Due to the continuous improvement of traffic analysis technology, traditional covert channels have become insecure and vulnerable to human sabotage. Blockchain technology has the characteristics of immutability and anonymity, making covert communication more unmonitored and robust. However, it also brings about low communication efficiency. In this article, we adopt the idea of transaction rounds and propose for the first time the construction of HMAC values order (HVO) scheme. Furthermore, we further propose a HMAC values and transaction matrices (HV-TM) scheme to improve communication efficiency. This article is the first to use the gas field to embed data to improve the embedding rate. Use the random numbers generated by the Mersenne Twister algorithm to disrupt the order of addresses to improve the concealment of reused addresses. Experiments have shown that the two schemes have higher communication efficiency and better embedding rate than existing schemes.
Advanced Steganography and Watermarking Techniques
Delegated-Proof-of-Stake (DPoS) blockchains, such as EOSIO, Steem and TRON, are governed by a committee of block producers elected via a coin-based voting system. We recently witnessed the first de facto blockchain takeover that happened between Steem and TRON. Within one hour of this incident, TRON founder took over the entire Steem committee, forcing the original Steem community to leave the blockchain that they maintained for years. This is a historical event in the evolution of blockchains and Web 3.0. Despite its significant disruptive impact, little is known about how vulnerable DPoS blockchains are in general to takeovers and the ways in which we can improve their resistance to takeovers. In this paper, we demonstrate that the resistance of a DPoS blockchain to takeovers is governed by both the theoretical design and the actual use of its underlying coin-based voting governance system. When voters actively cooperate to resist potential takeovers, our theoretical analysis reveals that the current active resistance of DPoS blockchains is far below the theoretical upper bound. However in practice, voter preferences could be significantly different. This paper presents the first large-scale empirical study of the passive takeover resistance of EOSIO, Steem and TRON. Our study identifies the diversity in voter preferences and characterizes the impact of this diversity on takeover resistance. Through both theoretical and empirical analyses, our study provides novel insights into the security of coin-based voting governance and suggests potential ways to improve the takeover resistance of any blockchain that implements this governance model.
To address privacy concerns of state-of-the-art centralized machine learning in non-intrusive load monitoring (NILM) applications, the adoption of federated learning (FL) has emerged as a solution to transfer training processes from cloud servers to edge devices. Nevertheless, conventional FL encounters several challenges including architecture safety, incentive mechanism, computing cost, and personalization. To overcome these challenges, the study proposes a self-motivated decentralized FL scheme for NILM, named blockchain-based clustered FL, by combining blockchain mechanism with clustered FL, incentivizing suitable clients to participate in FL by offering rewards based on data size and model performance. Under NILM-related differential privacy protections, the Laplace noise is injected into the first layer of neural networks in the blockchain-based clustered FL, and a decay factor is employed to mitigate the adverse effects of excessive noise on performance. Lightweight training techniques such as data quantization and weight pruning are employed to reduce computational complexity. Furthermore, a clustering approach is utilized to create multiple global models, thereby enhancing the model personalization degree. It is verified by the case study that the blockchain-based clustered FL outperforms the conventional FL in both accuracy and operation risk, and offers much superior performance and a more robust model compared to local training.
Abstract Business intelligence (BI) is driven by data and provides valuable business insights and decision support through data analysis, mining, and visualization. The application of blockchain technology in electronic voting can make the voting process more fair and transparent. This is because the decentralized nature of blockchain technology ensures that voting data is not lost due to a single central server failure and also mitigates the risk of data tampering. However, electronic voting still faces security issues that are not easily resistant to quantum attacks. To address these challenges, we propose post-quantum cryptography and verifiable random functions for secure and efficient business intelligence electronic voting. Firstly, we propose a post-quantum verifiable random function algorithm that can resist quantum computer attacks. Secondly, we introduce a consensus algorithm based on random functions to achieve fast and efficient consensus. Thirdly, we propose a blockchain architecture based on the consensus algorithm to achieve secure and efficient blockchain applications. By integrating post-quantum verifiable random functions, consensus algorithms, and blockchain technology, we present an efficient business intelligence electronic voting system. Implementation and comparison with relevant designs demonstrate that this system provides efficient and secure electronic voting services for business intelligence users. Furthermore, the efficient consensus algorithm can be utilized to improve other blockchain applications or decentralized applications.
