In the rapidly expanding field of the Internet of Things, ensuring secure and efficient communication between IoT devices and servers is crucial. This paper henceforth designs a lightweight authentication system under the Zero Knowledge Proof (ZKP) protocol, utilizing the HMAC hashing algorithm for the improvement of security measures put in place. This system is designed to enable the authentication of IoT devices without sending their actual password, thus avoiding risks due to password interception at the point of authentication. For instance, if using the phrase "God is great" as the password, one can get it hashed into HMAC with this method and still be assured that it is secure even if proof is intercepted. Simulations in the simulator shall evaluate the system’s effectiveness and performance. Performance metrics include accuracy, response time, memory consumption, latency, and throughput. The presented results intend to serve lightweight device authentication mechanisms for IoT devices such that the trustworthiness of IoT devices is achieved without hampering their performance. The presented results are also shown to outperform conventional methods.
User Authentication and Security Systems
Advanced Malware Detection Techniques
Advanced Steganography and Watermarking Techniques
This research paper explores the CONIKS key management system’s security and efficiency, a system designed to ensure transparency and privacy in cryptographic operations. We conducted a comprehensive analysis of the underlying mathematical principles, focusing on cryptographic hash functions and digital signature schemes, and their implementation in the CONIKS model. Through the use of Merkle trees, we verified the integrity of the system, while zero-knowledge proofs were utilized to ensure the confidentiality of key bindings. We conducted experimental evaluations to measure the performance of cryptographic operations like key generation, signing, and verification with varying key sizes and compared the results against theoretical expectations. Our findings demonstrate that the system performs as predicted by cryptographic theory, with only minor deviations in computational time complexities. The analysis also reveals significant trade-offs between security and efficiency, particularly when larger key sizes are used. These results confirm that the CONIKS system offers a robust framework for secure and efficient key management, highlighting its potential for real-world applications in secure communication systems.
Open access
Cryptography and Data Security
Security in Wireless Sensor Networks
Advanced Steganography and Watermarking Techniques
Matteo Loporchio, Anna Bernasconi, Damiano Di Francesco Maesa, Laura Ricci
Decentralized applications, the driving force behind the new Web3 paradigm, require continuous access to blockchain data. Their adoption, however, is hindered by the constantly increasing size of blockchains and the sequential scan nature of their read operations, which introduce a clear inefficiency bottleneck. Also, the growing amount of data recorded on the blockchain makes resource-constrained light nodes dependent on untrusted full nodes for fetching information, with a consequent need for query authentication protocols ensuring result integrity. Motivated by these reasons, in this paper we propose the skip index, an indexing data structure that allows users to quickly retrieve information simultaneously from multiple blocks of a blockchain. Our solution is also designed to be used as an authenticated data structure to guarantee the integrity of query results for light nodes. We discuss the theoretical properties of skip indices, propose efficient algorithms for their construction and querying, and detail their computational complexity. Finally, we assess the effectiveness of our proposal through an experimental evaluation on the Ethereum blockchain. As a reference use case, we focus on the popular CryptoKitties application and simulate a scenario where users seek to retrieve the events generated by the service. Our experimental results suggest that the use of skip indices offers a constant multiplicative speedup, thanks to search times that are at most logarithmic within a chosen search window. This allows to reduce the number of visited blocks by up to two orders of magnitude if compared to the naive sequential approach currently in use. • We propose the skip index, a data structure for efficient blockchain data retrieval. • The skip index provides guarantees about the integrity of query results. • We devise efficient algorithms to construct and query skip indices. • Compared to a sequential scan, skip indices offer a constant multiplicative speedup. • Skip indices experimentally provide a speedup of up to two orders of magnitude.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Random numbers play a vital role in many decentralized applications (dApps), such as gaming and decentralized finance (DeFi) applications. Existing random number provision mechanisms can be roughly divided into two categories, on-chain, and off-chain. On-chain approaches usually rely on the blockchain as the major input and all computations are done by blockchain nodes. The major risk for this type of method is that the input itself is susceptible to the adversary's influence. Off-chain approaches, as the name suggested, complete the generation without the involvement of blockchain nodes and share the result directly with a dApp. These mechanisms usually have a strong security assumption and high complexity. To mitigate these limitations and provide a framework that allows a dApp to balance different factors involved in random number generation, we propose a hybrid random number generation solution that leverages IoT devices equipped with trusted execution environment (TEE) as the randomness sources, and then utilizes a set of cryptographic tools to aggregate the multiple sources and obtain the final random number that can be consumed by the dApp. The new approach only needs one honest random source to guarantee the unbiasedness of the final random number and a user can configure the system to tolerate malicious participants who can refuse to respond to avoid unfavored results. We also provide a concrete construction that can further reduce the on-chain computation complexity to lower the cost of the solution in practice. We evaluate the computation and gas costs to demonstrate the effectiveness of the improvement.
