To address the challenge of balancing privacy protection with regulatory oversight in blockchain transactions, we propose a regulatable privacy protection scheme for blockchain transactions. Our scheme utilizes probabilistic public-key encryption to obscure the true identities of blockchain transaction participants. By integrating commitment schemes and zero-knowledge proof techniques with deep learning graph neural network technology, it provides privacy protection and regulatory analysis of blockchain transaction data. This approach not only prevents the leakage of sensitive transaction information, but also achieves regulatory capabilities at both macro and micro levels, ensuring the verification of the legality of transactions. By adopting an identity-based encryption system, regulatory bodies can conduct personalized supervision of blockchain transactions without storing users’ actual identities and key data, significantly reducing storage computation and key management burdens. Our scheme is independent of any particular consensus mechanism and can be applied to current blockchain technologies. Simulation experiments and complexity analysis demonstrate the practicality of the scheme.
Agus Tedyyana, Osman Ghazali, Tryo Asnafi, Onno W. Purbo · 6 authors
This study introduces a novel e-voting system utilizing blockchain technology to address the challenges inherent to traditional voting methods. Traditional systems often suffer from inaccuracies, susceptibility to manipulation, and elevated costs. Conversely, while e-voting shows potential, issues related to transparency and security have curbed its full adoption. Our research overcomes these hurdles by integrating a system developed through the Kanban methodology, with the blockchain serving as the central repository for all election data. This approach boosts transparency and security, using public-private key pairs for each transaction, and simplifying blockchain access. Organizers initiate elections and define eligible voters; this data is then securely moved to the Ethereum blockchain. Voters can effortlessly use the system, casting votes and accessing real-time, unalterable results. Various communication protocols ensure system stability, with simulated cyberattacks showcasing its security. After exhaustive testing and refinement, areas for further enhancement have been identified. This innovative system offers unmatched transparency and trust in the voting process, marking a considerable leap for trustworthy elections, especially in small to medium-sized settings.
In an era marked by technological advancements and a growing demand for secure and transparent electoral processes, the integration of blockchain technology into online voting systems has emerged as a promising solution.This research paper presents a comprehensive exploration of the design, implementation, and implications of an online voting system built upon blockchain technology.Through an in-depth analysis of existing electronic voting challenges and the potential of blockchain, this paper demonstrates how the decentralized, immutable, and transparent nature of blockchain addresses critical concerns such as security, voter privacy, and trust in electoral outcomes.The paper delves into the core architecture of the proposed system, highlighting the role of smart contracts in automating voting processes while ensuring authenticity and verifiability.Security and transparency are examined in detail, showcasing the cryptographic measures that safeguard voter information and prevent fraudulent activities.The challenges of voter authentication, scalability, and accessibility are discussed, along with potential solutions to overcome these obstacles.Drawing on case studies of real-world implementations, the paper offers insights into the successes, challenges, and lessons learned from adopting blockchain-based online voting systems.Legal and ethical considerations are also explored, emphasizing the need for aligning technological innovations with legal frameworks and ethical standards.Finally, the research paper contemplates the future of blockchain-powered online voting, envisioning how emerging technologies such as biometrics, artificial intelligence, and zero-knowledge proofs could further enhance the security and inclusivity of electoral processes.Overall, this paper underscores the transformative potential of blockchain in revolutionizing online voting, fostering a more resilient and democratic electoral landscape.
The office attendance system has shifted from using physical forms to digital inputs to minimize data errors and data loss when taking attendance. Unfortunately, digital systems generally still use traditional databases where the admin's role is crucial, and there is potential for fraud (e.g., admitting attendance of a non-attending person or manipulating a targeted person’s log due to personal grudges, competition, or other reasons) if the admin is dishonest. In this paper, we propose Absenin, a blockchain-based office attendance system, which replaces the role of traditional databases with blockchain and smart contracts to make it secure from malicious admins and fair for other participants. We create an Attendance Smart Contract that will run on the Ethereum blockchain. Admins and employees will interact with this smart contract to carry out attendance system operations. Absenin is also designed to have real-time attendance data, but the attendance machine does not need to be connected to the Internet, which is a unique feature of our system that no previous works have attempted. Despite using blockchain and smart contracts, our evaluation results show that Absenin is able to produce relatively small processing delays, and gas usage on the blockchain is still far below the gas limit of the Ethereum mainnet. Therefore, we can assure that the system is feasible and can be applied to organizations with a scale of thousands, tens, or hundreds of thousands of employees.
