Recent investigative frame works, digital forensic tools, and techniques are incapable of acquiring the IoT paradigm's dispersion and heterogeneity characteristics that make law enforcement organizations and digital forensic investigators do their tasks. To address these issues, this study presents a Blockchain-assisted digital forensic system for the IoT context. The devices in the perception layer contain several forensic evidences, which are transmitted to the further layer called the Fog layer. Moreover, the secure transmission of messages from the perception layer to the fog layer is a major challenge. To address this issue, the user's identity (investigators and devices) can be mapped to a pseudo-identity and the security of signature and confidentiality mechanisms ensures both privacy and security. Subsequently, the Fog layer verifies the signature data and employs an improved Blowfish encryption algorithm to provide security to the evidence transmission. In order to encrypt the evidence, the optimal key is generated using the SSAJO algorithm. Then the encrypted message is subjected to a distributed ledger called consortium blockchain that improves the security factors with a greater level of control. Moreover, the proposed IoT framework controls the cloud locally to store, and access data, and performs occasional synchronization with a consortium blockchain.
Log files are essential assets for IT engineers engaged in the security of server and computer systems. They provide crucial information for identifying malicious events, conducting cybersecurity incident analyses, performing audits, system maintenance, and ensuring compliance with security regulations. Nevertheless, there is still the possibility of deliberate data manipulation by own personnel, especially with regard to system access and configuration changes, where error tracking or debugging traces are vital. To address tampering of log files, this work proposes a solution to ensure data integrity, immutability, and non-repudiation through different blockchain-based public registry systems. This approach offers an additional layer of security through a decentralized, tamper-resistant ledger. To this end, this manuscript aims to provide a solid guideline for creating secure log storage systems. For this purpose, methodologies and experiments using two different blockchains are presented to demonstrate their effectiveness in various contexts, such as transactions with and without metadata. The findings suggest that Solanaโs response times make it well suited for environments with moderately critical records requiring certification. In contrast, Cardano shows higher response times, thus making it suitable for less frequent events with metadata that requires legitimacy.
Open access
Blockchain Technology Applications and Security
Digital and Cyber Forensics
Advanced Steganography and Watermarking Techniques
Oshoke Samson Igonor, Muhammad Bilal Amin, Saurabh K. Gargโ
Blockchain technology has risen in recent years from its initial application in finance to gain prominence across diverse sectors, including digital forensics. The possible application of blockchain technology to digital forensics is now becoming increasingly explored with many researchers now looking into the unique inherent properties that blockchain possesses to address the inherent challenges in this sector such as evidence tampering, the lack of transparency, and inadmissibility in court. Despite the increasing interest in integrating blockchain technology into the field of digital forensics and its domains, no systematic literature review currently exists to provide a holistic perspective on this integration. It is a challenge to find a comprehensive resource that examines how blockchain is being applied to enhance the digital forensics process. This paper provides a systematic literature review to explore the application of blockchain technology in digital forensics, focusing on its potential to address these challenges and enhance forensic methodologies. Through a rigorous review process, this paper examines selected studies to identify diverse frameworks, methodologies, and blockchain-driven enhancements applied to digital forensic investigations. The discussion highlights how blockchain properties such as immutability, transparency, and automation have been leveraged to improve evidence management and forensic workflows. Furthermore, this paper explores the common applications of blockchain-based forensic solutions across various domains and phases while addressing the associated limitations and challenges. Open issues and future research directions, including unexplored domains and operational gaps, are also discussed. This study provides valuable insights for researchers, investigators, and policymakers by offering a comprehensive overview of the state of the art in blockchain-based digital forensics, summarizing key contributions and limitations, and identifying pathways for advancing the field.
Durgam Rajababu, S. Surya, Mrutyunjay Padhiary, Harshadkumar S. Modi
The feasibility of using blockchain technology as a method to improve cybersecurity through data security transactions and users' anonymity is discussed in this paper. It scans network traffic, sings out abnormities, and uses the clustering approach to find cybersecurity risks. The identified evidence points to the prospects of blockchain to disrupt threat management and enhance the resilience of digital landscapes against cyber threats.