Przemysław Błaśkiewicz, Mirosław Kutyłowski, Anna Lauks-Dutka
Recently, solutions such as distributed ledgers have been promoted in order to achieve undeniability of past transactions. This creates the situation where signed transactions of a given person are recorded in a distributed data structure and are publicly available. We show that behind such a fully legitimate and trustworthy ledger system one can create a perfect infrastructure for a covert ledger for presumably illegal activities. Namely, a signer may hide signatures behind purely innocent signatures of legitimate transactions. Such signatures, called darknet signatures within this paper, can be used by the signer to authenticate illegal operations, where signature delivery is by means of the distributed ledger, and thereby to some degree anonymous. The darknet signatures are undetectable apart from the designated recipient - the signatures posted in the ledger look exactly the same as in case of an honest signer. In particular no extra data need to appear, thereby there are no witnesses of malicious activities in the form, e.g. of suspicious random components. To demonstrate the reality of the threat, we present a simple example realization of darknet signatures hidden in Schnorr signatures. As the construction is quite elementary in this case, it should serve as a strong warning against using probabilistic signature schemes in a distributed ledger.
The voting process serves as the mechanism to translate public opinion into actionable measures, significantly impacting democracy. Ensuring the transparency, reliability, and security of the voting procedure is essential to maintain the integrity and legitimacy of the entire system. Blockchain-based voting systems have gained popularity due to the immutability and advancements in blockchain technology. Creating a secure electronic voting system that offers the transparency and flexibility of electronic systems while preserving fairness and privacy has long been a challenge. This paper introduces a method for collecting data from various sources and databases using transparent Blockchain technology. The proposed Blockchain-based solution is dependable, secure, and ensures privacy. The objective of this paper is to leverage blockchain technology to construct a transparent and secure voting system. The development, testing, and deployment of smart contracts are executed using the Truffle framework, while a local blockchain network is established using the Ganache tool. MetaMask is employed for account validation. This paper also presents the cost analysis of the voting transactions.
To enhance security and confidentiality in P2P communication, we implement a blockchain-enabled system of identity management and mutual authentication protocol, Be-Mutual. It provides user-centric identity management based on blockchain addresses and employs mutual authentication based on asymmetric encryption to prevent unauthorized access. We address the complexity of blockchain addresses, a significant chal-lenge in real-world applications such as Decentralized Physical Infrastructure (DePIN) and Decentralized Wireless (DeWi), by integrating the Blockchain-enabled Domain Name System (Be-DNS) into BeMutual. BeDNS maps complex blockchain addresses to easy-to-remember domain names, improving user experience without sacrificing security. The proposed BeMutual system, combining blockchain-based identity management, mutual authentication, and domain name resolution, offers a pioneering solution for secure and user-friendly P2P communication in decentralized environments.
The role of digital identity systems in today’s cyber infrastructure is pivotal to providing secure access to online services. Privacy-preserving mechanisms, however, are becoming more important as cyber threats develop. Especially in large networks, zero-knowledge proofs (ZKPs) are an effective way to enhance privacy in digital identity systems. When used during authentication, they protect the privacy of user data by verifying knowledge to another entity without unveiling the actual data. A ZKP can also reduce identity theft risks, mitigate man-in-the-middle attacks, and enhance security when integrated into privacy-preserving networks. In this paper, we examine the role that ZKPs play in privacy-preserving networks and the possibility of using them in this regard, in order to gain insight into their application in digital identity systems.
