Qi Liang, Ning Shi, Yu‐an Tan, Chunying Li · 5 authors
With the widespread adoption of blockchain technology, its public ledger characteristic enhances transaction transparency but also amplifies the risk of privacy breaches. Attackers can infer users’ real identities and behaviors by analyzing public transaction patterns and address relationships, posing a severe threat to users’ privacy and security, and thus hindering further advancements in blockchain applications. To address this challenge, covert communication has emerged as an effective strategy for safeguarding the privacy of blockchain users and preventing information leakage. But existing blockchain-based covert communication schemes rely solely on the immutability of blockchain itself for robustness and suffer from low transmission efficiency. To tackle these issues, this paper proposes a stealthy communication model with blockchain smart contract for bidding systems. The model initiates by preprocessing sensitive information using a secret-sharing algorithm-the Shamir (t, n) threshold scheme-and subsequently embeds this information into bidding amounts, facilitating the covert transfer of sensitive data. We implemented and deployed this model on the Ethereum platform and conducted comprehensive performance evaluations. To assess the stealthiness of our approach, we employed a suite of statistical tests including the CDF, the Kolmogorov–Smirnov test, Welch’s t-test and K–L divergence. These analyses confirmed that amounts carrying concealed information were statistically indistinguishable from regular transactions, thus validating the effectiveness of our solution in maintaining the anonymity and confidentiality of information transmission within the blockchain ecosystem.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Abstract Online voting is gaining traction in contemporary society to reduce costs and boost voter turnout, allowing individuals to cast their ballots from anywhere with an internet connection. This innovation is cautiously met due to the inherent security risks, where a single vulnerability can lead to widespread vote manipulation. Blockchain technology has emerged as a promising solution to address these concerns and create a trustworthy electoral process. Blockchain offers a decentralized network of nodes that enhances transparency, security, and verifiability. Its distributed ledger and non‐repudiation features make it a compelling alternative to traditional electronic voting systems, ensuring the integrity of elections. To further bolster the security of online voting, we propose DemocracyGuard platform on the Ethereum blockchain, which incorporates facial recognition technology to authenticate voters. By leveraging these advancements, DemocracyGuard aims to provide a secure and resilient platform for online voting, paving the way for its broader adoption and revolutionizing the electoral landscape.
The architecture of SDN can be roughly divided into the application layer, the control plane, and the data plane. Applications at the application layer drive the controllers of the control plane through the northbound interface (NBI) to manage the network. Traditionally, there is usually only one controller to fulfill the management. However, in SD-WAN, the number of controllers in the control plane is no longer unique and may belong to different branches. For these distributed controllers to collaborate securely and effectively, an access control mechanism adapted to the distributed network environment is required. The network structure of SD-WAN is more complex and its network scale is larger than traditional SDN, which also puts forward new requirements for the design of access control mechanisms. Besides, in other scenarios such as the polymorphic network, multiple controllers are also required to achieve high availability and redundancy, which also brings in the access control issue among controllers. Attribute-based access control (ABAC) is a potential solution, which can provide higher fine-grained access control functions than traditional technologies such as role-based access control (RBAC), discretionary access control (DAC), etc. In addition, the blockchain can provide a practical environment for operating a decentralized and secure access control mechanism. Based on the combination of these two technologies, we designed and implemented a distributed access control mechanism using smart contracts, which is named DABS. Experimental results show that DABS is able to support the role of access control, whose performance and scalability are sufficient for the SD-WAN scenario.
Lukas Ingmarsson, Karl Duckert Karlsson, Niklas Carlsson
Bitcoin and the Dark Web present an interesting synergy that enables both legitimate anonymity and illicit activities, making it an important landscape to understand, especially as the Dark Web, with its hidden services, relies heavily on Bitcoin as a pseudonymous currency for transactions. However, a lack of scalable tools and timely datasets has limited systematic analysis of this ecosystem. To address this gap, we introduce Venom, a scalable framework for mapping Bitcoin activity on the Dark Web. Venom integrates multithreaded crawling, data extraction, and dataset generation, resulting in a comprehensive resource that allows us to easily collect snapshots of over 177,000 onion sites in roughly 24 hours. With the paper, we share both the tool and an example snapshot containing both per-site metadata and Bitcoin transaction data. Preliminary analysis reveals concentrated activity among key players and widespread content mirroring, offering new insights into the Dark Web's economic structure. Venom provides a critical resource for advancing research and monitoring in this domain.