Open access
2 source records
Peer-to-Peer Network Technologies
Advanced Steganography and Watermarking Techniques
In blockchain-based data trading platforms, the illegal resale of image data has led to serious copyright infringement issues. Traditional protective measures typically rely on embedding digital watermarks into images to verify data ownership and integrity. However, to ensure the correctness of the watermark embedding process, the embedded results need to be verified. Existing zero-knowledge proof schemes like Groth16 offer efficient verification but are limited in practical applications due to the high computational costs associated with the trusted setup phase required for third-party computations. To address this issue, this paper proposes a watermark embedding and verification mechanism based on block-based processing. By partitioning the image and embedding the watermark incrementally, the time required for the trusted setup and zkey generation in zero-knowledge proofs is significantly reduced, thereby improving the overall efficiency of proof generation. Experimental results show that after partitioning, the total proof generation time is reduced to 24.274% of that in the unpartitioned case. This demonstrates that the proposed method significantly reduces proof generation time, making it more efficient for large-scale image data transactions in blockchain environments.
Advanced Steganography and Watermarking Techniques
The study investigates the impact of blockchain technology on safeguarding supply chains in the liquor industry. The objectives include enhancing traceability, authenticity verification, and counterfeit prevention. Methodology involves implementing a blockchain-based model leveraging the Ethereum Network for transparent product tracking. Results demonstrate a significant reduction in counterfeit liquor sales, improved supply chain transparency, and enhanced product authentication. The study concludes that blockchain technology offers a robust solution to combat illicit liquor sales, ensuring integrity and traceability in the liquor bottle supply chain. The findings highlight the transformative potential of blockchain in fortifying supply chain security and promoting industry-wide trust and transparency.
Advanced Steganography and Watermarking Techniques
The research paper explores the concept of selective disclosure within blockchain networks, addressing the tension between transparency and privacy. It introduces cryptographic schemes that allow users to reveal only necessary information, maintaining confidentiality. The paper analyzes various selective disclosure methods, such as Zero-Knowledge Proofs and Attribute-Based Encryption, highlighting their applications in enhancing privacy and security in digital transactions. It also discusses the implementation of these schemes in blockchain for certification system, emphasizing their potential to foster trust and promote wider adoption of blockchain technology across different industries. The paper concludes by identifying future research directions to optimize these cryptographic protocols for better scalability and interoperability in blockchain systems.
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
In the era of digital technology, the widespread availability of multimedia content has presented major challenges in confirming the genuineness and reliability of digital media. This paper introduces a novel technology that utilizes the InterPlanetary File System (IPFS) and Ethereum to authenticate multimedia content, ensuring its provenance and prohibiting tampering. The suggested approach brings together a decentralized ledger system with cryptographic hashing and smart contracts to create an immutable record of content ownership and modification history. By integrating cryptographic hashes of multimedia files into blockchain transactions, we establish a secure, transparent, and tamper-proof mechanism for tracking content authenticity. Our methodology improves confidence and dependability in digital media by establishing a strong structure for creators, distributors, and consumers to authenticate the authenticity of multimedia materials. Experimental results confirm the effectiveness and efficiency of our system in preserving the integrity of various types of multimedia content, laying the path for a wider utilization areas such as digital rights management, content distribution, and forensic analysis, etc.