In smart contract fuzz testing, it is crucial to consider the inter-dependencies between the contract functions. To effectively test the business logic of a contract, its functions must be invoked in a meaningful order. In this paper, we propose techniques that utilize static analysis on Ethereum bytecode to tackle this challenge. When compared with the current state-of-the-art, our approach takes Solidity compilerโs variable packing optimization into account and allows more precise analysis of the data-flows between functions. In addition, we devise a novel test case initialization algorithm for fuzz testing, which minimizes the redundancy in the generated seed set. Our algorithm reduces test cases that share similar function call patterns and leads to more effective testing of the contract code during the fuzz testing. Experimental results show that the proposed techniques improve the effectiveness of smart contract fuzz testing for vulnerability detection. Specifically, our techniques enabled the fuzz testing tool to trigger the target bugs in the benchmark 3.0 times faster on average.
The rapid digital transformation across various sectors has intensified the need for secure, automated management systems to handle sensitive data with integrity and privacy. Traditional systems often struggle to securely manage and authenticate larg e volumes of data, leaving it vulnerable to unauthorized access and breaches. This paper presents an intelligent information management system based on blockchain technology, designed to enhance data security, integrity, and automated access control through decentralized storage, cryptographic algorithms, and smart contracts. The proposed system leverages blockchain's decentralized ledger to offer a tamper-resistant, distributed storage solution, minimizing risks of data tampering and enhancing transparency. Smart contracts add automation to access control and data verification processes, reinforcing system robustness and reducing the potential for human error. This paper's contributions include developing a blockchain-based intelligent data management framework, evaluating its efficacy in real-world scenarios, and demonstrating its advantages over traditional centralized approaches in terms of security, privacy, and operational automation. This study provides a foundational approach to enhance the security and autonomy of digital information systems, enabling more resilient data management infrastructures.
Cryptocurrency-related crimes are on the rise and have a wide-ranging impact across various areas. To effectively combat and prevent these illicit activities, cryptocurrency forensics (crypto forensics) is essential. At its core, this field relies on the investigation and analysis of blockchain data. However, the inherent pseudonymity and dynamics of Bitcoin introduce significant complexities to these investigations. The collection and validation of Bitcoin addresses are indispensable processes in blockchain forensic analysis, crucial for identifying suspicious transactions, tracing fund flows, and conducting de-anonymization investigations. Address clustering, which groups addresses likely controlled by the same entity, serves as a foundational technique. The accuracy of clustering outcomes significantly impacts the reliability of crypto forensic findings. While heuristic-based address clustering is commonly adopted, its effectiveness faces limitations primarily due to the absence of ground truth data. This lack introduces fundamental uncertainty into clustering results, hindering the validation of forensic conclusions. This uncertainty is compounded by the increasing adoption of privacy-enhancing technologies, which complicate address relationships and create additional hurdles for investigators. Moreover, other blockchain dynamic factors, such as introducing new network features, further challenge the accuracy of clustering, collectively making reliable forensic analysis increasingly complex. This study undertakes multiple approaches to address these limitations. In the first part, confronting the challenge of unavailable ground truth labels, we develop a simulation model to assess the potential error rates of two widely used clustering heuristics: the multi-input and one-time change address heuristics. The second part provides an in-depth behavioral analysis of peeling chains, a common structure utilized by entities such as exchanges and mixers. This analysis enhances our understanding of the operational characteristics of transaction data associated with privacy-enhancing practices. Building on works and insights from these first two parts, the third part introduces an enhanced simulation platform that more accurately replicates real-world Bitcoin transaction structures. Additionally, we propose and evaluate a novel heuristic algorithm specifically designed to improve the classification of one-time change addresses. This refined simulator provides a robust environment for assessing address clustering methods based on transaction details. The new heuristic aims to reduce misclassifications and achieve better clustering results. Overall, this research presents a simulation framework to quantify the uncertainties in heuristic clustering results. This facilitates a clearer assessment of the reliability and limitations of address clustering algorithms, thus strengthening the basis for the admissibility of clustering findings as forensic evidence. The proposed heuristic more effectively captures relevant transaction patterns, helping to alleviate the uncertainties introduced by privacy techniques in forensic analysis. Additionally, all three parts of this study contribute a comprehensive analysis of Bitcoin blockchain data from different periods, examining aspects such as transaction types, address reuse, and structural details. The identified characteristics and observed trends serve as a basis for refining forensic tools and methodologies.