Dingde Jiang, Zhihao Wang, Ye Wang, Lizhuang Tan · 6 authors
Federated learning (FL) in Industrial IoT (IIoT) facilitates collaborative model training across distributed edge devices, ensuring data privacy and localized insights without centralized data aggregation. However, the networked parameter sharing mechanism in FL renders it vulnerable to exploitation by man-in-the-middle (MITM) attackers, potentially disrupting the model training process. To mitigate this threat, this article presents a novel blockchain-reinforced FL architecture aimed at enabling cooperative intrusion detection. Initially, FL is leveraged to aggregate all learned information from edge servers, thereby disseminating extracted attack characteristics to all participants through gradient sharing. Subsequently, a blockchain-based parameter verification scheme is introduced to safeguard against tampered local parameters affecting the global model. Clients record model parameters in smart contracts deployed on a private chain, and parameter servers verify parameter confidentiality before aggregation, ensuring only valid parameters are considered. Finally, extensive experiments are conducted using an edge IIoT cybersecurity data set comprising 61 features spanning ten protocol layers and five attacks targeting IIoT connectivity protocols. Simulation results demonstrate that the proposed scheme significantly enhances intrusion detection accuracy, achieving a threefold improvement when two-thirds of federated nodes are subjected to MITM attacks.
Most trust models are identity based, which how-ever are not appropriate to the permissionless peer-to-peer (P2P) networking since anonymity is a built-in property in the cryptocurrency system (e.g., Bitcoin). Hence, there exists an inherent trade-off between anonymity and trust in the context of permissionless P2P networking system. This paper is motivated to propose a keyless authentication based on zero-knowledge proof. With this, peers can authenticate each other without disclosing any sensitive information. To this end, this approach leverages the software-defined networking (SDN) technique to facilitate the zero-knowledge proof so that the peer's link information can be identified while the proving process will never reveal any identity information. Therefore, the challenge-response exchange can prevent Man-in-the-Middle (MITM) attacks with minimal communication overhead. The experimental results built on the prototype show that this approach is efficient.
The inherent anonymity of blockchain technology has made the cryptocurrency sector a breeding ground for a multitude of illicit financial crimes. In the realm of blockchain transaction security, phishing scams are widely considered a highly severe form of deceit, leading to significant economic losses. This paper provides an overview of past research findings on methods for detecting phishing scam in blockchain networks. Extending graph neural network approaches to detect phishing scam in blockchain networks will be of utmost importance. Graph neural networks yield models with superior generalization capabilities in comparison to conventional approaches. Future research will involve examining high-quality datasets and evaluating the influence of transaction graphs and transaction subgraphs on the effectiveness of detecting phishing scam nodes in categorization. The primary objective is to construct a more resilient model that can achieve the desired detection outcomes and differentiate phishing scams nodes with greater efficiency and precision.
Phishing scams are one of Ethereum's most representative security risks that can defraud many transactions in a short period and severely threaten network security. Existing deep learning-based phishing scam detection methods mainly rely on constructing static transaction graphs which are assumed to be accessible before model training. However, static methods that have a high false positive rate to detect newly generated phishing scams by adding this newly generated data to existing algorithms for execution, due to new accounts and transactions constantly appearing in the real-world Ethereum network. Therefore, this article, for the first time, proposes a novel evolve-based phishing scams detection method (named GrabPhisher) that extracts temporal features of accounts and captures information about the dynamic topology of the graph as it evolves. Specifically, GrabPhisher can build the evolutionary pattern of accounts trading on Ethereum as a diffusion network graph in continuous time. It can continue to capture new transaction features based on existing transactions, which facilitates the identification of phishing accounts. Additionally, we implement GrabPhisher on the real-world Ethereum phishing scams datasets. Extensive experimental results demonstrate that GrabPhisher can effectively extract dynamic temporal features and outperform state-of-the-art methods (95% Recall, and 88% F1-score).