Abstract Bitcoin is a decentralized P2P cryptocurrency. It supports users to use pseudonyms instead of network addresses to send and receive transactions at the data layer, hiding users’ real network identities. Traditional transaction tracing attack cuts through the network layer to directly associate each transaction with the network address that issued it, thus revealing the sender’s network identity. But this attack can be mitigated by Bitcoin’s network layer privacy protections. Since Bitcoin protects the unlinkability of Bitcoin addresses and there may be a many-to-one relationship between addresses and nodes, transactions sent from the same node via different addresses are seen as coming from different nodes because attackers can only use addresses as node identifiers. In this paper, we proposed the evicting and filling attack to expose the correlations between addresses and cluster transactions sent from different addresses of the same node. The attack exploited the unisolation of Bitcoin’s incoming connection processing mechanism. In particular, an attacker can utilize the shared connection pool and deterministic connection eviction strategy to infer the correlation between incoming and evicting connections, as well as the correlation between releasing and filling connections. Based on inferred results, different addresses of the same node with these connections can be linked together, whether they are of the same or different network types. We designed a multi-step attack procedure, and set reasonable attack parameters through analyzing the factors that affect the attack efficiency and accuracy. We mounted this attack on both our self-run nodes and multi-address nodes in real Bitcoin network, achieving an average accuracy of 96.9% and 82%, respectively. Furthermore, we found that the attack is also applicable to Zcash, Litecoin, Dogecoin, Bitcoin Cash, and Dash. We analyzed the cost of network-wide attacks, the application scenario, and proposed countermeasures of this attack.
Delegated Proof of Stake (DPoS) is a high throughput, low power consumption consensus mechanism is which elected participants or witnesses vote to accept blocks to be included in the blockchain ledger. However, DPoS is prone to centralization of voting power which can introduce bias and degrade the usability of the blockchain. In this work, we propose the concept of virtual stake which measures the truthfulness of witness voting throughout the round. Virtual stake at the end of a round is used as incentive for the next election of witnesses, but electors have a discretionary right to cast a portion of their votes for candidate witnesses regardless of their past behavior. Virtual stake is also used to guide the process of selecting the leader(s) to propose blocks for voting in PBFT cycles within the round, which prevents mis.behaving witnesses from submitting blocks. We describe and solve the analytical model of witness behavior, assuming that witnesses can be categorized into behavioral classes with different probability of truthful voting, false voting, and abstention. Our results show the impact of class populations, and voting behavior on virtual stakes, distribution of votes, and, most importantly, on overall consensus probability. The impact of centralization and witness misbehavior in voting can be countered by an increase of voting groups and decrease of round size, although further control of voting process during a round may be necessary to maintain the desired performance level of the blockchain system.
Meng Li, Yanzhe Shen, Guixin Ye, Jialing He · 8 authors
Digital forensics is crucial to fight crimes around the world. Decentralized Digital Forensics (DDF) promotes it to another level by channeling the power of blockchain into digital investigations. In this work, we focus on the privacy and security of DDF. Our motivations arise from (1) how to track an anonymous-and-malicious data user who leaks only a part of the previously requested data, (2) how to achieve access control while protecting data from untrusted data centers, and (3) how to enable efficient and secure search on the blockchain. To address these issues, we propose Themis: an anonymous and secure DDF scheme with traceable anonymity, private access control, and efficient search. Our framework is boosted by establishing a Trusted Execution Environment in each authority (blockchain node) for securing the uploading, requesting, and searching. To instantiate the framework, we design a secure and robust watermarking scheme in conjunction with decentralized anonymous authentication, a private and fine-grained access control scheme, and an efficient and secure search scheme based on a dynamically updated data structure. We formally define and prove the privacy and security of Themis. We build a prototype with Ethereum and Intel SGX2 to evaluate its performance, which supports processing data from a considerable number of data providers and investigators.
