With the rapid development of cloud computing, more and more users tend to store their data remotely to the cloud. Taking into account data security and resource utilization comprehensively, in addition to providing users with basic remote data integrity verification, cloud servers also need to conduct redundancy checks. However, current deduplication schemes primarily focus on static file-level data and auditing processes, rendering them inadequate for managing resources with dynamic attributes. In this paper, we propose a fine-grained deduplication and dynamic auditing model (FiDD) for cloud storage to address these challenges. FiDD utilizes homomorphic verifier-based data tags to seamlessly integrate deduplication and auditing processes, allowing both block-level and file-level deduplications. Additionally, FiDD employs doubly linked lists and multi-set hash functions to enhance the efficiency of data updates. The security of FiDD is validated through rigorous security proofs, while its efficiency is demonstrated through comprehensive experimental analysis. The experiments demonstrate an average improvement of at least 35% in audit efficiency and at least 50% in dynamics efficiency. Consequently, FiDD enhanes the security of data management in cloud computing while improving its overall efficiency.

Abstract In cloud storage, deduplication techniques are essential for improving storage capacity. Low-entropy data, due to its predictable structure, pose security risks and challenges for convergent encryption, which can compromise semantic security and increase the likelihood of information leakage. To address these issues, robust auditing mechanisms tailored for low-entropy data are essential. Although double-layer encryption strategies have been suggested to enhance security, they often introduce significant overhead and do not ensure ownership verification or auditing for low-entropy data. To address these limitations, we propose BDEA, a blockchain-based secure deduplication scheme specifically designed for low-entropy data that improves security while enabling public auditing capabilities. BDEA employs advanced technologies such as random keys, Bloom filters, and chameleon hash functions to facilitate secure and efficient deduplication processes tailored for low-entropy datasets. The integration of blockchain technology with Rivest-Shamir-Adleman (RSA) signatures enhances the security and transparency of data integrity audits in cloud environments. Security analysis confirms the robustness of the BDEA scheme, while experimental results demonstrate its effectiveness. In Ubuntu 20.04, this scheme achieves approximately an 80% reduction in deduplication processes and a 70% decrease in audit verification time when applied to datasets ranging from 2 to 16 MB at intervals of 2 MB.

Blockchain technology, known for its immutable distributed ledger, which greatly improves the credibility of data management in various applications. However, the immutability may result in erroneous data being permanently stored in the blockchain, affecting the security of the blockchain system. To address this issue, redactable blockchain is proposed to allow flexibly modifications of erroneous data in blockchain. Despite their promise, current redactable blockchain solutions often fall short in balancing two critical aspects: decentralization and data accountability. In this paper, we propose a Decentralized, Accountable and Redactable Blockchain solution (DARB). Our solution aims to mitigate the risks associated with central authority while ensuring secure accountability in data modification processes. Decentralization is achieved by using authorized authorities instead of the central authority, utilizing decentralized ciphertext policy attribute-based encryption. Additionally, it incorporates traceable ring signatures, which enable the authorized authorities to collaborate effectively in holding edited data accountable and tracing the identity of malicious modifiers. The security analysis and experimental results demonstrate that the DARB scheme successfully facilitates secure data rewriting and ensures accountability, all while maintaining an acceptable level of additional time overhead.

Payment channels (PC) greatly improve blockchain scalability by allowing an unlimited number of off-chain transactions instead of committing every transaction to the blockchain. However, the payment channel structure is limited to only two nodes, which is inadequate in scenarios where one node frequently receives money from multiple nodes, such as Cafe. Recent proposals have extended the 2-node structure to a multi-node structure. Unfortunately, these approaches either require all participants to always be online, which is not realistic, or underestimate the efficiency problem of withdrawing funds, leading to higher fees and storage costs. What’s worse, the payment scope in these proposals is limited to their respective structures and is not mutually compatible. In this paper, we propose MPC+, a smart contract that enables multiple nodes to engage in off-chain transactions. MPC+ is designed to cater to scenarios where one node frequently receives money from multiple nodes, such as Cafe, shops, and more. The nodes in MPC+ can conduct off-chain transactions internally or with nodes in existing payment channel networks externally, and they only need to be online during off-chain transactions. Furthermore, MPC+ enhances the withdrawal logic through a binding strategy, effectively reducing the number of on-chain transactions required for fund withdrawals from O(n) to O(1), and it works over any blockchain system that supports Turing-complete smart contracts. The security is formally proven under the Universal Composability framework, and it is specifically implemented on the Ethereum platform. The experimental results clearly demonstrate that MPC+ surpasses other designs in terms of fees and storage costs.

