Ye Wang, Patrick Zuest, Yaxing Yao, Zhicong Lu · 5 authors
Decentralized finance (DeFi) enables crypto-asset holders to conduct complex financial transactions, while maintaining control over their assets in the blockchain ecosystem. However, the transparency of blockchain networks and the open mechanism of DeFi applications also cause new security issues. In this paper, we focus on sandwich attacks, where attackers take advantage of the transaction confirmation delay and cause financial losses for victims. We evaluate the impact and investigate users’ perceptions of sandwich attacks through a mix-method study. We find that due to users’ lack of technical background and insufficient notifications from the markets, many users were not aware of the existence and the impact of sandwich attacks. They also had a limited understanding of how to resolve the security issue. Interestingly, users showed high tolerance for the impact of sandwich attacks on individuals and the ecosystem, despite potential financial losses. We discuss general implications for users, DeFi applications, and the community.
Distributed ledger systems have become more prominent and successful in recent years, with a focus on blockchains and cryptocurrency. This has led to various misunderstandings about both the technology itself and its capabilities, as in many cases blockchain and cryptocurrency is used synonymously and other applications are often overlooked. Therefore, as a whole, the view of distributed ledger technology beyond blockchains and cryptocurrencies is very limited. Existing vocabularies and ontologies often focus on single aspects of the technology, or in some cases even just on one product. This potentially leads to other types of distributed ledgers and their possible use cases being neglected. In this paper, we present a knowledge graph and an ontology for distributed ledger technologies, which includes security considerations to model aspects such as threats and vulnerabilities, application domains, as well as relevant standards and regulations. Such a knowledge graph improves the overall understanding of distributed ledgers, reveals their strengths, and supports the work of security personnel, i.e. analysts and system architects. We discuss potential uses and follow semantic web best practices to evaluate and publish the ontology and knowledge graph.
Tanusree Sharma, Zhixuan Zhou, Andrew Miller, Yan Wang
Smart contracts are self-executing programs that run on blockchains (e.g., Ethereum). 680 million US dollars worth of digital assets controlled by smart contracts have been hacked or stolen due to various security vulnerabilities in 2021. Although security is a fundamental concern for smart contracts, it is unclear how smart contract developers approach security. To help fill this research gap, we conducted an exploratory qualitative study consisting of a semi-structured interview and a code review task with 29 smart contract developers with diverse backgrounds, including 10 early stage (less than one year of experience) and 19 experienced (2-5 years of experience) smart contract developers. Our findings show a wide range of smart contract security perceptions and practices including various tools and resources they used. Our early-stage developer participants had a much lower success rate (15%) of identifying security vulnerabilities in the code review task than their experienced counterparts (55%). Our hierarchical task analysis of their code reviews implies that just by accessing standard documentation, reference implementations and security tools is not sufficient. Many developers checked those materials or used a security tool but still failed to identify the security issues. In addition, several participants pointed out shortcomings of current smart contract security tooling such as its usability. We discuss how future education and tools could better support developers in ensuring smart contract security.
Sabreen Ahmadjee, Carlos Mera‐Gómez, Rami Bahsoon, Rick Kazman
Blockchain is a disruptive technology intended to implement secure decentralised distributed systems, in which transactional data can be shared, stored, and verified by participants of the system without needing a central authentication/verification authority. Blockchain-based systems have several architectural components and variants, which architects can leverage to build secure software systems. However, there is a lack of studies to assist architects in making architecture design and configuration decisions for blockchain-based systems. This knowledge gap may increase the chance of making unsuitable design decisions and producing configurations prone to potential security risks. To address this limitation, we report our comprehensive systematic literature review to derive a taxonomy of commonly used architecture design decisions in blockchain-based systems. We map each of these decisions to potential security attacks and their posed threats. MITRE’s attack tactic categories and Microsoft STRIDE threat modeling are used to systematically classify threats and their associated attacks to identify potential attacks and threats in blockchain-based systems. Our mapping approach aims to guide architects to make justifiable design decisions that will result in more secure implementations.