(English) One of the most common fears regarding electronic voting is that a voting device will disregard the voter's intent and cast a different vote instead. An undetectable attack like that on a large scale will allow the adversary to control the election result completely. Therefore, the cast-as-intended verification, which ensures that the ballot contains the voter's choice and not something else, is crucial. Another common fear when introducing electronic voting is coercion, which captures a variety of ways the coercer can use to prevent voters from expressing their will. Hence, coercion resistance is a valuable property of electronic voting as well. One particularly challenging task is to find a trade-off between ensuring a voter cannot be coerced and, at the same time, preventing a malicious voting device from cheating. This thesis explores this trade-off to find how we can provide coercion-resistant cast-as-intended verification. The contributions can be roughly divided into three parts: (1) study in the standard settings, (2) exploration of post-quantum cryptography, and (3) practical constructions and search for the limitations of both properties. In the first part, we give an extensive overview of the current state of the art in electronic voting literature regarding those properties. Then, we put forward two formal definitions for achieving coercion-resistant cast-as-intended verification in settings without pre-exchanged data. After that, we present two practical constructions and prove their security under the proposed definitions. We also show the efficiency of our proposals by providing proof of the concept implementations. In the second part, we switch to post-quantum settings and identify the usability issues rooted in the lattice-based math affecting both proposed solutions. To address those issues, we present a generic transformation that departs from an interactive zero-knowledge system (that might require multiple re-runs to complete the protocol) and obtains a 3-move zero-knowledge system (without re-runs). The transformation combines the well-known Fiat-Shamir technique with several initially exchanged messages. The resulting 3-move system enjoys honest-verifier zero-knowledge and can be easily turned into a fully deniable proof using standard methods. In the final part, we focus on the practical aspects of the coercion-resistant cast-as-intended verification. First, we present the case of a computationally limited voter, which we consider the most realistic. We show that even a computationally limited voter can enjoy coercion-resistant cast-as-intended verification, but a help of a simple aid device for nonce generation is required. Also, we demonstrate that our generic definition easily adapts to the constraints of the limited voter. After that, we present ongoing work that focuses on the cases of extreme coercion based on new and unexplored mechanisms such as delay encryption and blockchain. We show an advanced coercive attack on our first construction and describe an improvement to the second solution that reduces the number of interactions to an optimal three rounds. To summarize, we start by studying coercion-resistant cast-as-intended verification in standard settings, which results in formal definitions and two practical solutions. Then we move into the post-quantum world, where we learn that an extra step is needed to preserve the usability of our previously proposed constructions, which results in the generic transformation to avoid protocol re-runs. After that, we concentrate on a computationally limited voter, which leads to another simple solution and shows the adaptability of our original definitions. Finally, we explore the extreme coercion threats, which result in a new coercion attack on the first construction and upgrade of the second solution. (Català) Una de les preocupacions més comunes pel que fa al vot electrònic és que el dispositiu de votació no tingui en compte la intenció del votant i emeti un vot diferent. Un atac com aquest, si no fos detectable, a gran escala permetria a l'adversari controlar completament el resultat electoral. Per tant, és crucial permetre la propietat de verificació de la intenció del vot emès, la qual garanteix que la papereta contingui la intenció del votant i no una altra cosa. Una altra preocupació és la coacció, que engloba una varietat de maneres que el coaccionador pot utilitzar per obligar que els votants expressin la seva voluntat. La prevenció de la coacció també és una propietat valuosa del vot electrònic .Una tasca especialment difícil és trobar un compromís entre assegurar que un votant no pot ser coaccionat i, al mateix temps, evitar que un dispositiu de vot compromès faci trampes. Aquesta tesi analitza aquesta problemàtica; les contribucions de la tesi es poden dividir en tres parts: (1) estudi de les configuracions d’escenaris de vot estàndards, (2) exploració de la criptografia post-quàntica i (3) construccions pràctiques i cerca de les limitacions d'ambdues