Suman Bijapur, Shilpa Patil, Parimala, Shantala P H
With unparalleled threats to the integrity of digital information, democratic practices, and public confidence in media, deepfake technology comprises a new class of harm. Deep generative models can be used to generate realistic looking (and sounding) fake human faces and voices, which is great news for bad actors who seek to spread misinformation, commit crimes and ruin journalism. CyberLink Fights Deepfakes with New AI Model That Uses Neural Network Traditional methods used to identify deepfakes have depended on centralised AI systems that can't be trusted at face value and there is little or no way of proving a piece of content's authenticity. In this work, we have presented a solution that involves multi-modal deepfake detection and has utilized learning-based forgery detection framework to be deployed on blockchain for evidence tamper resistance. The proposed framework employs a hybrid CNN-RNN architecture that computes facial, audio and metadata feature in parallel to detect unseen deepfakes with accuracy of 94.2%, compared to the single-modal baselines (CNN only: 81.3%, and audio only: 67.4%). Novelty: Blockchain timestamping with cryptographically secured certificates of authenticity for third-party verification while protected proprietary detection logic is not revealed. At the computational efficiency and bandwidth threshold required for edge deployment, video processing at 30 FPS and only 2.1 MBs makes this applicable on any average mobile device. It holds for 12k synthetic videos (celebrities, politicians, newscasters) and diverse deepfake generation methods (FaceSwap, DeepFaceLab, StyleGAN). Societal impact: framework mitigates $1.2T annual disinformation damage and champions digital rights through decentralized verification. Via mashable.com Framework addresses the convergence of deepfake detection, blockchain authentication and the case for sustainable cybersecurity: As a global community grapples with synthetic media in ways we've never seen before, support online safety experts to respond.
Open access
2 source records
Generative Adversarial Networks and Image Synthesis
Abstract Cheap, disposable online identities make abuse easier to externalize. Users can harass, evade bans, amplify content through fake accounts, or abandon a damaged reputation at low cost, while other users, moderators, and platforms bear the consequences. This paper examines verified pseudonymity as an institutional response to that problem. First, I model online communities as club-governed informational commons in which incivility degrades the shared environment and raises enforcement costs. The model shows that conduct can improve when sanctions attach to a persistent pseudonymous identity and when users have future access, reputation, or governance rights at stake. Second, I compare verified pseudonymity with open pseudonymity, real-name mandates, centralized know-your-customer verification, algorithmic moderation, and no intervention. Decentralized identifiers, verifiable credentials, proof of personhood, and non-transferable standing credentials matter because they can separate authentication from public identification. Third, I add a community-currency layer that separates access to scarce attention from governance rights. The result is a governance framework in which accountability depends less on public naming than on durable standing, credible sanctions, and reusable privacy-preserving credentials.
In traditional, one-vote-per-person voting systems, privacy equates with ballot secrecy: voting tallies are published, but individual voters' choices are concealed. Voting systems that weight votes in proportion to token holdings, though, are now prevalent in cryptocurrency and web3 systems. We show that these weighted-voting systems overturn existing notions of voter privacy. Our experiments demonstrate that even with secret ballots, publishing raw tallies often reveals voters' choices. Weighted voting thus requires a new framework for privacy. We introduce a notion called B-privacy whose basis is bribery, a key problem in voting systems today. B-privacy captures the economic cost to an adversary of bribing voters based on revealed voting tallies. We propose a mechanism to boost B-privacy by noising voting tallies. We prove bounds on its tradeoff between B-privacy and transparency, meaning reported-tally accuracy. Analyzing 3,582 proposals across 30 Decentralized Autonomous Organizations (DAOs), we find that the prevalence of large voters ("whales") limits the effectiveness of any B-Privacy-enhancing technique. However, our mechanism proves to be effective in cases without extreme voting weight concentration: among proposals requiring coalitions of $\geq5$ voters to flip outcomes, our mechanism raises B-privacy by a geometric mean factor of $4.1\times$. Our work offers the first principled guidance on transparency-privacy tradeoffs in weighted-voting systems, complementing existing approaches that focus on ballot secrecy and revealing fundamental constraints that voting weight concentration imposes on privacy mechanisms.
