Applying Block Chain Technologies to Digital Voting Algorithms

Voting is a fundamental aspect to democracy. Many countries have advanced voting systems in place, but many of these systems have issues behind them such as not being anonymous or verifiable. Additionally, most voting systems currently have a central authority in charge of counting votes, which can be prone to corruption. We propose a voting system which mitigates many of these issues. Our voting system attempts to provide decentralization, pseudoanonymity, and verifiability. For our system, we have identified the requirements, implemented the backbone of the system, recognized some of its shortcomings, and proposed areas of future work on this voting system

What proof do we prefer? Variants of verifiability in voting

In this paper, we discuss one particular feature of Internet voting, verifiability, against the background of scientific literature and experiments in the Netherlands. In order to conceptually clarify what verifiability is about, we distinguish classical verifiability from constructive veriability in both individual and universal verification. In classical individual verifiability, a proof that a vote has been counted can be given without revealing the vote. In constructive individual verifiability, a proof is only accepted if the witness (i.e. the vote) can be reconstructed. Analogous concepts are de- fined for universal veriability of the tally. The RIES system used in the Netherlands establishes constructive individual verifiability and constructive universal verifiability, whereas many advanced cryptographic systems described in the scientific literature establish classical individual verifiability and classical universal verifiability. If systems with a particular kind of verifiability continue to be used successfully in practice, this may influence the way in which people are involved in elections, and their image of democracy. Thus, the choice for a particular kind of verifiability in an experiment may have political consequences. We recommend making a well-informed democratic choice for the way in which both individual and universal verifiability should be realised in Internet voting, in order to avoid these unconscious political side-effects of the technology used. The safest choice in this respect, which maintains most properties of current elections, is classical individual verifiability combined with constructive universal verifiability. We would like to encourage discussion about the feasibility of this direction in scientific research

Robustness Verification of Support Vector Machines

We study the problem of formally verifying the robustness to adversarial examples of support vector machines (SVMs), a major machine learning model for classification and regression tasks. Following a recent stream of works on formal robustness verification of (deep) neural networks, our approach relies on a sound abstract version of a given SVM classifier to be used for checking its robustness. This methodology is parametric on a given numerical abstraction of real values and, analogously to the case of neural networks, needs neither abstract least upper bounds nor widening operators on this abstraction. The standard interval domain provides a simple instantiation of our abstraction technique, which is enhanced with the domain of reduced affine forms, which is an efficient abstraction of the zonotope abstract domain. This robustness verification technique has been fully implemented and experimentally evaluated on SVMs based on linear and nonlinear (polynomial and radial basis function) kernels, which have been trained on the popular MNIST dataset of images and on the recent and more challenging Fashion-MNIST dataset. The experimental results of our prototype SVM robustness verifier appear to be encouraging: this automated verification is fast, scalable and shows significantly high percentages of provable robustness on the test set of MNIST, in particular compared to the analogous provable robustness of neural networks

Ethics of e-voting: an essay on requirements and values in Internet elections

In this paper, we investigate ethical issues involved in the development and implementation of Internet voting technology. From a phenomenological perspective, we describe how voting via the Internet mediates the relation between people and democracy. In this relation, trust plays a major role. The dynamics of trust in the relation between people and their world forms the basis for our analysis of the ethical issues involved. First, we consider established principles of voting, confirming the identity of our democracy, which function as expectations in current experiments with online voting in the Netherlands. We investigate whether and how Internet voting can meet these expectations and thereby earn trust, based on the experiments in the Netherlands. We identify major challenges, and provide a basis for ethical and political discussion on these issues, especially the changed relation between public and private. If we decide that we want to vote via the Internet, more practical matters come into play in the implementation of the technology. The choices involved here are discussed in relation to the mediating role of concrete voting technologies in the relation between citizen and state

Post-Election Audits: Restoring Trust in Elections

With the intention of assisting legislators, election officials and the public to make sense of recent literature on post-election audits and convert it into realistic audit practices, the Brennan Center and the Samuelson Law, Technology and Public Policy Clinic at Boalt Hall School of Law (University of California Berkeley) convened a blue ribbon panel (the "Audit Panel") of statisticians, voting experts, computer scientists and several of the nation's leading election officials. Following a review of the literature and extensive consultation with the Audit Panel, the Brennan Center and the Samuelson Clinic make several practical recommendations for improving post-election audits, regardless of the audit method that a jurisdiction ultimately decides to adopt

Gaining assurance in a voter-verifiable voting system

The literature on e-voting systems has many examples of discussion of the correctness of the computer and communication algorithms of such systems, as well as discussions of their vulnerabilities. However, a gap in the literature concerns the practical need (before adoption of a specific e-voting system) for a complete case demonstrating that the system as a whole has sufficiently high probability of exhibiting the desired properties when in use in an actual election. This paper discusses the problem of producing such a case, with reference to a specific system: a version of the Prêt à Voter scheme for voter-verifiable e-voting. We show a possible organisation of a case in terms of four main requirements – accuracy, privacy, termination and ‘trustedness’– and show some of the detailed organisation that such a case should have, the diverse kinds of evidence that needs to be gathered and some of the interesting difficulties that arise

Explanation and trust: what to tell the user in security and AI?

There is a common problem in artificial intelligence (AI) and information security. In AI, an expert system needs to be able to justify and explain a decision to the user. In information security, experts need to be able to explain to the public why a system is secure. In both cases, the goal of explanation is to acquire or maintain the users' trust. In this paper, we investigate the relation between explanation and trust in the context of computing science. This analysis draws on literature study and concept analysis, using elements from system theory as well as actor-network theory. We apply the conceptual framework to both AI and information security, and show the benefit of the framework for both fields by means of examples. The main focus is on expert systems (AI) and electronic voting systems (security). Finally, we discuss consequences of our analysis for ethics in terms of (un)informed consent and dissent, and the associated division of responsibilities