privacy-preserving MSNs

Local Market Mechanisms: how Local Markets can shape the Energy Transition

Europe has embarked on a journey towards a zero-emission system, with the power system at its core. From electricity generation to electric vehicles, the European power system must transform into an interconnected, intelligent network. To achieve this vision, active user participation is crucial, ensuring transparency, efficiency, and inclusivity. Thus, Europe has increasingly focused on the concept of markets in all their facets. This thesis seeks to answer the following questions: How can markets, often considered abstract and accessible only to high-level users, be integrated for end-users? How can market mechanisms be leveraged across various phases of the electrical system? Why is a market- driven approach essential for solving network congestions and even influencing planning? These questions shape the core of this research. The analysis unfolds in three layers, each aligned with milestones leading to 2050. The first explores how market mechanisms can be integrated into system operator development plans, enhancing system resilience in the face of changes. In this regard, this step addresses the question of how a market can be integrated into the development plans of a network and how network planning can account for uncertainties. Finally, the analysis highlights the importance of sector coupling in network planning, proposing a study in which various energy vectors lead to a multi-energy system. According to the roadmap to 2030, this layer demonstrates how markets can manage several components of the gas and electrical network. Finally, even though the robust optimisation increases the final cost in the market, it allows to cover the system operator from uncertainties. The second step delves into the concept of network congestion. While congestion management is primarily the domain of operators, it explores how technical and economic collaboration between operators and system users, via flexibility markets, can enhance resilience amid demand uncertainties and aggressive market behaviours. In addition to flexibility markets, other congestion markets are proposed, some radically different, like locational marginal pricing, and others more innovative, such as redispatching markets for distribution. Building upon the first analysis, this section addresses questions of how various energy vectors can be used not only to meet demand but also to manage the uncertainties associated with each resource. Consequently, this second part revisits the concept of sector coupling, demonstrating how various energy vectors can be managed through flexibility markets to resolve network congestion while simultaneously handling uncertainties related to different vectors. The results demonstrate the usefulness of the flexibility market in managing the sector coupling and the uncertainties related to several energy vectors. The third and most innovative step proposes energy and service markets for low-voltage users, employing distributed ledger technology. Since this step highlights topics that are currently too innovative to be realized, this third section offers a comparative study between centralised and decentralised markets using blockchain technology, highlighting which aspects of distributed ledger technology deserve attention and which aspects of low-voltage markets need revision. The results show that the blockchain technology is still in the early stage of its evolution, and several improvements are needed to fully apply this technology into real-world applications. To sum up, this thesis explores the evolving role of markets in the energy transition. Its insights are aimed at assisting system operators and network planners in effectively integrating market mechanisms at all levels of