Kiana Kiashemshaki, Elvis Nnaemeka Chukwuani, Mohammad Jalili Torkamani, Negin Mahmoudi
Blockchain technology offers a promising foundation for modernizing E-Voting systems by enhancing transparency, decentralization, and security. Yet, real-world adoption remains limited due to persistent challenges such as scalability constraints, high computational demands, and complex privacy requirements. This paper presents a comparative framework for analyzing blockchain-based E-Voting architectures, consensus mechanisms, and cryptographic protocols. We examine the limitations of prevalent models like Proof of Work, Proof of Stake, and Delegated Proof of Stake, and propose optimization strategies that include hybrid consensus, lightweight cryptography, and decentralized identity management. Additionally, we explore the novel role of Large Language Models (LLMs) in smart contract generation, anomaly detection, and user interaction. Our findings offer a foundation for designing secure, scalable, and intelligent blockchain-based E-Voting systems suitable for national-scale deployment. This work lays the groundwork for building an end-to-end blockchain E-Voting prototype enhanced by LLM-guided smart contract generation and validation, supported by a systematic framework and simulation-based analysis.
The digitization of democratic processes promises greater accessibility but presents challenges in terms of security, privacy, and verifiability. Existing electronic voting systems often rely on centralized architectures, creating single points of failure and forcing too much trust in authorities, which contradicts democratic principles. This research addresses the challenge of creating a secure, private e-voting system with minimized trust dependencies designed for the most versatile personal device: the smartphone. We introduce SmartphoneDemocracy, a novel e-voting protocol that combines three key technologies: the emerging European Digital Identity (EUDI) Wallet for Sybil-resistant identity verification, Zero-Knowledge Proofs for privacy-preserving validation, and a peer-to-peer blockchain (TrustChain) for a resilient, serverless public bulletin board. Our protocol enables voters to register and cast ballots anonymously and verifiably directly from their smartphones. We provide a detailed protocol design, a security analysis against a defined threat model, and a performance evaluation demonstrating that the computational and network overhead is feasible for medium- to large-scale elections. By developing and prototyping this system, we demonstrate a viable path to empower citizens with a trustworthy, accessible, and user-controlled digital voting experience.
Md. Rafiqul Islam, Muhammad Haseeb, Hina Batool, Nasir Ahtasham · 5 authors
The integrity of global elections is increasingly under threat from artificial intelligence (AI) technologies. As AI continues to permeate various aspects of society, its influence on political processes and elections has become a critical area of concern. This is because AI language models are far from neutral or objective; they inherit biases from their training data and the individuals who design and utilize them, which can sway voter decisions and affect global elections and democracy. In this research paper, we explore how AI can directly impact election outcomes through various techniques. These include the use of generative AI for disseminating false political information, favoring certain parties over others, and creating fake narratives, content, images, videos, and voice clones to undermine opposition. We highlight how AI threats can influence voter behavior and election outcomes, focusing on critical areas, including political polarization, deepfakes, disinformation, propaganda, and biased campaigns. In response to these challenges, we propose a Blockchain-based Deepfake Authenticity Verification Framework (B-DAVF) designed to detect and authenticate deepfake content in real time. It leverages the transparency of blockchain technology to reinforce electoral integrity. Finally, we also propose comprehensive countermeasures, including enhanced legislation, technological solutions, and public education initiatives, to mitigate the risks associated with AI in electoral contexts, proactively safeguard democracy, and promote fair elections.
