Advances in cryptographic voting systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 241-254).Democracy depends on the proper administration of popular elections. Voters should receive assurance that their intent was correctly captured and that all eligible votes were correctly tallied. The election system as a whole should ensure that voter coercion is unlikely, even when voters are willing to be influenced. These conflicting requirements present a significant challenge: how can voters receive enough assurance to trust the election result, but not so much that they can prove to a potential coercer how they voted? This dissertation explores cryptographic techniques for implementing verifiable, secret-ballot elections. We present the power of cryptographic voting, in particular its ability to successfully achieve both verifiability and ballot secrecy, a combination that cannot be achieved by other means. We review a large portion of the literature on cryptographic voting. We propose three novel technical ideas: 1. a simple and inexpensive paper-base cryptographic voting system with some interesting advantages over existing techniques, 2. a theoretical model of incoercibility for human voters with their inherent limited computational ability, and a new ballot casting system that fits the new definition, and 3. a new theoretical construct for shuffling encrypted votes in full view of public observers.by Ben Adida.Ph.D

FedComm: Federated Learning as a Medium for Covert Communication

Proposed as a solution to mitigate the privacy implications related to the adoption of deep learning, Federated Learning (FL) enables large numbers of participants to successfully train deep neural networks without having to reveal the actual private training data. To date, a substantial amount of research has investigated the security and privacy properties of FL, resulting in a plethora of innovative attack and defense strategies. This paper thoroughly investigates the communication capabilities of an FL scheme. In particular, we show that a party involved in the FL learning process can use FL as a covert communication medium to send an arbitrary message. We introduce FedComm, a novel multi-system covert-communication technique that enables robust sharing and transfer of targeted payloads within the FL framework. Our extensive theoretical and empirical evaluations show that FedComm provides a stealthy communication channel, with minimal disruptions to the training process. Our experiments show that FedComm successfully delivers 100% of a payload in the order of kilobits before the FL procedure converges. Our evaluation also shows that FedComm is independent of the application domain and the neural network architecture used by the underlying FL scheme.Comment: 18 page

Electronic Voting: 6th International Joint Conference, E-Vote-ID 2021, Virtual Event, October 5–8, 2021: proceedings

This volume contains the papers presented at E-Vote-ID 2021, the Sixth International Joint Conference on Electronic Voting, held during October 5–8, 2021. Due to the extraordinary situation brought about by the COVID-19, the conference was held online for the second consecutive edition, instead of in the traditional venue in Bregenz, Austria. The E-Vote-ID conference is the result of the merger of the EVOTE and Vote-ID conferences, with first EVOTE conference taking place 17 years ago in Austria. Since that conference in 2004, over 1000 experts have attended the venue, including scholars, practitioners, authorities, electoral managers, vendors, and PhD students. The conference focuses on the most relevant debates on the development of electronic voting, from aspects relating to security and usability through to practical experiences and applications of voting systems, also including legal, social, or political aspects, amongst others, and has turned out to be an important global referent in relation to this issue

Sixth International Joint Conference on Electronic Voting E-Vote-ID 2021. 5-8 October 2021

This volume contains papers presented at E-Vote-ID 2021, the Sixth International Joint Conference on Electronic Voting, held during October 5-8, 2021. Due to the extraordinary situation provoked by Covid-19 Pandemic, the conference is held online for second consecutive edition, instead of in the traditional venue in Bregenz, Austria. E-Vote-ID Conference resulted from the merging of EVOTE and Vote-ID and counting up to 17 years since the _rst E-Vote conference in Austria. Since that conference in 2004, over 1000 experts have attended the venue, including scholars, practitioners, authorities, electoral managers, vendors, and PhD Students. The conference collected the most relevant debates on the development of Electronic Voting, from aspects relating to security and usability through to practical experiences and applications of voting systems, also including legal, social or political aspects, amongst others; turning out to be an important global referent in relation to this issue. Also, this year, the conference consisted of: · Security, Usability and Technical Issues Track · Administrative, Legal, Political and Social Issues Track · Election and Practical Experiences Track · PhD Colloquium, Poster and Demo Session on the day before the conference E-VOTE-ID 2021 received 49 submissions, being, each of them, reviewed by 3 to 5 program committee members, using a double blind review process. As a result, 27 papers were accepted for its presentation in the conference. The selected papers cover a wide range of topics connected with electronic voting, including experiences and revisions of the real uses of E-voting systems and corresponding processes in elections. We would also like to thank the German Informatics Society (Gesellschaft für Informatik) with its ECOM working group and KASTEL for their partnership over many years. Further we would like to thank the Swiss Federal Chancellery and the Regional Government of Vorarlberg for their kind support. EVote- ID 2021 conference is kindly supported through European Union's Horizon 2020 projects ECEPS (grant agreement 857622) and mGov4EU (grant agreement 959072). Special thanks go to the members of the international program committee for their hard work in reviewing, discussing, and shepherding papers. They ensured the high quality of these proceedings with their knowledge and experience