Context: Smart contracts are computer programs that are automatically executed on the blockchain. Vulnerabilities in their implementation have led to severe loss of cryptocurrency. Smart contracts become immutable when deployed to the Ethereum blockchain. Therefore, it is essential to understand the nature of vulnerabilities in Ethereum smart contracts to prevent them in the future. Existing classifications exist, but are limited in several ways. Objective: We aim to characterize vulnerabilities in Ethereum smart contracts written in Solidity, and unify existing classifications schemes. Method: We extracted 2143 vulnerabilities from public coding platforms and popular vulnerability databases and categorized them using a card sorting approach. We targeted the Ethereum blockchain in this paper, as it is the first and most popular blockchain to support the deployment of smart contracts, and Solidity as the most widely used language to implement smart contracts. We devised a classification scheme of smart contract vulnerabilities according to their error source and impact. Afterwards, we mapped existing classification schemes to our classification. Results: The resulting classification consists of 11 categories describing the error source of a vulnerability and 13 categories describing potential impacts. Our findings show that the language specific coding and the structural data flow categories are the dominant categories, but that the frequency of occurrence differs substantially between the data sources. Conclusions: Our findings enable researchers to better understand smart contract vulnerabilities by defining various dimensions of the problem and supporting our classification with mappings with literature-based classifications and frequency distributions of the defined categories.
Miner malware has been steadily increasing in recent years as the value of cryptocurrency rises, which poses a considerable threat to users’ device security. Miner malware has obvious behavior patterns in order to participate in blockchain computing. However, most miner malware detection methods use raw bytes feature and sequential opcode as detection features. It is difficult for these methods to obtain better detection results due to not modeling robust features. In this paper, a miner malware identification method based on graph classification network is designed by analyzing the features of function call graph and control flow graph of miner malware, called MBGINet. MBGINet can model the behavior graph relationship of miner malware by extracting the connection features of critical nodes in the behavior graph. Finally, MBGINet transforms these node features into the feature vectors of the graph for miner malware identification. In the test experiments, datasets with different volumes are used for simulating real-world scenarios. The experimental results show that the MBGINet method achieves a leading and stable performance compared to the dedicated opcode detection method and obtains an accuracy improvement of 3.08% on the simulated in-the-wild dataset. Meanwhile, MBGINet gains an advantage over the general malware detection method Malconv. These experimental results demonstrate the superiority of the MBGINet method, which has excellent characteristics in adapting to realistic scenarios.
Heidelinde Rameder, Monika di Angelo, Gernot Salzer
Programs on public blockchains often handle valuable assets, making them attractive targets for attack. At the same time, it is challenging to design correct blockchain applications. Checking code for potential vulnerabilities is a viable option to increase trust. Therefore, numerous methods and tools have been proposed with the intention to support developers and analysts in detecting code vulnerabilities. Moreover, publications keep emerging with different focus, scope, and quality, making it difficult to keep up with the field and to identify relevant trends. Thus, regular reviews are essential to keep pace with the varied developments in a structured manner. Regarding blockchain programs, Ethereum is the platform most widely used and best documented. Moreover, applications based on Ethereum are entrusted with billions of USD. Like on similar blockchains, they are subject to numerous attacks and losses due to vulnerabilities that exist at all levels of the ecosystem. Countermeasures are in great demand. In this work, we perform a systematic literature review (SLR) to assess the state of the art regarding automated vulnerability analysis of smart contracts on Ethereum with a focus on classifications of vulnerabilities, detection methods, security analysis tools, and benchmarks for the assessment of tools. Our initial search of the major on-line libraries yields more than 1,300 publications. For the review, we apply a clear strategy and protocol to assure consequent, comprehensive, and reproducible documentation and results. After collecting the initial results, cleaning up references, removing duplicates and applying the inclusion and exclusion criteria, we retain 303 publications that include 214 primary studies, 70 surveys and 19 SLRs. For quality appraisal, we assess their intrinsic quality (derived from the reputation of the publication venue) as well as their contextual quality (determined by rating predefined criteria). For about 200 publications with at least a medium score, we extract the vulnerabilities, methods, and tools addressed, among other data. In a second step, we synthesize and structure the data into a classification of both the smart contract weaknesses and the analysis methods. Furthermore, we give an overview of tools and benchmarks used to evaluate tools. Finally, we provide a detailed discussion.