Advanced Steganography and Watermarking Techniques
With the widespread use of cryptocurrencies and the development of anonymity network technology, how to effectively identify cryptocurrency transactions through anonymity networks such as Tor has become a major challenge in cybersecurity. We introduce a new traffic correlation technique, TSMCorr, aimed at identifying cryptocurrency transactions through anonymous networks like Tor. Traditional traffic correlation methods struggle with the high cost of deployment, while we leverage advanced feature engineering and deep learning, including a Traffic Volume Matrix (TSM), to develop a more accurate and efficient flow correlation model. TSMCorr not only improves upon existing methods in terms of F1 score by $15.5 \%$ on DeepCoFFEA dataset, but also lowers the computational time by $89 \%$, RAM consumption by $77.4 \%$, and model parameters by $11.5 \%$.
Internet Traffic Analysis and Secure E-voting
Chaos-based Image/Signal Encryption
Advanced Steganography and Watermarking Techniques
Carsten Baum, Jens Berlips, W Q Chen, Ivan Damgård · 20 authors
Oblivious Pseudorandom Functions (OPRFs) allow a client to evaluate a pseudorandom function (PRF) on her secret input based on a key that is held by a server. In the process, the client only learns the PRF output but not the key, while the server neither learns the input nor the output of the client. The arguably most popular OPRF is due to Naor, Pinkas and Reingold (Eurocrypt 2009). It is based on an Oblivious Exponentiation by the server, with passive security under the Decisional Diffie-Hellman assumption. In this work, we strengthen the security guarantees of the NPR OPRF by protecting it against active attacks of the server. We have implemented our solution and report on the performance. Our main result is a new batch OPRF protocol which is secure against maliciously corrupted servers, but is essentially as efficient as the semi-honest solution. More precisely, the computation (and communication) overhead is a multiplicative factor <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>o</mml:mi> <mml:mo stretchy="false">(</mml:mo> <mml:mn>1</mml:mn> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> </mml:math> as the batch size increases. The obvious solution using zero-knowledge proofs would have a constant factor overhead at best, which can be too expensive for certain deployments. Our protocol relies on a novel version of the DDH problem, which we call the Oblivious Exponentiation Problem (OEP), and we give evidence for its hardness in the Generic Group model. We also present a variant of our maliciously secure protocol that does not rely on the OEP but nevertheless only has overhead <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>o</mml:mi> <mml:mo stretchy="false">(</mml:mo> <mml:mn>1</mml:mn> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> </mml:math> over the known semi-honest protocol. Moreover, we show that our techniques can also be used to efficiently protect threshold blind BLS signing and threshold ElGamal decryption against malicious attackers.
Open access
Cryptography and Data Security
Privacy-Preserving Technologies in Data
Advanced Steganography and Watermarking Techniques
Abstract With the rapid expansion of the Internet of Things (IoT), cloud storage has emerged as one of the cornerstones of data management, facilitating ubiquitous access and seamless sharing of information. However, with the involvement of a third party, traditional cloud‐based storage systems are plagued by security and availability concerns, stemming from centralized control and management architectures. A novel blockchain‐IoT model that leverages blockchain technology and decentralized storage mechanisms to address these challenges is presented. The model combines the Ethereum blockchain, interplanetary file system, and attribute‐based encryption to ensure secure and resilient storage and sharing of IoT data. Through an in‐depth exploration of the system architecture and underlying mechanisms, it is demonstrated how the framework decouples storage functionality from resource‐constrained IoT devices, mitigating security risks associated with on‐device storage. In addition, data owners and users can easily exchange data with one another through the use of Ethereum smart contracts, fostering a collaborative environment and providing incentives for data sharing. Moreover, an incentive mechanism powered by the FileCoin cryptocurrency is introduced, which motivates and ensures data sharing transparency and integrity between stakeholders. Furthermore, in the proposed blockchain‐IoT model, the proof‐of‐authority system consensus algorithm has been replaced by a delegated proof‐of‐capacity system, which reduces transaction costs and energy consumption. Using the Rinkby Ethereum official testing network, the proposed model has been demonstrated to be feasible and economical, emphasizing its potential to redefine IoT data management.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
Zeyu Zhou, Ding Liu, Tatiana R. Shmeleva, Dmitry A. Zaitsev
Bitcoin is under the threat of fork since it operates with a distributed ledger. Predicting the fork probability in advance is beneficial for taking early action to avoid malicious attacks. In this study, we compose a colored Petri net model of Bitcoin. Our model consists of a given number of nodes, and each node has five subpages representing the node structure: proof of work, broadcast blocks, verify blocks, and the process of adding blocks to blockchain, respectively. Simulation results of fork probability can be easily obtained and analyzed by observing the data in the measuring components of subpages. The results show that our model correctly simulates the fork probability: on recent Bitcoin data, compared with the results of the wide-known SimBlock simulator, a difference of some 4.3% has been obtained. Thus, taking into account vivid graphical representation, our model has certain advantages for the developing techniques of attack avoidance.