Cryptographic Protocols for Privacy Enhancing Technologies: From Privacy Preserving Human Attestation to Internet Voting

Desire of privacy is oftentimes associated with the intention to hide certain aspects of our thoughts or actions due to some illicit activity. This is a narrow understanding of privacy, and a marginal fragment of the motivations for undertaking an action with a desired level of privacy. The right for not being subject to arbitrary interference of our privacy is part of the universal declaration of human rights (Article 12) and, above that, a requisite for our freedom. Developing as a person freely, which results in the development of society, requires actions to be done without a watchful eye. While the awareness of privacy in the context of modern technologies is not widely spread, it is clearly understood, as can be seen in the context of elections, that in order to make a free choice one needs to maintain its privacy. So why demand privacy when electing our government, but not when selecting our daily interests, books we read, sites we browse, or persons we encounter? It is popular belief that the data that we expose of ourselves would not be exploited if one is a law-abiding citizen. No further from the truth, as this data is used daily for commercial purposes: users’ data has value. To make matters worse, data has also been used for political purposes without the user’s consent or knowledge. However, the benefits that data can bring to individuals seem endless and a solution of not using this data at all seems extremist. Legislative efforts have tried, in the past years, to provide mechanisms for users to decide what is done with their data and define a framework where companies can use user data, but always under the consent of the latter. However, these attempts take time to take track, and have unfortunately not been very successful since their introduction. In this thesis we explore the possibility of constructing cryptographic protocols to provide a technical, rather than legislative, solution to the privacy problem. In particular we focus on two aspects of society: browsing and internet voting. These two events shape our lives in one way or another, and require high levels of privacy to provide a safe environment for humans to act upon them freely. However, these two problems have opposite solutions. On the one hand, elections are a well established event in society that has been around for millennia, and privacy and accountability are well rooted requirements for such events. This might be the reason why its digitalisation is something which is falling behind with respect to other acts of our society (banking, shopping, reading, etc). On the other hand, browsing is a recently introduced action, but that has quickly taken track given the amount of possibilities that it opens with such ease. We now have access to whatever we can imagine (except for voting) at the distance of a click. However, the data that we generate while browsing is extremely sensitive, and most of it is disclosed to third parties under the claims of making the user experience better (targeted recommendations, ads or bot-detection). Chapter 1 motivates why resolving such a problem is necessary for the progress of digital society. It then introduces the problem that this thesis aims to resolve, together with the methodology. In Chapter 2 we introduce some technical concepts used throughout the thesis. Similarly, we expose the state-of-the-art and its limitations. In Chapter 3 we focus on a mechanism to provide private browsing. In particular, we focus on how we can provide a safer, and more private way, for human attestation. Determining whether a user is a human or a bot is important for the survival of an online world. However, the existing mechanisms are either invasive or pose a burden to the user. We present a solution that is based on a machine learning model to distinguish between humans and bots that uses natural events of normal browsing (such as touch the screen of a phone) to make its prediction. To ensure that no private data leaves the user’s device, we evaluate such a model in the device rather than sending the data over the wire. To provide insurance that the expected model has been evaluated, the user’s device generates a cryptographic proof. However this opens an important question. Can we achieve a high level of accuracy without resulting in a noneffective battery consumption? We provide a positive answer to this question in this work, and show that a privacy-preserving solution can be achieved while maintaining the accuracy high and the user’s performance overhead low. In Chapter 4 we focus on the problem of internet voting. Internet voting means voting remotely, and therefore in an uncontrolled environment. This means that anyone can be voting under the supervision of a coercer, which makes the main goal of the protocols presented to be that of coercionresistance. We need to build a protocol that allows a voter to escape the act of coercion. We present two proposals with the main goal of providing a usable, and scalable coercion resistant protocol. They both have different trade-offs. On the one hand we provide a coercion resistance mechanism that results in linear filtering, but that provides a slightly weaker notion of coercion-resistance. Secondly, we present a mechanism with a slightly higher complexity (poly-logarithmic) but that instead provides a stronger notion of coercion resistance. Both solutions are based on a same idea: allowing the voter to cast several votes (such that only the last one is counted) in a way that cannot be determined by a coercer. Finally, in Chapter 5, we conclude the thesis, and expose how our results push one step further the state-of-the-art. We concisely expose our contributions, and describe clearly what are the next steps to follow. The results presented in this work argue against the two main claims against privacy preserving solutions: either that privacy is not practical or that higher levels of privacy result in lower levels of security.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: Agustín Martín Muñoz.- Secretario: José María de Fuentes García-Romero de Tejada.- Vocal: Alberto Peinado Domíngue