Kelechi G. Eze, Cajetan M. Akujuobi, Shermar Hunter, Shumon , Alam · 6 authors
The Internet of Things (IoT) is growing at a very fast pace and being increasingly adopted in many scenarios of industrial applications such as energy (smart grid), automobile (smart cars), healthcare (smart healthcare), manufacturing (smart manufacturing and supply chain) and other application such as homes (smart home) and cities (smart city). Nonetheless, these IoT technologies (devices, systems, protocols, and applications) are faced with many security-related issues. IoT Systems have different layers that are vulnerable to various kinds of attacks. To defend against these attacks, one must consider appropriate security approaches and mechanisms to ensure privacy, security, and trust within the various components and layers that make up the IoT system. Appropriate security mechanism is needed at every layer of an IoT system to keep them secure. Hence, finding suitable mechanism for each IoT layer is a necessity to keep IoT systems secure in the 21st-century applications and implementations. The paper first investigates the IoT layers and protocols, their vulnerability issues, and methods to resolve the issues from existing literatures. We then present a blockchain-based security architecture for the internet of things and practically investigated its security feature through implementation of various security mechanism. Analysis and discussion of the blockchain implementation results are carried for the purpose of meeting the security, privacy, and trust requirements of IoT.
Alessandra Rizzardi, Sabrina Sicari, Daniele Miorandi, Alberto Coen‐Porisini
Abstract Security and privacy of information transmitted among the devices involved in an Internet of Things (IoT) network represent relevant issues in IoT contexts. Guaranteeing effective control and supervising access permissions to IoT applications is a complex task, mainly due to resources' heterogeneity and scalability requirements. The design and development of highly customizable access control policies, along with an efficient mechanism for ensuring that the rules applied by the IoT platform are not tampered with or violated, will undoubtedly have a significant impact on the diffusion of IoT‐based solutions. In such a direction, the article proposes the integration of a permissioned blockchain within an honest‐but‐curious (i.e., not trusted) IoT distributed middleware layer, which aims to guarantee the correct management of access to resources by the interested parties. The result is a robust and lightweight system, able to manage the data produced by IoT devices, support relevant security features, such as integrity and confidentiality, and resist different kinds of attacks. The use of blockchain will ensure the tamper‐resistance and synchronization of the distributed system, where various stakeholders own applications and IoT platforms. The methodology and the proposed architecture are validated employing a test‐bed.
A secure electronic learning platform has been created to enable teachers and students to log into their accounts to learn efficiently and safely at any place and time. This platform has been proposed due to the urgent need to develop the education system and move it from traditional to interactive e-learning. In this paper, an application implemented that access remotely using a web browser interface and saved on a server depends on a Zero-Knowledge Proof (ZKP) system with an RSA algorithm was employed to solve registration and login challenges and securely transfer passwords. Using adapted AES to encrypt each user's personal information, Exams, and save it in in encrypted form in the database. The simulated results in this paper indicate the existence of a secure e-learning system, where security was achieved by performing the registration and login process without sending the password in its explicit form over an insecure network such as the Internet, in addition to encrypting the necessary information to be stored in an incomprehensible manner in the database, in the case of presence of an attack on the database.
With the rapid development of the informatization and industrialization of the Internet of Vehicles (IoV), the number and application of connected vehicles are growing rapidly. The safety problem is related to the property and life of human beings, which has attracted extensive attention from academic and industrial circles. Based on the study of high-quality literature published in the past decade and other high-level research works, this paper first analyzes the forms of attack against the Internet of Vehicles from the two aspects of attack mode and target. Then, it summarizes the existing blockchain-based system framework of the Internet of Vehicles (BIoV) and then discusses the security solutions of blockchain-based vehicles from the aspects of authentication, privacy, trust management, access control, and so on, to support the distributed system architecture and solve the security challenges of the Internet of Vehicles. Finally, the technical difficulties and the direction of further research of BIoV are summarized.
The first special section is dedicated to Edge Consumer Electronics (ECE) that include gadgets or appliances, equipped with contemporary circuitry to carry out domestic tasks. They are designed and used exclusively for communication, entertainment, safety, and home-office endeavors. The abundance of consumer electronics is indebted to the semiconductor and appliance of related software solutions. T
Developing secure smart contracts remains a challenging task. Existing approaches are either impractical or leave the burden to developers for fixing bugs. In this paper, we propose the first practical smart contract compiler, called HCC, which automatically inserts security hardening checks at the source-code level based on a novel and language-independent code property graph (CPG) notation. The high expressiveness of our developed CPG allows us to mitigate all of the most common smart contract vulnerabilities, namely reentrancy, integer bugs, suicidal smart contracts, improper use of tx.origin, untrusted delegate-calls, and unchecked low-level call bugs. Our large-scale evaluation on 10k real-world contracts and several sets of vulnerable contracts from related work demonstrates that HCC is highly practical, outperforms state-of-the-art contract hardening techniques, and effectively prevents all verified attack transactions without hampering functional correctness.