Advanced Steganography and Watermarking Techniques
The advancements in telematics and communication technology for automobiles have contributed to the development of Vehicular ad Hoc Networks (VANETs). These networks serve as the foundation for Intelligent Transportation Systems (ITS). Communication across various VANET entities is challenging due to the open communication environment and the highly dynamic nature of VANETs. One of the major challenges in VANETs is ensuring stable and secure transmission. To address these factors, several studies have been conducted. The article discusses a clustering algorithm for VANETs that leverages SCVAN-DPSO to create stable clusters and provide secure communication for mitigating malicious nodes. Additionally, Hyperelliptic Curve Cryptography (HECC) with signcryption in blockchain is proposed. This algorithm is designed to identify and mitigate malicious nodes, ensuring robust and secure communication within the network. To verify vehicles in VANETs, this study also suggests a safe and reliable key management method that generates and stores cryptographic keys using blockchain’s distributed ledger technology. By doing so, the risk of rogue nodes is reduced, and a safe, stable connection between vehicles is guaranteed. This work has been implemented using NS 3.34 simulation with the SUMO real-time traffic mobility simulator, and its performance has been evaluated. The proposed algorithm SCVAN-BKM provides a 99.6 % packet delivery ratio for 20 nodes, 0.4 % packet loss, end-to-end delay of 32.65 ms, throughput of 9.522 Mbps, and a cluster lifetime of 105 s. As the number of nodes increases in the communication zone, stable communication is maintained due to the clustering algorithm used in the proposed approach, as cluster formation supports stability in the high-mobility nature of vehicles, while secure communication is ensured using blockchain technology. The findings demonstrate that our approach is more effective and yields better outcomes than existing systems.
Open access
Vehicular Ad Hoc Networks (VANETs)
Advanced Steganography and Watermarking Techniques
Recently, with the popularity of Internet of vehicles (IoV), there is an increasing market demand for integrating blockchain technology and smart contracts in electric vehicles. By utilizing distributed blockchain and smart contract technology, it provides data integrity preservation, traceability, and prevention of forgery. These features can be effectively used in the automated charging system. As a result, IoV can utilize blockchain and smart contract technologies to facilitate seamless payment for charging fees, tolls, parking fees, online shopping and other associated expenses without the need for intermediaries. However, since blockchain and smart contracts operate in an open internet environment, there is a risk of tampering with transaction records. Therefore, enhancing security becomes a crucial concern. The main aim of this study is to emphasize the growing significance of securing transactions and smart contracts in an open transmission environment to prevent potential damage or alteration. In order to achieve the implementation of secure smart contracts within a resource-constrained IoV, this study investigates various cryptographic mechanisms and realizes the elliptic curve cryptosystem (ECC) is widely recognized for providing strong security with shorter key lengths compared to other public key cryptography methods. This makes it ideal for environments with limited resources. Furthermore, in order to enhance the performance of smart contracts, this study proposes a cloud server architecture for parallel storage of smart contracts to improve access speed. Additionally, we introduce an automated trading framework for smart contracts that operates without human intervention. Finally, this study uses ECC to ensure the secure transmission of transaction data among the vehicle, base station, and cloud server, as well as to provide mutual verification of identities across all entities involved in the operation. As a result, this study proposes a secure architecture for blockchain and smart contracts that can autonomously initiate transactions while ensuring secure transmission and protection in the IoV.