propietats. A la primera part, donem una visió general de l'estat actual de la literatura sobre el vot electrònic relacionada a aquestes propietats. A continuació, proposem dues definicions formals per assolir una verificació resistent a la coacció de la intenció del vot emès, en escenaris on no existeix un intercanvi de dades previ. Després, presentem dues propostes pràctiques i demostrem la seva seguretat sota les definicions proposades. També mostrem l'eficàcia de les nostres propostes implementant proves de concepte A la segona part, canviem a l’escenari post-quàntic amb matemàtiques basades en reticles i identifiquem els problemes d'usabilitat que afectarien ambdues solucions proposades en aquest nou escenari. Per solucionar-los, presentem una transformació genèrica que parteix d'un sistema interactiu de coneixement nul (que podria requerir múltiples re-execucions per completar el protocol) i que obté un sistema de coneixement nul de 3 moviments (sense re-execucions). La transformació combina la coneguda tècnica Fiat-Shamir amb diversos missatges intercanviats inicialment. A la part final, ens centrem en els aspectes pràctics de la verificació resistent a la coacció de la intenció del vot emès. En primer lloc, presentem el cas d'un votant limitat computacionalment, que considerem el més realista. Mostrem que fins i tot un votant amb limitacions computacionals pot gaudir d'una verificació resistent a la coacció de la intenció del vot emès, però requereix l'ajuda d'un dispositiu senzill per a la generació d’una prova. A més, demostrem que la nostra definició genèrica s'adapta fàcilment a les limitacions del votant. Després d'això, presentem un treball recent que se centra en els casos de coacció extrema basats en mecanismes nous i poc explorats com ara el xifrat amb retard i la cadena de blocs. Mostrem un atac coercitiu avançat a la nostra primera proposta genèrica i descrivim una millora de la segona que redueix el nombre d'interaccions a tres rondes òptimes. Com a resum, comencem estudiant la verificació resistent a la coacció de la intenció del vot emès en entorns criptogràfics estàndard, que dóna lloc a definicions formals i dues solucions pràctiques. Aleshores ens movem al món de la criptografia post-quàntica, on cal un pas addicional per preservar la usabilitat de les dues solucions proposades anteriorment: una transformació genèrica per evitar repeticions del protocol. Després d'això, ens concentrem en un votant computacionalment limitat, que condueix a una altra solució senzilla i mostra l'adaptabilitat de les nostres definicions originals. Finalment, explorem les amenaces de coacció extremes, que donen lloc a un nou atac de coerció a la primera solució i a una actualització de la segona solució.
Ethereum introduced decentralized applications (DApps) to leverage blockchain's potential, distinct from the cryptocurrency buzz dominating discussions. Ethereum offers a robust platform for DApp development, utilizing the Ethereum Virtual Machine (EVM). With increasing smart contract integration, Ethereum's ecosystem strengthens, as these self-executing contracts govern transactions while ensuring consensus among all participants. In democratic societies, the demand for a transparent and secure electronic voting platform is high. Ethereum, with its expansive network, is an ideal choice for such projects. Our implementation focuses on a decentralized, blockchain-based voting system. Multiple nodes collectively store voting data, ensuring redundancy. In case of node issues, users can access their data from operational nodes, enhancing system reliability. This contrasts with traditional centralized servers, prone to hacking or failures that compromise data accessibility and integrity. Blockchain's immutable data storage prevents tampering, as nodes independently verify each block using cryptographic hash codes. Unauthorized changes trigger immediate alerts, enhancing security and trust in the voting system.
Tor is now using a centralized measurement system called Sbws to measure the bandwidth of relays to guide clients in selecting relays to balance traffic. Sbws has been proven to be vulnerable to multiple attacks because of the centralized structure and exposed measurements. We present SmartMeasurer, a secure and decentralized system for bandwidth measurement. Combining smart contract, Oracle Chainlink and ECC technology, we achieve decentralization while hiding the measurement circuits among the general circuits by exploiting the dual identity of randomly dynamic measurers and guards. We analyze the security of our system and demonstrate that it defends against three types of attacks. Our experiments on both private and public Tor networks show that our system is decentralized while keeping the error and the average of our measurements converges to a small interval of 0.30 Mbps. Compared to other existing methods, our system reduces trust assumptions and the costs of using smart contract, and enhances the practical feasibility of the solution.
