Distributed Key Generation and Its Applications

Numerous cryptographic applications require a trusted authority to hold a secret. With a plethora of malicious attacks over the Internet, however, it is difficult to establish and maintain such an authority in online systems. Secret-sharing schemes attempt to solve this problem by distributing the required trust to hold and use the secret over multiple servers; however, they still require a trusted {\em dealer} to choose and share the secret, and have problems related to single points of failure and key escrow. A distributed key generation (DKG) scheme overcomes these hurdles by removing the requirement of a dealer in secret sharing. A (threshold) DKG scheme achieves this using a complete distribution of the trust among a number of servers such that any subset of servers of size greater than a given threshold can reveal or use the shared secret, while any smaller subset cannot. In this thesis, we make contributions to DKG in the computational security setting and describe three applications of it. We first define a constant-size commitment scheme for univariate polynomials over finite fields and use it to reduce the size of broadcasts required for DKG protocols in the synchronous communication model by a linear factor. Further, we observe that the existing (synchronous) DKG protocols do not provide a liveness guarantee over the Internet and design the first DKG protocol for use over the Internet. Observing the necessity of long-term stability, we then present proactive security and group modification protocols for our DKG system. We also demonstrate the practicality of our DKG protocol over the Internet by testing our implementation over PlanetLab. For the applications, we use our DKG protocol to define IND-ID-CCA secure distributed private-key generators (PKGs) for three important identity-based encryption (IBE) schemes: Boneh and Franklin's BF-IBE, Sakai and Kasahara's SK-IBE, and Boneh and Boyen's BB1-IBE. These IBE schemes cover all three important IBE frameworks: full-domain-hash IBEs, exponent-inversion IBEs and commutative-blinding IBEs respectively, and our distributed PKG constructions can easily be modified for other IBE schemes in these frameworks. As the second application, we use our distributed PKG for BF-IBE to define an onion routing circuit construction mechanism in the identity-based setting, which solves the scalability problem in single-pass onion routing circuit construction without hampering forward secrecy. As the final application, we use our DKG implementation to design a threshold signature architecture for quorum-based distributed hash tables and use it to define two robust communication protocols in these peer-to-peer systems

Energy Storage Systems for Energy Management of Renewables in Distributed Generation Systems

Distributed generation (DG) systems are the key for implementation of micro/smart grids of today, and energy storages are becoming an integral part of such systems. Advancement in technology now ensures power storage and delivery from few seconds to days/months. But an effective management of the distributed energy resources and its storage systems is essential to ensure efficient operation and long service life. This chapter presents the issues faced in integrating renewables in DG and the growing necessity of energy storages. Types of energy storage systems (ESSs) and their applications have also been detailed. A brief literature study on energy management of ESSs in distributed microgrids has also been included. This is followed by a simple case study to illustrate the need and effect of management of ESSs in distributed systems

Deterministic Generation of Multipartite Entanglement via Causal Activation in the Quantum Internet

Entanglement represents ``\textit{the}'' key resource for several applications of quantum information processing, ranging from quantum communications to distributed quantum computing. Despite its fundamental importance, deterministic generation of maximally entangled qubits represents an on-going open problem. Here, we design a novel generation scheme exhibiting two attractive features, namely, i) deterministically generating different classes -- namely, GHZ-like, W-like and graph states -- of genuinely multipartite entangled states, ii) without requiring any direct interaction between the qubits. Indeed, the only necessary condition is the possibility of coherently controlling -- according to the indefinite causal order framework -- the causal order among the unitaries acting on the qubits. Through the paper, we analyze and derive the conditions on the unitaries for deterministic generation, and we provide examples for unitaries practical implementation. We conclude the paper by discussing the scalability of the proposed scheme to higher dimensional genuine multipartite entanglement (GME) states and by introducing some possible applications of the proposal for quantum networks

Who is to Blame? Runtime Verification of Distributed Objects with Active Monitors

In Proceedings VORTEX 2018, arXiv:1908.09302International audienceSince distributed software systems are ubiquitous, their correct functioning is crucially important. Static verification is possible in principle, but requires high expertise and effort which is not feasible in many eco-systems. Runtime verification can serve as a lean alternative, where monitoring mechanisms are automatically generated from property specifications, to check compliance at runtime. This paper contributes a practical solution for powerful and flexible runtime verification of distributed, object-oriented applications, via a combination of the runtime verification tool Larva and the active object framework ProActive. Even if Larva supports in itself only the generation of local, sequential monitors, we empower Larva for distributed monitoring by connecting monitors with active objects, turning them into active, communicating monitors. We discuss how this allows for a variety of monitoring architectures. Further, we show how property specifications, and thereby the generated monitors, provide a model that splits the blame between the local object and its environment. While Larva itself focuses on monitoring of control-oriented properties, we use the Larva front-end StaRVOOrS to also capture data-oriented (pre/post) properties in the distributed monitoring. We demonstrate this approach to distributed runtime verification with a case study, a distributed key/value store