In the Cyber-Physical-Social System (CPSS), mobile service applications share and exchange data in the cyberspace and physical world. With the explosive growth of data, cloud storage service is introduced as it has broken through the limitations of local storage space. However, since cloud storage servers may remove some data to deceive users to save space, it is important to check the integrity of data in cloud storage servers. Most existing verification schemes support users to delegate a semi-trusted entity third-party auditor (TPA) to audit the stored data publicly, but it may result in user data security risks for its interests. The security risk is one aspect, what is worse, the high overhead of auditing also limits the the practicality of auditing. To tackle the issues, we put forward a secure dynamic public audit scheme based on blockchain and a red-black tree structure. Unlike relying on any single TPA, every user on the blockchain can act as an auditor to achieve public auditing. Secondly, based on the red-black tree, a new storage structure is proposed to store data signatures, which achieves efficient data storage and auditing. Based on the raised prototype system, we prove the security of our scheme and implement it on Hyperledger Fabric. Many experiments indicate that the scheme achieves the expected efficacy.

Payment channel (PC) greatly improves blockchain scalability by allowing an unlimited number of off-chain transactions instead of committing every transaction to the blockchain. However, one PC just confines to two nodes. Thus, for a node, like Cafe, who frequently receives money from multiple nodes, massive PCs need to be created, which leads to massively and repeatedly information addition of channels to the blockchain and costs much fees. In this paper, we introduce a multi-node payment channel (MPC) method to solve the problem above. MPC suits the scenario that one node frequently receives money from multiple nodes, such as Cafe, shop, etc. Compared to PC, MPC can contain nearly unlimited number of nodes, thus avoiding repetitive channel information addition to the blockchain and meanwhile reducing the fee. MPC supports the same transaction logic of PC and cooperates well with existing PC. The security, economy and efficiency of MPC are proved. We implement MPC’s smart contract in Ethereum and experimental results show that MPC outperforms the existing PC.

Abstract The recognition of malware in network traffic is an important research problem. However, existing solutions addressing this problem rely heavily on the source code and misrecognise vulnerabilities (i.e. incur a high false positive rate (FPR)) in some cases. In this paper, we initially use the K‐means clustering algorithm to extract malware patterns under user to root attacks in network traffic. Since the traditional K‐means algorithm needs to determine the number of clusters in advance and it is easily affected by the initial cluster centres, we propose an improved K‐means clustering algorithm (NIKClustering algorithm) for cluster analysis. Furthermore, we propose the use of self‐similarity and our improved clustering algorithm to recognise buffer overflow vulnerabilities for malware in network traffic. This motivates us to design and implement a recognition approach for buffer overflow vulnerabilities based on self‐similarity and our improved clustering algorithm, called Reliable Self‐Similarity with Improved K‐means Clustering (RSS‐IKClustering). Extensive experiments conducted on two different datasets demonstrate that the RSS‐IKClustering can achieve much fewer false positives than other notable approaches while increasing accuracy. We further apply our RSS‐IKClustering approach on a public dataset (Center for Applied Internet Data Analysis), which also exhibited a high accuracy and low FPR of 96% and 1.5%, respectively.