Ethereum is the second-largest blockchain platform, and the financial value of its cryptocurrency has constantly increased. Unfortunately, regulatory challenges have resulted in a surge of scams, particularly phishing, which now accounts for over 50% of fraudulent funds. Therefore, phishing scam issues have become a top priority, thus calling for dynamic early warning and accurate identification to achieve effective market regulation. However, the existing works focusing on phishing address detection do not consider early warnings for phishing scams. Furthermore, these methods depend on static graphs to extract node information and overlook the dynamic evolution process of the Ethereum network. In this article, we propose EWDPS, a novel framework to achieve dynamic early warning and effectively identify phishing scams on Ethereum. Specifically, we create a new network called the dynamic temporal transaction network (DTTN), which effectively models the dynamic temporal evolution of transactions. In DTTN, we propose the concepts of temporal evolution interaction network and account feature interaction network. Next, we design a novel feature extraction module to capture temporal sequential patterns effectively. This module takes full advantage of the dynamic interaction process of node-related transactions. Finally, we innovatively use the extracted account, network, and temporal features to enhance transaction representation in multiple dimensions. Extensive experiments show that our proposed scheme effectively achieves dynamic early warning and accurately identifies phishing scams. EWDPS achieves 92.20% accuracy, 95.90% precision, 96.77% recall, and 96.53% F1-score, and outperforms the state-of-the-art methods in phishing address identification.
In order to achieve zero-knowledge proof (ZKP) in distributed mobile scenarios, we propose a two-stage multi-prover ZKP framework. Our method utilizes secure multi-party computation (MPC), which has advantages such as flexible adaptation, stable performance, and fewer restrictions compared to existing solutions. In addition, based on the properties of cyclic groups, we optimize secure multi-party summation, improving the balance between security and efficiency, as well as transferability of the algorithm.
As the field of Web3 continues its rapid expansion, the security of Web3 authentication, often the gateway to various Web3 applications, becomes increasingly crucial. Despite its widespread use as a login method by numerous Web3 applications, the security risks of Web3 authentication have not received much attention. This paper investigates the vulnerabilities in the Web3 authentication process and proposes a new type of attack, dubbed blind message attacks. In blind message attacks, attackers trick users into blindly signing messages from target applications by exploiting users' inability to verify the source of messages, thereby achieving unauthorized access to the target application. We have developed Web3AuthChecker, a dynamic detection tool that interacts with Web3 authentication-related APIs to identify vulnerabilities. Our evaluation of real-world Web3 applications shows that a staggering 75.8% (22/29) of Web3 authentication deployments are at risk of blind message attacks. In response to this alarming situation, we implemented Web3AuthGuard on the open-source wallet MetaMask to alert users of potential attacks. Our evaluation results show that Web3AuthGuard can successfully raise alerts in 80% of the tested Web3 authentications. We have responsibly reported our findings to vulnerable websites and have been assigned two CVE IDs.
Matthew Marcellino, Arya Wicaksana, Moeljono Widjaja
The advancement of blockchain technology introduces the new concept of electronic voting systems (e-voting) that are fully anonymous, transparent, trustless, and decentralized. The limitation of blockchain-based e-voting systems is the need for initial setup to verify and validate eligible voters. This initial setup requires human intervention, which curbs the full potential and exploitation of blockchain technology. Identity authentication is crucial in voting systems to ensure the eligibility of the voters and the validity of the results. This paper proposes a hybrid approach using ZK-SNARK for identity authentication systems in blockchain-based e-voting. The proposed hybrid approach aims to maintain the benefit of blockchain technology while guaranteeing the eligibility of voters. Both on-chain and off-chain identity authentication modules are designed and developed to balance the trade-off of centralized and decentralized nature for the blockchain-based e-voting systems. The affordability of the proposed system is essential in justifying the approach's feasibility and usability. Voting systems are expected to host thousands to millions of voters, and the cost is one major consideration. The proposed system is deployed in the Ethereum blockchain network, including its sidechain and Layer 2, i.e., Avalanche, Arbitrum One, and Polygon. The gas fee required for the smart contract deployment in Ethereum is USD12.5, while the lowest gas fee is in the Polygon blockchain network for USD0.02.