In response to the data revolution, academic research and media attention have increasingly focused on the technological adaptation and innovation displayed by the far right. The greatest attention is paid to social media and how groups and organizations are utilizing technological advancement and growth in virtual networks to increase recruitment and advance radicalization on a global scale. As with most social and political endeavors, certain technologies are in vogue and thus draw the attention of users and regulators and service providers. This creates a technological blind spot within which extremist groups frequently operate older and less well regarded technologies without the oversight that one might expect. This article examines the less well-studied traditional and official websites of the Ku Klux Klan, the most established and iconic of American far-right organizations. By incorporating non-participant observation of online spaces and thematic analysis, this research analyzes the evolution of 26 websites, from their emergence in the early 1990s to the present day. We examine the ways in which traditional printed communications and other ephemera have progressed with advances in technology, focusing on the following central elements of Klan political activism and community formation: Klan identity, organizational history, aims and objectives; technology and outreach, including online merchandise and event organization; and the constructions of whiteness and racism. The results add value and insight to comparable work by offering a unique historical insight into the ways in which the Klan have developed and made use of Web 1.0, Web 2.0, and Web3 technologies.
Open access
Hate Speech and Cyberbullying Detection
Social Media and Politics
Terrorism, Counterterrorism, and Political Violence
This paper investigates netizens’ viewpoints on Decentralized Finance (DeFi) using emotion theory and lexicon sentiment analysis via machine learning. The data of 15,000 tweets on DeFi is gathered through automated web-scraping. Emotion score is evaluated through sentiment lexicon analysis and includes anger, anticipation, disgust, fear, joy, sadness, surprise, trust, and primary sentiments. The supervised machine learning reveals a score of 47,054 sentiments from 15,000 tweets, showing predominantly positive and trust sentiments in the sample. The positive sentiment may describe potential of Decentralized market. Meanwhile, trust emotion was indicative of the market’s response to the transparency and security of the DeFi system. This study contributes to theoretically explaining the implications of the DeFi phenomenon under the lens of emotion theory.
Wenrui Zuo, Raúl J. Mondragón, Aravindh Raman, Gareth Tyson
There have been numerous recent attempts to “decentralize” social media platforms, loosely referred to as Web3. Such ideas, often underpinned by blockchain solutions, offer decentralized equivalents of well-known services (e.g., forums, social networks, video sharing sites, microblogs). One particularly challenging function to implement in such a design is content moderation, due to the lack of central control. Consequently, they often rely on user-controlled moderation, whereby each user must create their own personal block list to filter out content they do not wish to see. This paper presents a first study of user-controlled moderation on one exemplar Web3 social microblogging platform called memo.cash. Based on a dataset covering 391K posts, we study the factors that lead users to “mute” each other. We find that the most crucial factor is the platform action count, rather than the presence of things like hate speech. We also show that the followership network plays a pivotal role in determining their visibility on the platform, further influencing their muting behavior. This leads us to design tooling to automate the muting process on a per-user basis. We model this as a recommendation problem, and experiment with a number of state-of-the-art recommender engines. We show that our system can generate effective personalized mute lists for users.
Integrating healthcare into traffic accident prevention through predictive modeling holds immense potential. Decentralized Defense presents a transformative vision for combating cyberbullying, prioritizing user privacy, fostering a safer online environment, and offering valuable insights for both healthcare and predictive modeling applications. As cyberbullying proliferates in social media, a pressing need exists for a robust and innovative solution that ensures user safety in the cyberspace. This paper aims toward introducing the approach of merging Blockchain and Federated Learning (FL), to create a decentralized AI solutions for cyberbullying. It has also used Alloy Language for formal modeling of social connections using specific declarations that are defined by the novel algorithm in the paper on two different datasets on Cyberbullying and are available online. The proposed novel method uses DBN to run established relation tests amongst the features in two phases, the first is LSTM to run tests to develop established features for the DBN layer and second is that these are run on various blocks of information of the blockchain. The performance of our proposed research is compared with the previous research and are evaluated using several metrics on creating the standard benchmarks for real world applications.