Open access
Internet Traffic Analysis and Secure E-voting
Cryptography and Data Security
Physical Unclonable Functions (PUFs) and Hardware Security
The use of smart contracts enhances the capabilities of blockchain-based botnets, allowing for greater information capacity, richer application scenarios, and the deployment of program functions directly on the blockchain. However, smart blockchains offer a better solution for the intelligence of IoT systems, but they also come with some security risks. Botnet is a highly insecure community because it is used to do hazardous things like Distributed Denial of Service (DDoS). It is extremely essential to detect botnets with some useful tools, such as artificial intelligence (AI) algorithms, because these algorithms can assist us to monitor the network automatically. We need to pay the utmost attention to some feature engineering work, as recognition rates of AI models are considerably improved with suitable features. In this article, we propose domain embedding (DE) models to generate low-dimensional features for domains with unsupervised learning algorithms. We also explore some key parameters of the DE model to obtain decent effects on domain features. A modified version of the$k$-means algorithm called extended$k$-means, is used to cluster these domains in certain hubs and botnets that can be found for smart blockchain-based IoT systems. In the experiments, some domain correlation scores can be computed during the DE model, and similar domains have higher correlation scores.
Shalu J. Rajawat, Manju Kaushik, Surendra Kumar Yadav
Decentralized applications (DApps) are digital programs or applications that exist and run on a blockchain or peer-to-peer (P2P) community of computer systems as opposed to a single computer. DApps (additionally called “dapps”) are outside the purview and control of a single authority. DApps—which can be regularly built on the Ethereum platform—may be evolved for a spread of functions along with gaming, finance, and social media. Nowadays security is the major concern while developing any application, and decentralized applications are used in many sectors in order to remove the security issues. So, as a developer, to keep up with the technology, here is a development of this decentralized voting system based on blockchain that will allow the election to be conducted fairly without any security issues exactly as programmed without any possibility of downtime, fraud, censorship, and third-party interference. The motivation behind building this application is that in the current scenario in which necessary things are going online, the elections are also being conducted online but the major issues are tampering of the results which leads to unfair elections. DApps uses smart contracts to completely prevent assigning of duplicate vote. Blockchain technology first emerged for the transactions of cryptocurrency and taking that into account to make an application that conducts fair elections that have no security loopholes with the use of blockchain technology and its distributions. There are already some applications that provide the same functionality, but had not emerged in India until recently. The idea of adapting digital voting systems to make the public election process digitized, cheaper, faster, and easier is a compelling one in modern society with proper security concerns.
The rapid expansion of the Internet of Things (IoT) on a global scale has facilitated the convergence of revolutionary technologies such as artificial intelligence (AI), blockchain, and cloud computing. The integration of these technologies has paved the way for the development of intricate infrastructures, such as smart homes, smart cities, and smart industries, that are capable of delivering advanced solutions and enhancing human living standards. Nevertheless, IoT devices, while providing effective connectivity and convenience, often rely on traditional network interfaces that can be vulnerable to exploitation by adversaries. If not properly secured and updated, these legacy communication protocols and interfaces can expose potential vulnerabilities that attackers may exploit to gain unauthorized access, disrupt operations, or compromise sensitive data. To overcome the security challenges associated with smart home systems, we have devised a robust framework that leverages the capabilities of both AI and blockchain technology. The proposed framework employs a standard dataset for smart home systems, from which we first eliminated the anomalies using an isolation forest (IF) algorithm using random partitioning, path length, anomaly score calculation, and thresholding stages. Next, the dataset is utilized for training classification algorithms, such as K-nearest neighbors (KNN), support vector machine (SVM), linear discriminate analysis (LDA), and quadratic discriminant analysis (QDA) to classify the attack and non-attack data of the smart home system. Further, an interplanetary file system (IPFS) is utilized to store classified data (non-attack data) from classification algorithms to confront data-manipulation attacks. The IPFS acts as an onsite storage system, securely storing non-attack data, and its computed hash is forwarded to the blockchain’s immutable ledger. We evaluated the proposed framework with different performance parameters. These include training accuracy (99.53%) by the KNN classification algorithm and 99.27% by IF for anomaly detection. Further, we used the validation curve, lift curve, execution cost of blockchain transactions, and scalability (86.23%) to showcase the effectiveness of the proposed framework.