Priced oblivious transfer (POT) is a cryptographic protocol designed for privacy-preserving e-commerce of digital content. It involves two parties: the merchant, who provides a set of priced items as input, and a customer, who acquires one of them. After the protocol has run, the customer obtains the item they chose, while the merchant cannot determine which one. Moreover, the protocol guarantees that the customer gets the content only if they have paid the price established by the merchant. In a recent paper, the authors proposed a POT system where the payments employed e-coin transactions. The strong point of the proposal was the absence of zero-knowledge proofs required in preceding systems to guarantee the correctness of payments. In this paper, we propose a novel e-coin-based POT system with a fast item retrieval procedure whose running time does not depend on the number of items for sale. This is an improvement over the aforementioned existing proposal whose execution time becomes prohibitively long when the catalog is extensive. The use of zero-knowledge proofs is neither required.
Se Elnour, William J. Buchanan, Paul Keating, Mwrwan Abubakar · 5 authors
The vSPACE experimental proof-of-concept (PoC) on the TrueElect[Anon][Creds] protocol presents a novel approach to secure, private, and scalable elections, extending the TrueElect and ElectAnon protocols with the integration of AnonCreds SSI (Self-Sovereign Identity). Such a protocol PoC is situated within a Zero-Trust Architecture (ZTA) and leverages confidential computing, continuous authentication, multi-party computation (MPC), and well-architected framework (WAF) principles to address the challenges of cybersecurity, privacy, and trust over IP (ToIP) protection. Employing a Kubernetes confidential cluster within an Enterprise-Scale Landing Zone (ESLZ), vSPACE integrates Distributed Ledger Technology (DLT) for immutable and certifiable audit trails. The Infrastructure as Code (IaC) model ensures rapid deployment, consistent management, and adherence to security standards, making vSPACE a future-proof solution for digital voting systems.
With the emergence of blockchain technology, the cryptocurrency market has experienced significant growth in recent years, simultaneously fostering environments conducive to cybercrimes such as phishing scams. Phishing scams on blockchain platforms like Ethereum have become a grave economic threat. Consequently, there is a pressing demand for effective detection mechanisms for these phishing activities to establish a secure financial transaction environment. However, existing methods typically utilize only the most recent transaction record when constructing features, resulting in the loss of vast amounts of transaction data and failing to adequately reflect the characteristics of nodes. Addressing this need, this study introduces a multiscale feature fusion approach integrated with a graph convolutional network model to detect phishing scams on Ethereum. A node basic feature set comprising 12 features is initially designed based on the Ethereum transaction dataset in the basic feature module. Subsequently, in the edge embedding representation module, all transaction times and amounts between two nodes are sorted, and a gate recurrent unit (GRU) neural network is employed to capture the temporal features within this transaction sequence, generating a fixed-length edge embedding representation from variable-length input. In the time trading feature module, attention weights are allocated to all embedding representations surrounding a node, aggregating the edge embedding representations and structural relationships into the node. Finally, combining basic and time trading features of the node, graph convolutional networks (GCNs), SAGEConv, and graph attention networks (GATs) are utilized to classify phishing nodes. The performance of these three graph convolution-based deep learning models is validated on a real Ethereum phishing scam dataset, demonstrating commendable efficiency. Among these, SAGEConv achieves an F1-score of 0.958, an AUC-ROC value of 0.956, and an AUC-PR value of 0.949, outperforming existing methods and baseline models.
Koteswara Rao Kodepogu, Mudigonda Dharmateja, J. M. S. V. Ravi Kumar, Muraboina Hari Pavan Gopi Krishna · 5 authors
In this exploration, our paper delves into the intricate implementation of robust authentication and transaction management within educational blockchain systems.Our project showcases a commitment to privacy and integrity, safeguarding interactions through advanced cryptographic techniques.The multifaceted capabilities of blockchain technology are showcased through the seamless maintenance of student records, the facilitation of secure voting processes, and the optimization of token transfers, collectively contributing to an ecosystem characterized by enhanced security, transparency, and efficiency.Our study uncovers insights into blockchain's transformative potential in education, redefining paradigms by introducing security measures and transparency to student-admin interactions.We highlight the successful implementation of blockchainbased authentication and transaction management systems, leading to enhanced educational processes.Additionally, we briefly outline our research design and methodology, emphasizing the rigorous approach to exploring blockchain applications.