The rise of blockchain and cryptocurrencies come with the promise of decentralizing transactions and disrupting the power of market intermediaries. Despite these promises, scholars argue that the risks associated with cryptocurrencies are still unclear. Some preliminary works investigate the manipulative role played by the circulation of problematic content on platforms such as Reddit, Twitter, Discord, or Telegram. Nonetheless, the research still lacks a clear and comprehensive picture of how widespread the phenomenon is across the whole ecosystem. Despite its prominence, Facebook is understudied in this context. To fill this gap, this work focuses on the role played by Meta’s main platform, as a venue employed to reach a wide audience prone to potential manipulative practices or scams related to cryptocurrencies. As part of a broader investigation on coordinated disinformation in Africa, we have come across a cluster of Facebook groups sharing content related to cryptocurrencies. The links shared by these networks revealed a very prolific cluster of 152 groups dedicated to Airdrop and Bounty initiatives for new cryptocurrencies. We collected a list of recent posts created by these groups between November 2021 and January 2022 (378,513 URLs). A preliminary analysis of these URLs pointed out an overwhelming presence of links to Telegram (47%) that highlights the central role played by this platform in this specific ecosystem. This paper explores the overlap between the cryptocurrency community and social media, analyzing how crypto-related projects are disseminated as a new type of problematic content on Facebook and Telegram.
The previous smart contract code comment (SCC) generation approaches can be divided into two categories: fine-tuning paradigm-based approaches and information retrieval-based approaches. However, for the fine-tuning paradigm-based approaches, the performance may be limited by the quality of the gathered dataset for the downstream task and they may have knowledge-forgetting issues. While for the information retrieval-based approaches, it is difficult for them to generate high-quality comments if similar code does not exist in the historical repository. Therefore we want to utilize the domain knowledge related to SCC generation in large language models (LLMs) to alleviate the disadvantages of these two types of approaches. In this study, we propose an approach SCCLLM based on LLMs and in-context learning. Specifically, in the demonstration selection phase, SCCLLM retrieves the top-k code snippets from the historical corpus by considering syntax, semantics, and lexical information. In the in-context learning phase, SCCLLM utilizes the retrieved code snippets as demonstrations, which can help to utilize the related knowledge for this task. We select a large corpus from a smart contract community Etherscan.io as our experimental subject. Extensive experimental results show the effectiveness of SCCLLM when compared with baselines in automatic evaluation and human evaluation.
Zsofia Baruwa, Sanjay Bhattacherjee, Sahil Rey Chandnani, Zhen Zhu
This work is the first study on the effects of attacks on cryptocurrencies as expressed in the sentiments and emotions of social media users. Our goals are to design the methodologies for the study including data collection, conduct volumetric and temporal analyses of the data, and profile the sentiments and emotions that emerge from the data. As a first step, we have created a first-of-its-kind comprehensive list of 31 events of 51% attacks on various PoW cryptocurrencies, showing that these events are quite common contrary to the general perception. We have gathered Twitter data on the events as well as benchmark data during normal times for comparison. We have defined parameters for profiling the datasets based on their sentiments and emotions. We have studied the variation of these sentiment and emotion profiles when a cryptocurrency is under attack and the benchmark otherwise, between multiple attack events of the same cryptocurrency, and between different cryptocurrencies. Our results confirm some expected overall behaviour and reactions while providing nuanced insights that may not be obvious or may even be considered surprising. Our code and datasets are publicly accessible.