Open access
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Cryptocurrency is designed for anonymous financial transactions to avoid centralized control, censorship, and regulations. To protect anonymity in the underlying P2P networking, Bitcoin adopts and supports anonymous routing of Tor, I2P, and CJDNS. We analyze the networking performances of these anonymous routing with the focus on their impacts on the blockchain consensus protocol. Compared to non-anonymous routing, anonymous routing adds inherent-by-design latency performance costs due to the additions of the artificial P2P relays. However, we discover that the lack of ecosystem plays an even bigger factor in the performances of the anonymous routing for cryptocurrency blockchain. I2P and CJDNS, both advancing the anonymous routing beyond Tor, in particular lack the ecosystem of sizable networking-peer participation. I2P and CJDNS thus result in the Bitcoin experiencing networking partitioning, which has traditionally been researched and studied in cryptocurrency/blockchain security. We focus on I2P and Tor and compare them with the non-anonymous routing because CJDNS has no active public peers resulting in no connectivity. Tor results in slow propagation while I2P yields soft partition, which is a partition effect long enough to have a substantial impact in the PoW mining. To better study and identify the latency and the ecosystem factors of the cryptocurrency networking and consensus costs, we study the behaviors both in the connection manager (directly involved in the P2P networking) and the address manager (informing the connection manager of the peer selections on the backend). This paper presents our analyses results to inform the state of cryptocurrency blockchain with anonymous routing and discusses future work directions and recommendations to resolve the performance and partition issues.
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
The integration of the blockchain technology into electronic voting systems is an innovation that has gained popularity due to the issues prevailing with the conventional voting methods. The purpose of the work is to provide a thorough explanation of the design and execution of the blockchain-based electronic voting system, emphasizing the system’s significance in revolutionizing global electoral procedures. This study explores various blockchain consensus mechanisms such as Proof of Work (PoW), Proof of Stake (PoS), and Practical Byzantine Fault Tolerance (PBFT), analyzing their relevance in e-voting systems. Additionally, the paper investigates challenges related to scalability, interoperability, and regulatory compliance, proposing innovative solutions to address these complexities.
Online voting is a trend that is gaining momentum in modern society. It has great potential to decrease organizational costs and increase voter turnout. It eliminates the need to print ballot papers or open polling stations—voters can vote from wherever there is an Internet connection. Despite these benefits, online voting solutions are viewed with a great deal of caution because they introduce new threats. A single vulnerability can lead to large-scale manipulations of votes. Electronic voting systems must be legitimate, accurate, safe, and convenient when used for elections. Nonetheless, adoption may be limited by potential problems associated with electronic voting sys-tems . Blockchain technology came into the ground to overcome these issues and offers decentralized nodes for electronic voting and is used to produce electronic voting systems mainly because of their end-to-end verification advantages. This technology is a beautiful replacement for traditional electronic voting solutions with distributed, non-repudiation, and security protection characteristics. The following article gives an overview of electronic voting systems based on blockchain technology. The main goal of this analysis was to examine the current status of blockchain-based voting research and online voting systems and any related difficulties to predict future developments. This study provides a conceptual description of the intended blockchain-based electronic voting application and an introduction to the fundamental structure and characteristics of the blockchain in connection to electronic voting. As a consequence of this study, it was discovered that blockchain systems may help solve some of the issues that now plague election system
Open access
Blockchain Technology Applications and Security
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
The role played by email communication in our lives nowadays has been such a tremendous one especially when it comes to fast exchange of information. Nevertheless, this convenience is marred by the omnipresent threat of email spam that not only disrupts channels of communication but also present serious security and privacy concerns. Traditional models of spam detection which are based on rules or heuristics tend to fail because they do not adapt quickly enough to the new techniques employed by spammers. In response to these challenges, this paper proposes an inventive solution to the problem—integration of blockchain technology into the process of detecting email spams.Email spam is often defined as an unwanted and usually malicious form of correspondence, thus it has continued being a notable cyber security worry. The conventional mechanisms for discovering them are prone to false positives and negatives at times. Additionally, such systems have centralized data which can be interfered with and accessed without permission. Weighing up the limitations inherent in existing methods, this research examines how blockchain may change email spam detection. Keywords— Blockchain technology, ethereum, Spam, email