Patikiri Arachchige Don Shehan Nilmantha Wijesekara
Access Control (AC) in networking attempts to make sure that only authorized devices perform actions formed upon privileges defined for them with a view to prevent malicious users' entry and interaction in the communication grid. Blockchain solutions contain an arrangement of related blocks that naturally safeguards the trustworthiness, defending the incontestability, defend masked-identity of its transactions/transfers due to scattered consensus strategies and cryptographic solutions. Our survey comprehensively reviews BC-formed AC in broad scope of networking considering AC techniques while breaking down into 4 propositions and assessing them in terms of blockchain roles, AC technique and approach, network elements, and rest. We stockpiled a primary sample of 79 bibliographic references by weeding out them for screening criteria sought from scientific information reservoirs exploiting a qualitative and extensive strategy. Formed upon this survey, in blockchain-formed AC, blockchain can be exploited as an AC manager to administrate network devices and access information, implement automatic AC by means of smart contracts, secure storage of AC related data to reinforce overall AC security, and for safe data exchanging in the operation of AC. Minute assessment highlights that from blockchain-formed AC, 52.5% provide AC using blockchain itself or using smart contracts, 92.5% exploit sequential blockchain, 35% exploit PBFT consensus, provide 100% fine-grained and host-formed AC, 85% decentralized AC, 87.5% have single-factor authentication, 92.5% provide dynamic AC, and 45% have opted for IoT. Finally, we evaluate the chances and difficulties of the principle of blockchain-formed AC and then giving recommended actions to beat them.
Electronic voting system is the process of polling votes and counting votes. In most of the countries voting may now be done electronically, there are still several difficulties involved, including the expense of paper, how ballots are organized, the possibility of varying results when tallying the votes, and others. Duplicate votes pose a significant concern as they can be fraudulently cast by individuals. To focus on this issue, Distributed Ledger Technology (DLT) is employed to enhance the voting procedure in a secured manner. A directed acyclic graph is used by the Internet of Things Application (IOTA), a promising distributed ledger system. Faster transaction confirmation, high scalability and zero transaction fees are achieved via the Directed Acyclic Graph structure. In both IOTA tangle and blockchain technology, the public cast duplicate votes. The unauthorized user can create duplicate votes in the blockchain as well as IOTA tangle. This can be focused in this proposed method. The double spending problem can be solved by using Crow Search Algorithm (CSA). This Optimization problem produces an improved result for resolving double spending in e-voting systems.
Open access
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
In a democratic regime, voting is crucial to making collective decisions. Unfortunately, although this activity has great significance and value, little effort has been made to improve the way we vote. Paper ballots are still the most used method, although this method is relatively simple, brings many inconveniences, and represents a contradiction to the modern world and its advances. This paper mostly focuses on a review study of blockchain-based voting systems. It aims at identifying the strategies and the guidelines as well as provides a comprehensive end-to-end electronic voting system based on blockchain, with the help of cryptographic techniques such as zero-knowledge proofs to improve privacy. The novelty of this paper is that we tackle the limitations of electronic voting systems found in the literature, including cost, identity management, and scalability problems. Our purpose is to provide key elements for organizations on how to design their proper electronic voting system based on blockchain technology.
Open access
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
ABSTRACT Voting has always been a crucial topic of public attention for democratic reasons. The ease of use and low cost are the result of e‐voting being frequently used for such important decision outcomes. However, the tremendous authority and intervening data in current e‐voting systems make it risky and difficult to achieve correct equity and clarity in e‐voting. So, by combining e‐voting with blockchain technology, these issues can be resolved while providing reorganization and intervention‐resistant characteristics. A voter's improper manipulation, frequent voting, or non‐party voting, may also undermine fairness. A verifier is therefore required to check the e‐voting mechanism in order to ensure its effectiveness and control the process equality and fairness. In this paper, a Blockchain‐based e‐Voting Mechanism (BVM) is developed for providing the end to end security and fairness for transparent voting. This mechanism also provides a zero‐knowledge proof (ZP) based verifier to inspect the voting procedure against voter's mis‐operations and uses a novel Improved Master‐key Administration (IMA) based public key cryptography to attack prevention. The utilization of blockchain technology ensures transparency, anonymity, confidentiality, authentication, tamper resistance, and a high level of data integrity, making it a promising choice for modernizing and enhancing the electoral process. Also, the performance of BVM has been compared with similar voting mechanisms and analyzed based on time complexity, security analysis, performance factors like delay and throughput, and anti‐attack examination.