On the Coexistence of Aperiodic and Periodic Traffic in Cellular Vehicle-to-Everything

Cellular Vehicle-to-Everything (C-V2X) communications are the key to connected and autonomous driving, and pave the way for future Intelligent Transport Systems (ITS). To support non-safety and safety critical applications in the demanding out-of-coverage scenario, the 3rd Generation Partnership Project (3GPP) has standardized the distributed C-V2X Mode 4 solution, whose behavior has been thoroughly analyzed for periodic traffic. In the current work, the problem of allocating aperiodic traffic in Mode 4 is tackled, a matter that has not been addressed before and that raises several challenging questions. A solution for serving such traffic type is put forth, and an analytical insight on the attainable performance is offered. Further, it is numerically proved that guaranteeing aperiodic flows good service levels is hard when their packets are not small sized. This holds true even for sophisticated physical layer choices and at relatively modest traffic densities, revealing that novel approaches to radio resource assignment are a necessity in Fifth Generation (5G) vehicular communications

Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses

The ongoing deployment of the fifth generation (5G) wireless networks constantly reveals limitations concerning its original concept as a key driver of Internet of Everything (IoE) applications. These 5G challenges are behind worldwide efforts to enable future networks, such as sixth generation (6G) networks, to efficiently support sophisticated applications ranging from autonomous driving capabilities to the Metaverse. Edge learning is a new and powerful approach to training models across distributed clients while protecting the privacy of their data. This approach is expected to be embedded within future network infrastructures, including 6G, to solve challenging problems such as resource management and behavior prediction. This survey article provides a holistic review of the most recent research focused on edge learning vulnerabilities and defenses for 6G-enabled IoT. We summarize the existing surveys on machine learning for 6G IoT security and machine learning-associated threats in three different learning modes: centralized, federated, and distributed. Then, we provide an overview of enabling emerging technologies for 6G IoT intelligence. Moreover, we provide a holistic survey of existing research on attacks against machine learning and classify threat models into eight categories, including backdoor attacks, adversarial examples, combined attacks, poisoning attacks, Sybil attacks, byzantine attacks, inference attacks, and dropping attacks. In addition, we provide a comprehensive and detailed taxonomy and a side-by-side comparison of the state-of-the-art defense methods against edge learning vulnerabilities. Finally, as new attacks and defense technologies are realized, new research and future overall prospects for 6G-enabled IoT are discussed

A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks

The fifth generation (5G) mobile networks are envisaged to enable a plethora of breakthrough advancements in wireless technologies, providing support of a diverse set of services over a single platform. While the deployment of 5G systems is scaling up globally, it is time to look ahead for beyond 5G systems. This is driven by the emerging societal trends, calling for fully automated systems and intelligent services supported by extended reality and haptics communications. To accommodate the stringent requirements of their prospective applications, which are data-driven and defined by extremely low-latency, ultra-reliable, fast and seamless wireless connectivity, research initiatives are currently focusing on a progressive roadmap towards the sixth generation (6G) networks. In this article, we shed light on some of the major enabling technologies for 6G, which are expected to revolutionize the fundamental architectures of cellular networks and provide multiple homogeneous artificial intelligence-empowered services, including distributed communications, control, computing, sensing, and energy, from its core to its end nodes. Particularly, this paper aims to answer several 6G framework related questions: What are the driving forces for the development of 6G? How will the enabling technologies of 6G differ from those in 5G? What kind of applications and interactions will they support which would not be supported by 5G? We address these questions by presenting a profound study of the 6G vision and outlining five of its disruptive technologies, i.e., terahertz communications, programmable metasurfaces, drone-based communications, backscatter communications and tactile internet, as well as their potential applications. Then, by leveraging the state-of-the-art literature surveyed for each technology, we discuss their requirements, key challenges, and open research problems

An interdisciplinary review of energy storage for communities: challenges and perspectives

Given the increasing penetration of renewable energy technologies as distributed generation embedded in the consumption centres, there is growing interest in energy storage systems located very close to consumers. These systems allow to increase the amount of renewable energy generation consumed locally, they provide opportunities for demand-side management and help to decarbonise the electricity, heating and transport sectors. In this paper, the authors present an interdisciplinary review of community energy storage (CES) with a focus on its potential role and challenges as a key element within the wider energy system. The discussion includes: the whole spectrum of applications and technologies with a strong emphasis on end user applications; techno-economic, environmental and social assessments of CES; and an outlook on CES from the customer, utility company and policy-maker perspectives. Currently, in general only traditional thermal storage with water tanks is economically viable. However, CES is expected to offer new opportunities for the energy transition since the community scale introduces several advantages for electrochemical technologies such as batteries. Technical and economic benefits over energy storage in single dwellings are driven by enhanced performance due to less spiky community demand profile and economies of scale respectively. In addition, CES brings new opportunities for citizen participation within communities and helps to increase awareness of energy consumption and environmental impacts