Ethereum Smart Contracts based on Blockchain Technology (BT) enables monetary transactions among peers on a blockchain network independent of a central authorizing agency. Ethereum Smart Contracts are programs that are deployed as decentralized applications, having the building blocks of the blockchain consensus protocol. This enables consumers to make agreements in a transparent and conflict-free environment. However, there exist some security vulnerabilities within these smart contracts that are a potential threat to the applications and their consumers and have shown in the past to cause huge financial losses. This paper presents a framework and empirical analysis that use code clone detection techniques for identifying vulnerabilities and their variations in smart contracts. Our empirical analysis is conducted using the Nicad code clone detection tool on a dataset of approximately 50k Ethereum smart contracts. We evaluated VOLCANO on two datasets, one with confirmed vulnerabilities and another with approximately 50k random smart contracts collected from the Etherscan. Our approach shows an improvement in the detection of vulnerabilities in terms of coverage and efficiency when compared to two of the publicly available static analyzers to detect vulnerabilities in smart contracts. To the best of our knowledge, this is the first study that uses a clone detection technique to identify vulnerabilities and their evolution in Ethereum smart contracts.
Vehicular Ad-hoc networks (VANETs) during the communication process, nodes are always varying and the process is always under security threats like Sybil attacks, masquerading attacks, etc. In order to reduce the probability of these attacks and to regulate traffic flow in the network, a software-defined network (SDN) is used. The SDN is used for implementing protocols like OpenFlow and reducing the routing load in the network, but it doesn’t provide a high level of security to the network, hence protocols like encryption, hashing, etc. are applied to the VANET. In the paper, SDN based blockchain-inspired algorithm is implemented, which coordinates network traffic and improves the overall security of the network. Security analysis of the proposed algorithm shows that the combination of blockchain with encrypted SDN is removing more than 95% of the network attacks as compared to its non-blockchain counterparts.
Abstract The recent years have garnered huge attention towards the Internet of Things (IoT) because it enables its consumers to improve their lifestyles and professionally keep up with the technological advancements in the cyber-physical world. The IoT edge devices are heterogeneous in terms of the technology they are built on and the storage file formats used. These devices require highly secure modes of mutual authentication to authenticate each other before actually sending the data. Mutual authentication is a very important aspect of peer-to-peer communication. Secure session keys enable these resource-constrained devices to authenticate each other. After successful authentication, a device can be authorized and can be granted access to shared resources. The need for validating a device requesting data transfer to avoid data privacy breaches that may compromise confidentiality and integrity. Blockchain and artificial intelligence (AI) both are extensively being used as an integrated part of IoT networks for security enhancements. Blockchain provides a decentralized mechanism to store validated session keys that can be allotted to the network devices. Blockchain is also used to load balance the stressing edge devices during low battery levels. AI on the other hand provides better learning and adaptiveness towards IoT attacks. The integration of newer technologies in IoT key management yields enhanced security features. In this article, we systematically survey recent trending technologies from an IoT security point of view and discuss traditional key security mechanisms. This article delivers a comprehensive quality study for researchers on authentication and session keys, integrating IoT with blockchain and AI-based authentication in cybersecurity.
In recent years, the number of smart contracts running in the blockchain has increased rapidly, accompanied by many security problems, such as vulnerability propagation caused by code reuse or vicious transaction caused by malicious contract deployment, for example. Most smart contracts do not publish the source code, but only the bytecode. Based on the research of bytecode similarity of smart contract, smart contract upgrade, vulnerability search and malicious contract analysis can be carried out. The difficulty of bytecode similarity research is that different compilation versions and optimization options lead to the diversification of bytecode of the same source code. This paper presents a solution, including a series of methods to measure the similarity of smart contract bytecode. Starting from the opcode of smart contract, a method of pre-training the basic block sequence of smart contract is proposed, which can embed the basic block vector. Positive samples were obtained by basic block marking, and the negative sampling method is improved. After these works, we put the obtained positive samples, negative samples and basic blocks themselves into the triplet network composed of transformers. Our solution can obtain evaluation results with an accuracy of 97.8%, so that the basic block sequence of optimized and unoptimized options can be transformed into each other. At the same time, the instructions are normalized, and the order of compiled version instructions is normalized. Experiments show that our solution can effectively reduce the bytecode difference caused by optimization options and compiler version, and improve the accuracy by 1.4% compared with the existing work. We provide a data set covering 64 currently used Solidity compilers, including one million basic block pairs extracted from them.