Open access
2 source records
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Beulah Jayakumari, S. Lilly Sheeba, Maya Eapen, L. Jani Anbarasi · 7 authors
With the invention of Internet-enabled devices, cloud and blockchain-based technologies, an online voting system can smoothly carry out election processes. During pandemic situations, citizens tend to develop panic about mass gatherings, which may influence the decrease in the number of votes. This urges a reliable, flexible, transparent, secure, and cost-effective voting system. The proposed online voting system using cloud-based hybrid blockchain technology eradicates the flaws that persist in the existing voting system, and it is carried out in three phases: the registration phase, vote casting phase and vote counting phase. A timestamp-based authentication protocol with digital signature validates voters and candidates during the registration and vote casting phases. Using smart contracts, third-party interventions are eliminated, and the transactions are secured in the blockchain network. Finally, to provide accurate voting results, the practical Byzantine fault tolerance (PBFT) consensus mechanism is adopted to ensure that the vote has not been modified or corrupted. Hence, the overall performance of the proposed system is significantly better than that of the existing system. Further performance was analyzed based on authentication delay, vote alteration, response time, and latency.
Payment channels serve as an effective solution to the scalability problem of cryptocurrencies, which significantly increase transaction rates by allowing users to conduct large-scale offline transactions off-chain without posting everything to the blockchain. However, the existing payment channels lack privacy protection for the transaction amount and the linking relationship between the two parties to the transaction. Therefore, in order to address the scalability and privacy issues of cryptocurrencies such as Bitcoin, this paper proposes a zk-SNARKs-based anonymous payment channel (zk-APC), which supports an unlimited number of off-chain payments between the payer and the payee and protects the privacy of the participants. Specifically, the proposed scheme achieves relational anonymity and amount privacy for both on-chain and off-chain transactions in the payment channel through utilizing zero-knowledge proof (zk-SNARKs) and commitment schemes. This paper proves that the proposed method is more effective than similar schemes through a performance evaluation.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Abstract Due to the anonymous and contract transfer nature of blockchain cryptocurrencies, they are susceptible to fraudulent incidents such as phishing. This poses a threat to the property security of users and hinders the healthy development of the entire blockchain community. While numerous studies have been conducted on identifying cryptocurrency phishing users, there is a lack of research that integrates class imbalance and transaction time characteristics. This paper introduces a novel graph neural network-based account identification model called CT-GCN+, which utilizes blockchain cryptocurrency phishing data. It incorporates an imbalanced data processing module for graphs to consider cryptocurrency transaction time. The model initially extracts time characteristics from the transaction graph using LSTM and Attention mechanisms. These time characteristics are then fused with underlying features, which are subsequently inputted into a combined SMOTE and GCN model for phishing user classification. Experimental results demonstrate that the CT-GCN+ model achieves a phishing user identification accuracy of 97.22% and a phishing user identification area under the curve of 96.67%. This paper presents a valuable approach to phishing detection research within the blockchain and cryptocurrency ecosystems.
Elizabeth M. Johnson, Victoria Grace Wilson, W. Thompson
Blockchain technology presents a decentralized and transparent solution for secure voting systems. This paper provides a comparative analysis of consensus protocols, such as Proof of Work (PoW), Proof of Stake (PoS), and Delegated Proof of Stake (DPoS), to evaluate their effectiveness in a secure voting environment. Results show that PoS offers optimal security with reduced energy consumption, making it suitable for public elections.
Voting aims to provide the best decision or select the most selected option for the largest group of voters. Malicious parties gaining access, and otherwise tampering with election results, or the votes make this effort counterproductive. To alleviate this, this study examined the introduction of blockchain. The transparent and immutable nature of the blockchain makes this data impossible to alter and allows the election results to be transparent. To further increase the transparency of the system while keeping voters anonymous, a biometric based cryptography was introduced. The biometric was introduced as the source for the private key for each voter while a public was generated to act as the identity of the voter. The biometric trait of each individual is unique and cannot be forged, hence the identity of the voter is secured. The public key available cannot be traced by to the private key, hence, identity of the voter is anonymous. The system showed an encouraging performance after testing.