The problem with police is not that they are fascist pigs but that our country is ruled by majoritarian pigs. Ta-Nehisi Coates To change the police without changing the police role in society is as futile as the labors of Sisyphus. John van Maanen This question is, I will argue, of considerable importance to political philosophy, because it exposes a tension in the liberal project as a whole. It has, unfortunately, been subject to relative neglect; there has until recently been very little philosophical or normative literature on policing, much less the policing of minorities.3 There are two reasons for this, both of them based ultimately on the perception that the problem is theoretically straightforward, and so does not raise any philosophically difficult questions.4 With respect to policing in general, many political philosophers appear to believe that the police are uninteresting, because they serve the purely instrumental role of enforcing statutory law. And with respect to minorities, widespread acceptance of the fascist pig theory leads to the perception that the problem is also normatively straightforward. If tensions between police and minorities are caused by the police being racist, then the solution is obviously for the police to become less racist. These two views, when combined, generate a highly simplistic account of the problem of policing minorities.5 It suggests that, since the police are there to enforce the law, all they need to do is enforce the law in a non-discriminatory way, treating all citizens equally, and the problem should go away. The argument, however, rests on a false premise, since the police do a great deal more than simply enforce the law, and it is primarily these other activities that give rise to problems. My preliminary contention in this article will be that both of the underlying theories about policing are false or misleading. Obviously, the police do enforce the law, but as several decades of work in the sociology of policing have shown, this is not all that they do, and, indeed, this does not even add up to a substantial fraction of what they do. And equally obviously, there are some police who are racist, both consciously and subconsciously, but this goes only part of the way to explaining the seriousness of the difficulties that practically every major police force experiences in its relations with particular a great deal of the for the in in on the subject in the that the on or has the of in many to the of the I will argue, it is to that policing is The is that who are to a subject to of and of that of the they I to this, Ta-Nehisi as the theory of to the that it a only on statutory law, is to this problem is the policing of minorities a in liberal To the in highly even when the is society is and the in to be are to society The article as I by two very normative of policing, about the of police The I to as the of policing, rests on the that police should be to law is to in and who have the to this, I will what I to as the of policing, the of statutory law as with of the The of the on this the of law to a of the of to The as a of policing is what the widespread for more as a to It is not difficult to however, that this a of normative difficulties in a The tension the on the part of the liberal to a on the of force only that a of The is that the police are subject to the for that the of law. this tension be by a and the activities of the police to law I will the by several reasons I this be I do not have any to to the underlying I do, however, that a of the of the problem is has been the subject of a great deal of in has of policing as not in the but many as This has many of is to the the police to as and in them with to normative The of the a of the of the problem and the to police are being to to in the in the they the to that they what the police do of the or it is the police that are they that statutory law a fraction of what the of the this what the police do, there any about the of is that they are of the who are to It is also liberal that this to force is or but also and law, and and in some law. 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become in until the of the to that, the by the as a to the of in the the of as the The not to this of until the a that in with the of this of should with the rise of policing is since the only to it has the not to but to a is a has so to all This that when the of and appear to the of that the are of the will be to fraction of is not but in to a the police are subject to two there are and other who that the police enforce there are of who as a of to in of This is what for the that the the of statutory law, also to this police in the between the and other of in the to have two in they without or there the of and the of and there the the of the the of the and the of and to the of and of in part because the as the for to be as the only of This to a of the importance of statutory law, the of the to the of has been The police however, to its as police a of The that the police enforce not but also the and so it is to be about its in the simply to the of the citizens the of what be the that are to and, in when they the of what be without to they the the this of a between a and that is to of to in a that has up the to a of in the to a who is to to deal with a who is a the of police the police are to force in these they to statutory law in to that of the that the they are or the reasons for they are are to that is in any a policing up of that is of the reasons that police all the of are only police is in by of the is to the that in of force has of by who for the The to or the of has a on other much of simply when it in force to be as a there is a about policing in the that, because there is substantial between the by police and the be by the The problem is not that and have the to It is also that the of to force a of in that is difficult to The of and is that it go on some however, and be citizens police in to deal with that for police is for that the police are in all of the underlying of the of these of the the police in of with the that they the the of and the of the police to enforce statutory law, on the of the underlying This is a major in the work of who that of police enforce when the of it has This is not because police on of the to but also because the of are the The are the on the of and who simply by the and of the police are in to and as the police the to with the law way the part of the is by the that rests the of the the police to to the and of the by in that are to of or that the of in these force to the that are to This is the of policing because the is to a is that be by the is or it what of the of in the of of a or a is And these are but are by police to up some other to but not to the of the The that some are the law by in a practically about what the police should it a a a of it the in the it a of These are very when it to the of they or are they And are they they it for or in a way