Luís T. A. N. Brandão, Carlos Galhardo, René Peralta
Abstract Software-controlled measuring instruments used in commercial transactions, such as fuel dispensers and smart meters, are sometimes subject to “memory replacement” attacks. Cybercriminals replace the approved software by a malicious one that then tampers with measurement results, inflicting a financial loss to customers and companies. To mitigate such attacks, legal metrology systems often require regular device attestation, where an auditor checks that the device possesses (“knows”) the approved software. However, current attestation methods usually require the software to be known by the auditor, thus increasing the risk of inadvertent leakage or malicious theft of proprietary information, besides facilitating its malicious adulteration. We describe how this issue can be addressed in legal metrology systems by using zero-knowledge proofs of knowledge (ZKPoK). These proofs enable attestation of possession of approved software, while ensuring its confidentiality from the auditor. To further provide publicly verifiable evidence of freshness, each such proof can be related to a fresh random value from a public randomness beacon. This article presents the basic conceptual idea, while also discussing pitfalls that should be avoided.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
Rajasekhar Chaganti, Bharat Bhushan, Vinayakumar Ravi
With the proliferation of new technologies such as Internet of Things (IOT) and Software-Defined Networking(SDN) in the recent years, the distributed denial of service (DDoS)attack vector has broadened and opened new opportunities for more sophisticated DDoS attacks on the targeted victims. The new attack vector includes unsecured and vulnerable IoT devices connected to the internet, denial of service vulnerabilities like southbound channel saturation in the SDN architecture. Given the high-volume and pervasive nature of these attacks, it is beneficial for stakeholders to collaborate in detecting and mitigating the denial of service attacks in a timely manner. The blockchain technology is considered to improve the security aspects owing to the decentralized design, secured distributed storage and privacy. A thorough exploration and classification of blockchain techniques used for DDoS attack mitigation is not explored in the prior art. This paper reviews and categorizes the existed state-of-the-art DDoS mitigation solutions based on blockchain technology. The DDoS mitigation techniques are classified based on the solution deployment location i.e. network based, near attacker location, near victim location and hybrid solutions in the network architecture with emphasis on the IoT and SDN architectures. Additionally, based on our study, the research challenges and future directions to implement the blockchain based DDoS mitigation solutions are discussed. We believe that this paper could serve as a starting point and reference resource for future researchers working on denial of service attacks detection and mitigation using blockchain technology.
Wenjuan Li, Yu Wang, Weizhi Meng, Jin Li · 5 authors
To safeguard critical services and assets in a distributed environment, collaborative intrusion detection systems (CIDSs) are usually adopted to share necessary data and information among various nodes, and enhance the detection capability. For simplifying the network management, software defined networking (SDN) is an emerging platform that decouples the controller plane from the data plane. Intuitively, SDN can help lighten the management complexity in CIDSs, and a CIDS can protect the security of SDN. In practical implementation, trust management is an important approach to help identify insider attacks (or malicious nodes) in CIDSs, but the challenge is how to ensure the data integrity when evaluating the reputation of a node. Motivated by the recent development of blockchain technology, in this work, we design BlockCSDN — a framework of blockchain-based collaborative intrusion detection in SDN, and take the challenge-based CIDS as a study. The experimental results under both external and internal attacks indicate that using blockchain technology can benefit the robustness and security of CIDSs and SDN.