Cyber attack detection is the process of detecting and responding to malicious or unauthorized activities in networks, computer systems, and digital environments. The objective is to identify these attacks early, safeguard sensitive data, and minimize the potential damage. An intrusion detection system (IDS) is a cybersecurity tool mainly designed to monitor system activities or network traffic to detect and respond to malicious or suspicious behaviors that may indicate a cyber attack. IDSs that use machine learning (ML) and deep learning (DL) have played a pivotal role in helping organizations identify and respond to security risks in a prompt manner. ML and DL techniques can analyze large amounts of information and detect patterns that may indicate the presence of malicious or cyber attack activities. Therefore, this study focuses on the design of blockchain-assisted hybrid metaheuristics with a machine learning-based cyber attack detection and classification (BHMML-CADC) algorithm. The BHMML-CADC method focuses on the accurate recognition and classification of cyber attacks. Moreover, the BHMML-CADC technique applies Ethereum BC for attack detection. In addition, a hybrid enhanced glowworm swarm optimization (HEGSO) system is utilized for feature selection (FS). Moreover, cyber attacks can be identified with the design of a quasi-recurrent neural network (QRNN) model. Finally, hunter–prey optimization (HPO) algorithm is used for the optimal selection of the QRNN parameters. The experimental outcomes of the BHMML-CADC system were validated on the benchmark BoT-IoT dataset. The wide-ranging simulation analysis illustrates the superior performance of the BHMML-CADC method over other algorithms, with a maximum accuracy of 99.74%.
Розвинені демократичні країни стрімко удосконалюють інфраструктуру систем електораль-ного волевиявлення. Технологія блокчейн швидко заполонила дефіцит інновацій в різноманітних сферах людської діяльності. У системи підтримки виборчого процесу також поступово впроваджуються концепції децентралізованого реєстру зберігання голосів та виключення із парадигми голосування третіх зацікавлених осіб. Від третіх осіб, які зазвичай є фальсифікаторами голосів, ніяк не можна було позбутись. Із появою блокчейнів така можливість стає реальністю. Об’єктом дослідження є процес електронного голосування. Предметом дослідження є системи електронного голосування на децентралізованих реєстрах типу блокчейн. Метою роботи є проведення оглядового дослідження існуючих систем електронного голосування на найбільш вживаних, поширених і надійних блокчейнах Bitcoin та Ethereum. Серед досліджених блокчейн-рішень електронного голосування, нажаль, жодне не впроваджено на загальнонаціональному рівні. У майбутніх дослідженнях планується пошук систем електронного голосування на новітніх блокчейнах, зокрема на блокчейні Near Protocol.
Due to the modern relevance of blockchain technology, smart contracts present both substantial risks and benefits. Vulnerabilities within them can trigger a cascade of consequences, resulting in significant losses. Many current papers primarily focus on classifying smart contracts for malicious intent, often relying on limited contract characteristics, such as bytecode or opcode. This paper proposes a novel, two-layered framework: 1) classifying and 2) directly repairing malicious contracts. Slither’s vulnerability report is combined with source code and passed through a pre-trained RandomForestClassifier (RFC) and Large Language Models (LLMs), classifying and repairing each suggested vulnerability. Experiments demonstrate the effectiveness of fine-tuned and prompt-engineered LLMs. The smart contract repair models, built from pre-trained GPT-3.5-Turbo and fine-tuned Llama-2-7B models, reduced the overall vulnerability count by 97.5% and 96.7% respectively. A manual inspection of repaired contracts shows that all retain functionality, indicating that the proposed method is appropriate for automatic batch classification and repair of vulnerabilities in smart contracts.