Digital transformation and new technologies have made people’s lives easier and led to great results in most areas of business and society. Implementing blockchain technology is one of the best tools for establishing sustainable smart cities and societies. In terms of sustainable governance sophisticated and secure voting systems are necessary to achieve high integrity and transparency and null election fraud, and, in environmental sustainability, e-voting systems eliminate the mass waste of paper and transportation gas emissions; namely, e-voting systems are eco-friendly with high democratic outcomes. Blockchain technology can revolutionize e-voting by increasing the security and transparency of the voting process. Integrating artificial intelligence (AI) and machine learning (ML) into blockchain-based e-voting systems further augments their effectiveness. AI algorithms can analyze voting patterns and detect irregularities, supporting the prevention of fraudulent activities and coercion. ML procedures can enhance voter authentication processes, improve accessibility for diverse demographics, and optimize the productivity of blockchain networks during peak voting periods. This study focuses on understanding citizen perceptions of blockchain-based e-voting in a smart city context using the Technology Acceptance Model (TAM). The study’s results indicate that perceived ease of use and perceived usefulness are important factors in determining citizens’ intentions to use blockchain-based e-voting. Furthermore, trust in the technology and perceived security were found to influence the usefulness of blockchain-based e-voting positively. This study provides important insights for policymakers and technologists seeking to promote the adoption of blockchain-based e-voting systems in smart cities. The findings of the research supported the research model with positive results. In conclusion, our research model encourages the adoption of a blockchain-based e-voting system to enhance the future voting environment.
The article delves into the intricate characteristics and security properties of the secp256k1 elliptic curve used for the generation of addresses in the Bitcoin blockchain. The Bitcoin blockchain is a decentralized digital ledger that records all transactions made with Bitcoin cryptocurrency. In this work, the secp256k1 elliptic curve and its parameters and the method of generating private and public keys using random numbers are described. While the private key allows for the signing of transactions to spend Bitcoin, the corresponding public key and address enable others to verify transactions and send funds to that specific address on the blockchain, ensuring security, authenticity, and privacy in the decentralized network. The attacks on the use of secp256k1 for generating the bitcoin addresses like the Brute force attack, twist attack, fault attacks, and side channel attacks in the implementation of the elliptic curve are discussed. By maintaining the security and integrity of secp256k1, we can ensure that cryptographic operations, such as digital signatures and key exchanges, remain uncompromised. If the curve's security were compromised, malicious users could potentially derive private keys from public keys, leading to unauthorized transactions, double-spending, or other malicious activities. The security of implementation can be enhanced by ensuring cryptographic libraries and software implementations that utilize secp256k1 undergo thorough testing and validation to ensure correct and secure operations. The important attacks on blockchain technology like the 51% attack, Sybil attack, Double Spending attack, and Smart Contract vulnerabilities are discussed. Through a comprehensive exploration, readers will gain insights into why this particular elliptic curve was chosen for use in Bitcoin's cryptographic protocols, highlighting its role in ensuring the robustness and integrity of the blockchain ecosystem.
Open access
2 source records
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Due to the large population in places like India, traditional voting systems done in physical mode have many disadvantages like manipulation, security issues, transparency, and privacy issues. So, countries like India need to modernize their voting systems from traditional voting to electronic voting (e-voting). E-voting is an election system that uses electronic means to allow voters to cast votes with privacy, ballot security, and integrity. The e-voting systems use computers connected to the internet. The use of these technologies enables the government to successfully deal with the requirements associated with security, accuracy, scalability, auditability, cost-effectiveness, and sustainability. Based on the new technologies in voting, one recent technology that has attracted many is block chain technology. A block chain is a distributed digital ledger. This ledger is never stored but rather exists on the chain linked to data blocks or nodes connected to each other using encryption and hashing techniques, which makes voting secure. The current trends in block chain technology analysis are being discussed in this paper, highlighting the issues and challenges raised so far in the community regarding the privacy and security of the voter and the vote without putting complete trust in the third-party system.