that for the or with other of the And is should the be and the to should some or all be And to the should they be or as it is is a to the and of the by the is simply a on the part of the other to them that and in the are not being is the role that of in police police are more to and to when the to a less as they are more to when they The of the a to to and to to and so is by of a or the police on to who the to the The is, of being for all between the of and and police also on who are as the of of the and and, until this it is not difficult to the of policing tension with the of political The of who is and who is not a of highly are based on the law in a liberal to on a of of society are not subject to any when it to the are all with these in is than work is than is than is than and in a of is than up in the up is than all and so a police is to a particular is a who to have in the the or a who to be with more it is these the of and are to the John in that who in a and does so in a way that on should be both and The part of this has a great deal more than the the law has become a great deal less about many of the that and even have 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of the of of by police for and a police that or with for political or this of police up in a way that a to a with a by in a with of the they a is of this, there is considerable in the literature about it is to the of the it is not to what or is to and the of to what are police or the in the of and of are as to there is the that more and not do much to police relations with of the This has a great deal of on the or that to this in to is to without is to they with respect to minorities that are not a of the or of the this it is not difficult to of but in relations and the of minorities in a liberal society to the of policing even in the of This has been in the with a of that the to the I will the highly account of the that is the of policing it is to by a society between two of the the of the there is need to any of or between the or any or of both are by the of law, there is a police and are the both this it is not difficult to the our it does not the is on the police only that when of the to the that a between the of the and that of the police this there is a that to the of policing of the the of to the police do not of law, but the that police in that the the particular difficulties when these are by of a of the that they not what the not be to what is and what is not when a is of and not be with and they will be to who is and who is as a of they up treating both and of the of this with police and the to to relations with the that there is with its and so many by the of police on and even treating and citizens as they These widespread of police the that the being the police also have when with who is a and who is not in even need to a in to the of all police the it difficult to the because they are to highly in they of leads to a of in the of the police about to be to with in the and to the of or with force or in that do not the that the police are not of the of the but a force that of to its This leads to of the of the in leads to more as citizens become less to in with of leads the police to more up the more to and to police up more because of to force in to The of the police has a on both and The of the is not because of a to the to the of the to they than with respect to of that them to with a of the is of a that the normative of the police the that serve as a a great deal of is with and so a in the of the police to in the of the police it more difficult to who do by it for the police to the of has on the of does have a a a in police to in by And the of without the perception of a as a of police to as it have for policing is to what is to as the of the in with a with will have to a a the and so a with by many of these will be and so the will be more to the a the for policing, not but also by the of the to its The on the that are less are to or they are to when they in be in this because of the way that it citizens in the for policing police more to to the they This the that majoritarian policing, than the to and the of have the of the of the on the This for the of being both and the police are a the to have much of a on This of rise to the perception the that the of the police is to its not to or It in the that police the the that the of they and so this the of policing to My in this account is to a even highly there are that the of it should be are particular to the and so should be not to this widespread in the both the of and leads police to much more of police on in of the and the of police it very difficult to and of these be simply by other There however, other that be in and are to that they The is obviously of the or minorities, in as as a of for This to the of of the police in the of in to have to It also to in as of to the as a and be to between its and part to and are also than the a that is with more and is of a of between all of these and it is as a the that the to in of with generate for police both by the of the and by to This also for police and the that police will in a more This to some on minorities 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Sihao Hu, Tiansheng Huang, Fatih İlhan, Selim Furkan Tekin · 5 authors
This paper provides a systematic analysis of the opportunities, challenges, and potential solutions of harnessing Large Language Models (LLMs) such as GPT-4 to dig out vulnerabilities within smart contracts based on our ongoing research. For the task of smart contract vulnerability detection, achieving practical usability hinges on identifying as many true vulnerabilities as possible while minimizing the number of false positives. Nonetheless, our empirical study reveals contradictory yet interesting findings: generating more answers with higher randomness largely boosts the likelihood of producing a correct answer but inevitably leads to a higher number of false positives. To mitigate this tension, we propose an adversarial framework dubbed GPTLens that breaks the conventional one-stage detection into two synergistic stages $-$ generation and discrimination, for progressive detection and refinement, wherein the LLM plays dual roles, i.e., auditor and critic, respectively. The goal of auditor is to yield a broad spectrum of vulnerabilities with the hope of encompassing the correct answer, whereas the goal of critic that evaluates the validity of identified vulnerabilities is to minimize the number of false positives. Experimental results and illustrative examples demonstrate that auditor and critic work together harmoniously to yield pronounced improvements over the conventional one-stage detection. GPTLens is intuitive, strategic, and entirely LLM-driven without relying on specialist expertise in smart contracts, showcasing its methodical generality and potential to detect a broad spectrum of vulnerabilities. Our code is available at: https://github.com/git-disl/GPTLens.