Leandro Loffi, Gerson Luiz Camillo, Cristiano Antonio de Souza, Carla Merkle Westphall ยท 5 authors
Digital evidence plays an increasingly crucial role in judicial proceedings due to the exponential growth in the creation, storage, and transmission of digital data. However, its inherent volatility and susceptibility to tampering necessitate robust mechanisms to ensure integrity and authenticity, making an effective chain of custody (CoC) a fundamental requirement. While state-of-the-art reviews identify various aspects, it is necessary to include the use of Self-Sovereign Identity (SSI) systems within the scope of research. To address this challenge, this article conducts a systematic review of the literature on the use of blockchain and SSI in managing the chain of custody of digital evidence. The review began with 9,178 studies, which, after a rigorous process applying inclusion and exclusion criteria, resulted in 39 studies directly related to the research topic. The study maps and reviews techniques, tools, methods, approaches, and security components for managing the chain of custody of digital evidence. The findings confirm the widespread adoption of blockchain for preserving digital evidence while indicating that SSI remains an emerging and underexplored concept in forensic applications. The results highlight the need for further research on off-chain storage mechanisms, privacy-preserving techniques such as Zero-Knowledge Proofs (ZKPs) to enhance security, auditability, and interoperability when combined with Verifiable Credentials (VCs). By mapping the current state of research, this study provides valuable insights into CoC, Blockchain, and SSI in forensic-based proposals, identifying research gaps, limitations, and opportunities for developing more robust and scalable evidence management systems.
The rise of blockchain and Digital Ledger Technology (DLT) has gained wide traction. Instead of relying on a traditional centralized data authority, a blockchain system consists of digitally entangled block data shared across a distributed network. The specially designed chain data structure and its consensus mechanism protect blockchain data from being tampered by unauthorized adversaries. However, implementing a full-fledged blockchain system to protect a database can be technically cumbersome. In this work, we introduce an in-database design, named chain table, to protect data integrity without the need for a blockchain system. It features a succinct design without significant technology barriers or storage overhead. To realize rigorous data security, we also propose a set of data writing principles for the chain table. We prove that the chain table, together with the data writing principles, will guarantee flexible data integrity, named table-level data integrity (TDI).
The growth in the technology of cloud storage has meant that more and more organizations outsource large amounts of data to the cloud for storage, for archival and compliance purposes. This offers cost and scalability benefits but it introduces issues around verifying data integrity and the risk of leaking sensitive during audits by third parties. Past public auditing frameworks rely on interactive challenge-response mechanisms that leak metadata, increase audit latency and are susceptible to man in the middle attacks. This research proposes a non-interactive, privacy preserving public auding framework using Zero-knowledge Scalable Transparent Arguments of Knowledge (zk-STARKS). Using the Winterfell library to generate cryptographic proofs that a data set remains unchanged without revealing the content of the data or structural metadata to the verifier. The frame is deployed using a cloud native architecture, composed of AWS services. Evaluation of a 200MB dataset split into 2mb per block achieved proof and verification times of approx. 900 ms per block, which can be scaled up to larger datasets with limited cloud compute costs. The result confirm that zk-STARKS can be used to implement an efficient, trust less and privacy preserving framework for cold data auditing, detecting tampering of data without the need for a trusted TPA.