In this article, we present a cutting-edge private voting system that prioritizes anonymity, using Zero-knowledge Proof (ZKP) technology. Our solution utilizes a Solidity smart contract to manage secure voting on the blockchain. In our method, voters can anonymously submit their votes after successfully verifying their identities using ZKP. This process unfolds in three stages. Initially, voters authenticate their identities on their machines. Once verified, a proof of the successful authentication is generated. This proof, accompanied by the confidential vote, is then sent for verification by a smart contract verifier embedded in the system. The verifier evaluates the proof and proceeds only if the criteria are met. Votes that pass verification are securely stored. Our innovation represents a significant step forward in blockchain-based private voting, promising enhanced transparency, security, and privacy. By blending cryptographic methods with blockchain technology, we offer a strong and trustworthy approach that safeguards the integrity of each voter's input.
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
In a global context characterized by a pressing need to find a solution to the problem of digital copyright protection, buyer-seller watermarking protocols based on asymmetric fingerprinting and adopting a “buyer-friendly” approach have proven effective in addressing such a problem. They can ensure high levels of usability and security. However, they usually resort to trusted third parties (TTPs) to guarantee the protection process, and this is often perceived as a relevant drawback since TTPs may cause conspiracy or collusion problems, besides the fact that they are generally considered as some sort of “big brother”. This paper presents a buyer-seller watermarking protocol that can achieve the right compromise between usability and security without employing a TTP. The protocol is built around previous experiences conducted in the field of protocols based on the buyer-friendly approach. Its peculiarity consists of exploiting smart contracts executed within a blockchain to implement preset and immutable rules that run automatically under specific conditions without control from some kind of central authority. The result is a simple, usable, and secure watermarking protocol able to do without TTPs.
Open access
Advanced Steganography and Watermarking Techniques
Aulia Arif Wardana, Grzegorz Kołaczek, Parman Sukarno
This research introduces a comprehensive collaborative intrusion detection system (CIDS) framework aimed at bolstering the security of Internet of Things (IoT) environments by synergistically integrating lightweight architecture, trust management, and privacy-preserving mechanisms. The proposed hierarchical architecture spans edge, fog, and cloud layers, ensuring efficient and scalable collaborative intrusion detection. Trustworthiness is established through the incorporation of distributed ledger technology (DLT), leveraging blockchain frameworks to enhance the reliability and transparency of communication among IoT devices. Furthermore, the research adopts federated learning (FL) techniques to address privacy concerns, allowing devices to collaboratively learn from decentralized data sources while preserving individual data privacy. Validation of the proposed approach is conducted using the CICIoT2023 dataset, demonstrating its effectiveness in enhancing the security posture of IoT ecosystems. This research contributes to the advancement of secure and resilient IoT infrastructures, addressing the imperative need for lightweight, trust-managing, and privacy-preserving solutions in the face of evolving cybersecurity challenges. According to our experiments, the proposed model achieved an average accuracy of 97.65%, precision of 97.65%, recall of 100%, and F1-score of 98.81% when detecting various attacks on IoT systems with heterogeneous devices and networks. The system is a lightweight system when compared with traditional intrusion detection that uses centralized learning in terms of network latency and memory consumption. The proposed system shows trust and can keep private data in an IoT environment.
Jesús García-Rodríguez, Stephan Krenn, Jorge Bernal Bernabé, Antonio Skármeta
The increasing user awareness and regulatory framework (e.g., GDPR, eIDAS2) have contributed to considering data minimization and privacy-by-design as central guiding principles for new systems. Among others, this has led to a paradigm shift towards Self-Sovereign Identity solutions to put the user in full control over their data. Despite the promising landscape, privacy-preserving Attribute-Based Credentials (p-ABC) have not been widely adopted, mainly due to the lack of secure, flexible and efficient implementations that cover the basic and advanced needs in p-ABC systems. In this work, we tackle this gap by developing an improved zero-knowledge showing protocol of a distributed p-ABC scheme based on Pointcheval-Sanders Multi-Signatures to allow for modular extensions through commit-and-prove techniques. We use it to implement a flexible p-ABC system with decentralized issuance that, apart from the basic notions of p-ABCs, covers range proofs, pseudonyms, inspection and revocation. Lastly, we thoroughly evaluate the performance of the system under different testbed conditions, showing a significant efficiency improvement over previous implementations.