Wenrui Zuo, Aravindh Raman, Raúl J. Mondragón, Gareth Tyson
Web3 social media strives to eliminate the need for centralized management by building upon on technologies such public ledgers and smart contracts. This has generated significant hype, but creates many notable challenges, many of which remain unaddressed. One such challenge is content moderation. Specifically, the immutable nature of blockchain means that it becomes impossible to retrospectively delete posts. This means that illegal content posts cannot be moderated or removed. In an attempt to overcome this, Web3 platforms, such as memo.cash, allow users to filter out posts from their personal timelines. Taking memo.cash as a use case, the goal of this work is to study the efficacy of the approach, and identify associated challenges. A particularly unique feature of memo.cash is that users must pay money (satoshi) for each social action (e.g., posting and blocking other users). We conjecture that this may impact the nature of moderation, particularly among poorer users. To explore this, we gather data from memo.cash covering 24K users, 317K posts, and 2.57M user actions. We investigate how the need to pay may impact the moderation system and propose potential solutions to address the challenges that arise.
The development of an electronic voting system that would replace traditional election procedures is a research topic of great interest for many years. Blockchain technology could provide some guarantees and fulfill strong requirements for electronic voting platforms, such as transparency, immutability, and confidentiality. From time to time research is conducted to address problems in voting systems. Many research works attempt to implement secure and reliable voting systems, which address known security, anonymity, and fraud issues that might threaten such systems. This paper presents a proposal of a secure electronic voting system, the EtherVote, using the Ethereum Blockchain network that focuses deeply on the field of identification of eligible citizens. The proposed system will be entirely based on Blockchain without any central authority servers or databases, thus improving security, privacy, and election cost. Limitations, problems, and solutions are discussed, in order to make the proposed electronic voting system ideal and ready to use for national elections.
Arnab Mukherjee, Souvik Majumdar, Anup Kumar Kolya, S. Nandi
Within a modern democratic nation, elections play a significant role in the nation's functioning. However, with the existing infrastructure for conducting elections using Electronic Voting Systems (EVMs), many loopholes exist, which illegitimate entities might leverage to cast false votes or even tamper with the EVMs after the voting session is complete. The need of the hour is to introduce a robust, auditable, transparent, and tamper-proof e-voting system, enabling a more reliable and fair election process. To address such concerns, we propose a novel solution for blockchain-based e-voting, focusing on the security and privacy aspects of the e-voting process. We consider the security risks and loopholes and aim to preserve the anonymity of the voters while ensuring that illegitimate votes are properly handled. Additionally, we develop a prototype as a proof of concept using the Ethereum blockchain platform. Finally, we perform experiments to demonstrate the performance of the system.
Misinformation constitutes one of the main challenges to counter the infodemic: misleading news, even if not blatantly false, can cause harm especially in crisis scenarios such as the pandemic. Due to the fast proliferation of information across digital media, human fact-checkers struggle to keep up with fake news, while automatic fact-checkers are not able to identify the grey area of misinformation. We, thus, propose to reverse engineer the manipulation of information offering citizens the means to become their own fact-checkers through digital literacy and critical thinking. Through a corpus analysis of fact-checked news about COVID-19, we identify 10 fallacies–arguments which seem valid but are not–that systematically trigger misinformation and offer a systematic procedure to identify them. Next to fallacies, we examine the types of sources associated to (mis-/dis-)information in our dataset as well as the type of claims making up the headlines. The statistical patterns surfaced from these three levels of analysis reveal a misinformation ecosystem where no source type is exempt from flawed arguments with frequent evading the burden of proof and cherry picking behaviors, even when descriptive claims are at stake. In such a scenario, exercising the audience’s critical skills through fallacy and semantic analysis is necessary to guarantee fake news immunity.