Advances in the Convergence of Blockchain and Artificial Intelligence

Blockchain (BC) and artificial intelligence (AI) are currently two of the hottest computer science topics and their future seems bright. However, their convergence is not straightforward, and more research is needed in both fields. Thus, this book presents some of the latest advances in the convergence of BC and AI, gives useful guidelines for future researchers on how BC can help AI and how AI can become smarter, thanks to the use of BC. This book specifically analyzes the past of BC through the history of Bitcoin and then looks into the future: from massive internet-of-things (IoT) deployments, to the so-called metaverse, and to the next generation of AI-powered BC-based cyber secured applications

Privacy Enhancing Technologies for solving the privacy-personalization paradox : taxonomy and survey

Personal data are often collected and processed in a decentralized fashion, within different contexts. For instance, with the emergence of distributed applications, several providers are usually correlating their records, and providing personalized services to their clients. Collected data include geographical and indoor positions of users, their movement patterns as well as sensor-acquired data that may reveal users’ physical conditions, habits and interests. Consequently, this may lead to undesired consequences such as unsolicited advertisement and even to discrimination and stalking. To mitigate privacy threats, several techniques emerged, referred to as Privacy Enhancing Technologies, PETs for short. On one hand, the increasing pressure on service providers to protect users’ privacy resulted in PETs being adopted. One the other hand, service providers have built their business model on personalized services, e.g. targeted ads and news. The objective of the paper is then to identify which of the PETs have the potential to satisfy both usually divergent - economical and ethical - purposes. This paper identifies a taxonomy classifying eight categories of PETs into three groups, and for better clarity, it considers three categories of personalized services. After defining and presenting the main features of PETs with illustrative examples, the paper points out which PETs best fit each personalized service category. Then, it discusses some of the inter-disciplinary privacy challenges that may slow down the adoption of these techniques, namely: technical, social, legal and economic concerns. Finally, it provides recommendations and highlights several research directions

Electronic voting : 6th International Joint Conference, E-Vote-ID 2021, virtual event, October 5-8, 2021

This book constitutes the proceedings of the 6th International Conference on Electronic Voting, E-Vote-ID 2021, held online -due to COVID -19- in Bregenz, Austria, in October 2021. The 14 full papers presented were carefully reviewed and selected from 55 submissions. The conference collected the most relevant debates on the development of Electronic Voting, from aspects relating to security and usability through to practical experiences and applications of voting systems, as well as legal, social or political aspects

AUC: Accountable Universal Composability

Accountability is a well-established and widely used security concept that allows for obtaining undeniable cryptographic proof of misbehavior, thereby incentivizing honest behavior. There already exist several general purpose accountability frameworks for formal game-based security analyses. Unfortunately, such game-based frameworks do not support modular security analyses, which is an important tool to handle the complexity of modern protocols. Universal composability (UC) models provide native support for modular analyses, including re-use and composition of security results. So far, accountability has mainly been modeled and analyzed in UC models for the special case of MPC protocols, with a general purpose accountability framework for UC still missing. That is, a framework that among others supports arbitrary protocols, a wide range of accountability properties, handling and mixing of accountable and non-accountable security properties, and modular analysis of accountable protocols. To close this gap, we propose AUC, the first general purpose accountability framework for UC models, which supports all of the above, based on several new concepts. We exemplify AUC in three case studies not covered by existing works. In particular, AUC unifies existing UC accountability approaches within a single framework