Internet of Things (IoT) devices are widely used in many industries including smart cities, smart agriculture, smart medical, smart logistics, etc. However, Distributed Denial of Service (DDoS) attacks pose a serious threat to the security of IoT. Attackers can easily exploit the vulnerabilities of IoT devices and control them as part of botnets to launch DDoS attacks. This is because IoT devices are resource-constrained with limited memory and computing resources. As an emerging technology, Blockchain has the potential to solve the security issues in IoT. Therefore, it is important to analyse various Blockchain-based solutions to mitigate DDoS attacks in IoT. In this survey, a detailed survey of various Blockchain-based solutions to mitigate DDoS attacks in IoT is carried out. First, we discuss how the IoT networks are vulnerable to DDoS attacks, its impact over IoT networks and associated services, the use of Blockchain as a potential technology to address DDoS attacks, in addition to challenges of Blockchain implementation in IoT. We then discuss various existing Blockchain-based solutions to mitigate the DDoS attacks in the IoT environment. Then, we classify existing Blockchain-based solutions into four categories i.e., Distributed Architecture-based solutions, Access Management-based solutions, Traffic Control-based solutions and the Ethereum Platform-based solutions. All the solutions are critically evaluated in terms of their working principles, the DDoS defense mechanism (i.e., prevention, detection, reaction), strengths and weaknesses. Finally, we discuss future research directions that can be explored to design and develop better Blockchain-based solutions to mitigate DDoS attacks in IoT.
Jusop Choi, Wonseok Choi, William Aiken, Hyoungshick Kim · 8 authors
Since Bitcoin appeared in 2009, over 6,000 different cryptocurrency projects have followed. The cryptocurrency world may be the only technology where a massive number of competitors offer similar services yet claim unique benefits, including scalability, fast transactions, and security. But are these projects really offering unique features and significant enhancements over their competitors? To answer this question, we conducted a large-scale empirical analysis of code maintenance activities, originality and security across 592 crypto projects. We found that about half of these projects have not been updated for the last six months; over two years, about three-quarters of them disappeared, or were reported as scams or inactive. We also investigated whether 11 security vulnerabilities patched in Bitcoin were also patched in other projects. We found that about 80% of 510 C-language-based cryptocurrency projects have at least one unpatched vulnerability, and the mean time taken to fix the vulnerability is 237.8 days. Among those 510 altcoins, we found that at least 157 altcoins are likely to have been forked from Bitcoin, about a third of them containing only slight changes from the Bitcoin version from which they were forked. As case studies, we did a deep dive into 20 altcoins (e.g., Litecoin, FujiCoin, and Feathercoin) similar to the version of Bitcoin used for the fork. About half of them did not make any technically meaningful change - failing to comply with the promises (e.g., about using Proof of Stake) made in their whitepapers.
Cryptocurrencies have completely altered the digital transaction process all over the globe. Almost a decade after Satoshi Nakamoto generated the first Bitcoin block; many cryptocurrencies have been established. The Ransomware attack is a type of cybercrime and a class of malware that encrypts the files and prevents users from accessing their data or systems and demands payment for decrypting and retrieving access to their files. Ransomware data classification using present data mining and machine learning methods is difficult because predictions aren't always correct. We aim to build two models that effectively address these challenges and can diagnose and classify Ransomware attacks accurately, then compare the performance of the models. In this paper, we investigated the use of Rule-Based algorithms for mining Bitcoin Ransomware Data to classify Ransomware attacks in Bitcoin transactions. Employing Rule-Based techniques in detecting Bitcoin data is beneficial because the algorithms effectively classify non-linear datasets. The analysis was done on a Bitcoin dataset for 61,004 addresses selected from 29 Ransomware families and contained ten descriptive and decision attributes. Both Rule-Based algorithms were illustrated and compared on the dataset employing 10-fold cross-validation. Experimental results show that classification under partial decision tree (PART) algorithm performed better in different metrics than the Decision Table algorithm. It provides an accuracy of 96.01%, a recall of 96%, a precision of 95.9%, and an F-Measure of 95.6%. Experimental results propose that it is beneficial to further investigate the application of PART to predictive modelling tasks in Ransomware studies.
Internet of Things (IoT) device security is one of the crucial topics in the field of information security. IoT devices are often protected securely through firmware update. Traditional update methods have their shortcomings, such as bandwidth limitation and being attackers' easy targets. Although many scholars proposed a variety of methods that are based on the blockchain technology to update the firmware, there are still demerits existing in their schemes, including large storage space and centralized stored firmware. In summary, this research proposes a highly secure and efficient protection mechanism that is based on the blockchain technology to improve the above disadvantages. Therefore, this study can reduce the need of storage space and improve system security. The proposed system has good performance in some events, including firmware integrity, security of IoT device connection, system security, and device anonymity. Furthermore, we confirm the high security and practical feasibility of the proposed system by comparing with the existing methods.