Remote voting has become more critical in recent years, especially since the COVID-19 outbreak. Blockchain technology and its benefits such as decentralization, security, and transparency have given rise to proposals for blockchain-based voting systems. However, the traceability of blockchain transactions violates voter anonymity in existing proposals. Besides, transaction costs also need to be considered. Solutions that may cause repeated elections should be avoided for a low-cost scalable voting system. In this work, we propose ElectAnon, a blockchain-based, self-tallying, and ranked-choice voting protocol focusing on anonymity, robustness, and scalability. ElectAnon achieves anonymity by enabling voters to register with identity commitments and cast their votes via zero-knowledge proofs. Robustness is realized by removing the direct control of the authorities in the voting process by using timed-state machines. Each voter encodes the ballot into a single integer and blinds the vote off-chain while making the verification on-chain. This makes the protocol infinitely scalable in the number of voters. ElectAnon is also a solution for governance in Decentralized Autonomous Organizations (DAO): It includes a candidate proposal module and an algorithm-agnostic mechanism to plug-in different tallying methods easily. The Merkle forest extension is proposed for conducting even more trustless elections. ElectAnon is implemented with smart contracts based on Ethereum Virtual Machine (EVM) and a zero-knowledge gadget, Semaphore. The implementation also includes two different sophisticated tallying methods, Borda Count and Tideman. Experimental results show that a 40-voter and 10-candidate election can be implemented with the gas consumption reduced up to 89% compared to previous works. While other studies could not exceed a 25,000-voter setup, ElectAnon has been observed to run safely for 1,000,000 voters. The implementation can be found at https://github.com/ceyonur/electanon .
Domain-specific Microservice Reference Architectures (MSRA) have become relevant study objects in software technology. They facilitate the technical evaluation of service designs, compositions patterns and deployment configurations in realistic operational practice. Current knowledge about MSRA is predominantly confined to business domains with modest numbers of users per application. Due to the ongoing massive digital transformation of society, people-related online services in e-government, e-health and similar domains must be designed to be highly scalable at entire nation level at affordable infrastructure cost. With ZVAX, we present such a service in the e-health domain. Specifically, the ZVAX implementation adheres to an MSRA for pandemic-related processes such as vaccination registration and passenger locator form submission, with emphasis on selectable levels of privacy. We argue that ZVAX is valuable as study object for the training of software engineers and for the debate on arbitrary government-to-people services at scale.
Amrita Dhillon, Grammateia Kotsialou, Peter McBurney, Luke Riley
This work discusses the potential of a blockchain based infrastructure for a decentralised online voting platform. When compared to paper based voting, online voting can vastly increase the speed that votes can be counted, expand the overall accessibility of the election system and decrease the cost of turnout. Yet despite these advantages, online voting for political office is subject to fraud at various levels due to its centralised nature. In this paper, we describe a general architecture of a centralised online voting system and detail which areas of such a system are vulnerable to electoral fraud. We then proceed to introduce the key ideas underlying blockchain technology as a decentralised mechanism that can address these problems. We discuss the advantages and weaknesses of the blockchain technology, the protocols the technology uses and what criteria a good blockchain protocol should satisfy (depending on the voting application). We argue that the decentralisation inherent in the blockchain technology could increase the public's trust in national elections, as well as eliminate voter impersonation and double voting. We conclude with a discussion regarding how economists and social scientists can collaborate with the blockchain community in a research agenda on the design of efficient blockchain protocols and new voting systems such as liquid democracy.