Open access
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
As a decentralized network infrastructure, the data sent to the blockchain are public and temper-evident. The cover of massive normal transactions in a blockchain network is ideal for constructing a stable and reliable covert channel to achieve one-to-many group covert communication. Existing blockchain-based covert communication schemes face challenges in balancing concealment, embedding rate and filtering efficiency, making them unsuitable for direct extension to group scenarios. Adopting a key-leakage scheme can increase the channel capacity while maintaining high concealment from external adversaries. However, it will also expose more knowledge to the receiver. A malicious receiver has the ability to steal a sender’s identity or replay historical transactions to control the entire channel. In this paper, we define the capabilities of malicious receivers in blockchain-based group covert communication scenarios and propose a group covert communication scheme resistant to transaction forgery attacks. Theoretical analysis and experiments prove that our covert transactions do not have any transaction correlativity, ensuring the unique authenticity of the sender’s identity while maintaining supreme concealment compared with the existing schemes. The precision and recall of machine learning detection results can reach 0.57–0.62 (0.5 is the ideal value).
Open access
Internet Traffic Analysis and Secure E-voting
Adversarial Robustness in Machine Learning
Advanced Steganography and Watermarking Techniques
Abstract Timed-release encryption (TRE) is a cryptographic primitive that can control the decryption time and has significant application value in time-sensitive scenarios. To solve the reliability issue of nodes in existing TRE anonymous interaction schemes, we propose a blockchain-based TRE protocol for anonymous query time trapdoors. In our protocol, the recipient divides the encrypted trapdoor request information into n ciphertext fragments using secret sharing technology near the decryption time, and employs the idea of onion routing to perform layer-by-layer encryption, creating onion-type data transmitted through middlemen selected from the smart contract. After receiving the ciphertext fragments, the time server integrates them to obtain the trapdoor request information and returns the corresponding time trapdoor to the recipient. This allows the recipient to query any time trapdoor anonymously. Our protocol provides a normative design for the smart contract and specific constraints on the participants’ behavior. Compared with the related anonymous query trapdoor schemes, our protocol improves the probability of successful queries. Security analysis shows that our protocol can resist release-ahead attack, interruption attack, eavesdropping attack, and replacement attack. Performance analysis shows that our protocol outperforms related protocols regarding anonymity, efficiency, and flexibility, achieving highly efficient anonymous interactions. Finally, we conducted an experiment in the Ethereum Rinkeby test network. For the settings of ciphertext fragment number $$n=3$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>3</mml:mn></mml:mrow></mml:math> and ciphertext fragment threshold $$t=2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>t</mml:mi><mml:mo>=</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:math> , the gas consumption for a user to execute the contract was $5.66, which was higher than the contract cost of related schemes, but the contract execution cost was within an acceptable range.
Wisam Ali Mahmood, Jumana Waleed, Ayad R. Abbas, Haya Alaskar · 6 authors
Electronic voting systems have often associated with issues of security, transparency, and limited accessibility, particularly for people with disability, elderly, and visually impaired voters. These systems, impeded by complex authentication procedures and non-intuitive user interfaces, have also struggled to ensure voter trust and widespread participation. To address these issues, this paper presents a new electronic voting system that combines the gesture recognition with blockchain technology. The proposed system has two phases, the first one is a user identification phase using a pre-trained dataset based on both cvzone and Dlib tools for face and finger identifications. Gestures from the face and hands, such as eyebrow and nose movements are used as authentication mechanisms as well as a mean of input into the system. The second is a voting process phase which uses the blockchain technology. This new approach strengthens the security and transparency of voting through a tamper-proof ledger provided by the blockchain technology, as well as enhances considerably the inclusiveness and also user friendliness. Real time simulations show that the user interaction times for different age groups ranges between (24.3s to 29.7s) and the accuracy rate for gesture types varies between (88.7s to 92.5s). Moreover, the simulation results indicated that real time voting using our proposed system generated 100% precision and 99% recall. Our system showed high accuracy in gesture recognition and profound security when using Equal Error Rate quality measure. Different to other approaches, the interface of our proposed system, designed for a wide audience of users, greatly simplifies the voting process.