Open access
2 source records
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Inderpreet Singh, Amandeep Kaur, Parul Agarwal, Sheikh Mohammad Idrees
Abstract Most existing e-government services are centralized and rely heavily on human control. This centralized approach makes the system more susceptible to external attacks and compromises data integrity by rogue insiders. Additionally, relying on individuals to monitor and control workflows introduces errors and corruption risks. In order to guarantee security and transparency, this study proposes an automated and decentralized online voting system that makes use of blockchain technology. Compared to conventional voting techniques, it is more efficient and cost-effective, because it eliminates the need of intermediaries. The primary goal of this research is to use blockchain technology to develop a transparent and safe online voting system. In this paper, a decentralized voting system will be developed utilizing ethereum blockchain and smart contracts to ensure the voting process’s integrity. The system can be evaluated with simulated voting data to reflect real-world scenarios, focusing on security, scalability, and user-friendliness. The study also explores potential future enhancements, such as incorporating biometric authentication to further improve accessibility and security. The insights provided will be valuable to policymakers, researchers, and practitioners involved in the development, implementation, and regulation of blockchain-based voting systems.
Open access
Blockchain Technology Applications and Security
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
Francesco Zola, Jon Elduayen, Igor Pallin, Raúl Orduna-Urrutia
Abstract Despite being backed by blockchain technology that promises security, immutability, and full transparency, some cryptocurrencies such as Bitcoin have been used as enablers for many licit and illicit activities such as money laundering, terrorism financing, and ransomware payments. In this scenario, the analysis of the transactions, as well as the entities that have generated them, became a crucial step for law enforcement officer (LEO) investigations. However, the (pseudo) anonymity of the network, the lack of regulatory authority, the employment of anonymizer mechanisms, the evolution of entities’ behavior, and the emergence of new dynamics are just five of the main elements that make this task challenging. At the same time, the huge amount of information to be analyzed can result in a waste of time and resources, slowing the investigations. For this reason, in this work, we present Kriptosare, a tool able to classify entity behaviors belonging to Bitcoin, Bitcoin Cash, and Litecoin. On the one hand, the tool makes use of state-of-the-art machine learning techniques to reduce anonymity in the considered cryptocurrencies. This model extracts behaviors from interactions and dynamics of different known entities involved in the transactions and then predicts the behaviors of new unseen entities. On the other hand, Kriptosare includes a crypto simulator able to create and control a private Bitcoin, Bitcoin Cash, or Litecoin network. This unit allows the simulation of crypto transactions in a controlled way for evaluating hypotheses and/or enriching the input data. The presented tool can be used by LEOs to search and highlight the most important red flag indicators that could suggest criminal behavior, and to support their analysis by optimizing their investigation resources.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
As digital crime continues to rise, the preservation of digital evidence has become a critical phase in digital forensic investigations. This phase focuses on securing and maintaining the integrity of evidence for legal proceedings. Existing solutions for evidence preservation, such as centralized storage systems and cloud frameworks, present challenges related to security and collaboration. In this paper, we propose a novel framework that addresses these challenges in the preservation phase of forensics. Our framework employs a combination of advanced technologies, including the following: (1) Segmenting evidence into smaller components for improved security and manageability, (2) Utilizing steganography for covert evidence preservation, and (3) Implementing blockchain to ensure the integrity and immutability of evidence. Additionally, we incorporate Long Short-Term Memory (LSTM) networks to enhance steganography in the evidence preservation process. This approach aims to provide a secure, scalable, and reliable solution for preserving digital evidence, contributing to the effectiveness of digital forensic investigations. An experiment using linguistic steganography showed that the LSTM autoencoder effectively generates coherent text from bit streams, with low perplexity and high accuracy. Our solution outperforms existing methods across multiple datasets, providing a secure and scalable approach for digital evidence preservation.
Open access
Advanced Steganography and Watermarking Techniques
Current authentication schemes based on zero-knowledge proof (ZKP) still face issues such as high computation costs, low efficiency, and security assurance difficulty. Therefore, we propose a secure and efficient authentication scheme (SEAS) for large-scale IoT devices based on ZKP. In the initialization phase, the trusted authority creates prerequisites for device traceability and system security. Then, we propose a new registration method to ensure device anonymity. In the identity tracing and revocation phase, we revoke the real identity of abnormal devices by decrypting and updating group public keys, avoiding their access and reducing revocation costs. In the authentication phase, we check the arithmetic relationship between blind certificates, proofs, and other random data. We propose a new anonymous batch authentication method to effectively reduce computation costs, enhance authentication efficiency, and guarantee device authentication security. Security analysis and experimental results show that an SEAS can ensure security and effectively reduce verification time and energy costs. Its security and performance exceed existing schemes.
Open access
User Authentication and Security Systems
Advanced Steganography and Watermarking Techniques