Mr. Amar More, Mr . Karan More, Mr . Nikhil Neavse, Mr. Prasanna Deokar ยท 6 authors
This project introduces a decentralized file storage system that leverages blockchain technology to create a secure, immutable, and tamper-resistant platform for file sharing. By storing files within blocks on a blockchain, the system ensures that once data is uploaded, it cannot be altered or deleted, making it ideal for applications where data integrity is critical. Users interact with the platform through a web interface, allowing them to upload, download, and share files across a peer-to-peer network. The blockchain structure used in this project employs a Proof of Work (PoW) consensus mechanism, requiring peers (miners) to solve cryptographic puzzles to validate blocks and add them to the chain. Two different PoW methods are used: one generates nonces at random, while the other increases the nonce value one after the other. By comparing the effectiveness and security of different methods, the project finds that random nonce generation outperforms them at higher difficulty levels, providing quicker block validation and more robust defense against possible assaults. On the other hand, the incremental approach is less secure over time because it is simpler to foresee. The project also covers the advantages of on-chain storage, which involves storing files directly inside blockchain blocks. This approach offers better security but comes at the expense of more processing power. Furthermore, it investigates alternatives such as off-chain blockchain architectures for more effective file storage in subsequent iterations and Proof of Stake (PoS) for lowering resource use
Christos Karapapas, Iakovos Pittaras, George C. Polyzos, Constantinos Patsakis
The InterPlanetary File System~(IPFS) offers a decentralized approach to file storage and sharing, promising resilience and efficiency while also realizing the Web3 paradigm. Simultaneously, the offered anonymity raises significant questions about potential misuse. In this study, we explore methods that malicious actors can exploit IPFS to upload and disseminate harmful content while remaining anonymous. We evaluate the role of pinning services and public gateways, identifying their capabilities and limitations in maintaining content availability. Using scripts, we systematically test the behavior of these services by uploading malicious files. Our analysis reveals that pinning services and public gateways lack mechanisms to assess or restrict the propagation of malicious content.
M. Imrankhan, Maria Viji, Ramamoorthy Sathishkumar, T. Gnanaprakash ยท 6 authors
This can be one of the most magnificent advantages realized from applying blockchain technology in a forensic investigation context, namely, a transformative approach to address challenges embedded within legal and criminal justice systems. For example, smart contracts, being self-executing agreements with the automated inclusion of predefined rules, may even automate and secure the process of tracking evidence, managing chain of custody, and access control. This smart contract will ensure that forensic operations are transparent and of sound integrity. Every transaction and action performed on the blockchain is recorded there, instantaneously bringing down tampering to the lowest possibility and any chance for human mistakes. Regarding decentralized nature and cryptography-based security combined with immutability, blockchain is a technology known to have safeguards over sensitive data. Once recorded on the blockchain, the information thereupon becomes completely un-changeable, assuring the reliability and authenticity of evidence. This will be especially important in the management of an unforgeable chain of custody and in ensuring that forensic evidence remains unchanged and can be relied on with integrity throughout the court process.[6] Critical data can then be maintained tamper-proof for management and storage by developing Ethereum-based smart contracts on Remix IDE using Solidity.[15]Each transaction will be time-stamped and safely logged on the Ethereum blockchain, thus developing an unchallenged ledger that makes any investigation that much more trustworthy. In a nutshell, the application of blockchain in forensic activities builds greater control and efficiencies, reduces possible errors and conflicts, and provides transparency, integrity, and an unchangeable, permanent record for forensic processes. The invention thereby significantly upgrades the general integrity and confidence in legal and criminal justice inquiries.
The proliferation of Internet of Things (IoT) devices has facilitated the exchange of information among individuals and devices. This development has introduced several challenges, including increased vulnerability to potential cyberattacks and digital forensics. IoT forensic investigations need to be managed in a forensically sound manner using a standard framework. However, adopting traditional digital forensics tools introduces various challenges, such as identifying all IoT devices and users at the crime scene. Therefore, collecting evidence from these devices is a major problem. This paper proposes a permissioned blockchain integration solution for IoT forensics (PBCIS-IoTF) that aims to observe data transactions within the blockchain. The PBCIS-IoTF framework designs and tests Hyperledger blockchains simulated with a Raspberry Pi device and chaincode to address the challenges of IoT forensics. This blockchain is deployed using multiple nodes within the network to avoid a single point of failure. The authenticity and integrity of the acquired evidence are analysed by comparing the SHA-256 hash metadata in the blockchain of all peers within the network. We further integrate webpage access with the blockchain to capture the forensics data from the userโs IoT devices. This allows law enforcement and a court of law to access forensic evidence directly and ensures its authenticity and integrity. PBCIS-IoTF shows high authenticity and integrity across all peers within the network.