Voice over Internet Protocol (VoIP) networks are vulnerable to caller-ID (caller-identification) spoofing attacks due to the open nature of Session Initiation Protocol (SIP) signaling. Caller-ID spoofing is a critical security threat in modern telecommunication systems, allowing attackers to impersonate legitimate callers and gain access to sensitive information. While these attacks pose a significant threat to the telecom and financial industries, the existing solutions are limited to only closed-circuit options for subscribers of the same service provider. In this paper, we present a novel blockchain-based solution to effectively prevent caller-ID spoofing attacks in real time. Our approach employs a low-latency consensus algorithm to manage and verify end-to-end the caller-ID information of Internet Service Providers (ISPs) and institutions. We propose a two-step verification process, in which the accuracy and integrity of Automatic Number Identification (ANI) information is verified at different stages of the call. The proposed solution initiates a renewal of the ISP registration on every caller-ID change, making it unaffected by unusual situations such as roaming, the use of an IP-PBX (Internet Protocol Private Branch Exchange), or the use of a VPN (Virtual Private Network). We also discuss the proposed solution’s feasibility and potential deployment issues, including its integration into existing RFC (Request for Comments) efforts and the necessary regulations for service providers to demonstrate compliance. Furthermore, we address future research directions, such as handling complex call scenarios such as call forwarding and teleconference calls. Our approach not only improves the security of telecommunication systems but also provides an efficient and scalable solution to prevent caller-ID spoofing attacks.
The coming 6G wireless network is poised to achieve unprecedented data rates, latency, and integration with newer technologies like AI and IoE. On the other hand, along with this kind of growth in the AI domain and the large-scale connectivity in 6G. It is also going to raise many security concerns at the level of intrusion detection and prevention. For intrusion detection, centralized approaches won’t be able to work effectively, therefore there is an utmost need to design decentralized and privacy-preserving solutions. In this work, we propose a novel secure gradients exchange algorithm for distributed intrusion detection in 6G networks. Our method is designed to take into account the use of Federated Learning with secure multi-party computation and blockchain technology. This way ensures that the collaborating parties are able to conduct the training of intrusion detection models in a secure and collaborative manner by retaining privacy in the data. Gradient compression and adaptive secure aggregation strategies are used to further optimize communication overhead and computational complexity. Therefore, our design works in a robust and efficient manner with the high data rates and huge connectivity that 6G networks will provide. To achieve our goal, experiments using the CICIoT2023 dataset were performed, and results showed that our federated learning-based hybrid model composed of CNN1D and a multi-head attention mechanism outperformed other well-known deep learning models in terms of performance. It achieved the highest average accuracy with 79.92%, the highest average detection rate with 77.41%, and a low false alarm rate with 2.55%.
Minjae Seo, Jaehan Kim, Myoungsung You, Seungwon Shin · 5 authors
Blockchain technology has ushered in a transformative paradigm of decentralized and transparent systems, offering innovative solutions across diverse sectors. While these systems strive for unparalleled transparency and trustlessness in a fully distributed framework, permissionless blockchains, such as Bitcoin and Ethereum, encounter vulnerabilities due to their intrinsically public nature. Addressing these vulnerabilities, the emergence of permissioned blockchains presents a fortified alternative, incorporating rigorous access controls and authentication protocols to ensure participation exclusivity and transaction confidentiality. Nevertheless, a keen observation reveals that, despite encryption, the operational traffic within these blockchains manifests distinct time-series patterns and operational relations during sensitive data exchanges. Such patterns hold the potential to inadvertently expose critical details about the network, encompassing its topology and the operational dependencies among nodes. In light of this revelation, we introduce a pioneering blockchain fingerprinting mechanism, denoted as gShock. This system meticulously analyzes periodic patterns and the context of operational relations from the collected blockchain network traffic. It employs a Graph Neural Network (GNN)-based model, adept at capturing the intricate characteristics innate to specialized blockchain operations. Through empirical experiments conducted in a realistic permissioned blockchain environment, comprising various nodes, we ascertain that gShock demonstrates a remarkable proficiency in classifying blockchain operational traffic with an F1-score of$\geq 96$% and identifying individual dependencies with a macro F1-score of$\geq 93$%.
Open access
Advanced Steganography and Watermarking Techniques