As one of the most frequently used Internet-of-Things (IoT) devices, energy smart meter has been widely adopted to facilitate the measures of residential energy use. Residents pay for the bills from energy suppliers according to their monthly/seasonal usage. Practically, there is a demand from residents/governments to check whether the bills are in line with their real consumptions. However, it is challenging to realize this demand due to two critical problems. The first problem refers to the nonrepudiated privacy issue caused by access to residents’ energy consumption history (e.g., data integrity may be questioned, and residents’ daily timetables may be exposed). The second problem comes from the efficiency requirement for bulk auditing requests on residents’ bills and consumptions, usually risen by governments. So far, we have not found any solutions that can be directly used in this case. In this article, we propose using homomorphic encryption cooperated with the blockchain technique to leverage the data auditing and privacy-preserving requirements. We also employe a certificateless signature to resolve the efficiency bottleneck in batch auditing. This framework, calledpAuditChain, not only accepts personal requests from residents for consumption checking but also handles bulk auditing requests issued by governments. To validate the correctness of the framework functions, we carried out a series of theoretical analysis, especially on the privacy preserving and auditing processes. To the best of our knowledge, the proposed framework is among the first solutions to improve the security and privacy of bills without losing the auditing function. Our approach concerns with IoT smart meters in energy supply industries and could be further extended to other forms of IoT devices with the bill demands.

Cloud storage services give users a great facility in data management such as data collection, storage and sharing, but also bring some potential security hazards. An utmost importance is how to ensure the integrity of data files stored in the cloud, particular for user groups without trusted managers. Existing literature focuses on integrity checking for groups with managers who have lots of permissions. To overcome the shortage of public auditing for non-manager user groups in clouds, we develop a novel framework IPANM that integrates$(t,n)$threshold technology, blinding technology, and incentive mechanism to realize an incentive privacy-preserving public auditing scheme. In IPANM, the data integrity is guaranteed by our$(t,n)$threshold signature based public auditing and the data privacy during public auditing is protected by the blinding technology. The generation of signatures can be accelerated by our blockchain-aided incentive mechanism that mobilizes the initiative of signers in the signature generation by rewarding the contributed signers. We formally prove the security of our IPANM and conduct numerical analysis and evaluation study to validate its high efficiency. The experimental results demonstrate that IPANM has lower overheads of storage, communication, and computation as compared to the state-of-the-art technique IAID-PDP and NPP.

To ensure data security and privacy during big data publishing, it is challenging to design a security and privacy protection scheme for the big data environment with a large scale of users. At the same time, due to the users' dynamically joining and exiting, it is also very important to design a user's dynamic update mechanism. To address such challenges, we design a novel scalable and updatable attribute-based privacy protection scheme (SUAPP) for big data publishing. The proposed scheme can realize users' hierarchical management, which can reduce the overhead on key generation and management caused by the large scale of data users in the big data center (BDC). We set a user group for each attribute, then adapt the Chinese remaining theorem to dynamically assist the big data center to generate and update group keys for the attribute users group. Analyses and experiments show that while ensuring the privacy protection of big data publishing, our scheme also has low communication and computation overhead and higher efficiency compared with two state peer schemes.

Vehicular Edge Computing (VEC) is an integration of Mobile Edge Computing with traditional vehicular networks, which aims to shift computing, communication, and storage resources to the edge of networks and is more close to vehicles. Due to the high mobility of vehicles, connection interruption and network changes may frequently occur. To tackle this issue, cache-based content delivery is regarded as a promising solution to achieve efficient data sharing in VEC. However, privacy-preserving access control and fair incentive distribution are rarely taken into account in prior VEC-oriented studies. In this paper, we propose an efficient and secure access control scheme for providing cache-based content delivery in VEC. Specifically, we construct two layer access control to enable flexible access control and fair incentive distribution with the assistance of edge nodes. Moreover, we construct a group signature-based scheme to achieve anonymous authentication and conditional revocation. The performance analysis shows that our secure scheme has an acceptable effect on network performance.

Summary In a data sharing group, each user can upload, modify, and access group files and a user is required to generate a new signature for the modified file after modification. There is a situation that two or more users modify the same file at almost the same time, which should be avoided as it gives rise to a signature conflict. However, the existing schemes do not take it into consideration. In this paper, we proposed a new mechanism SeShare for data storing based on blockchain to realize signature uniqueness, which solves the problem of generating signatures for the same file meanwhile by different group users. Specifically, we record every signature of a file in a blockchain in chronological order, and only one user is allowed to add new signature at the end of the blockchain when modification conflicts occur. On the other hand, to provide a secure data sharing service, SeShare introduces an efficient public auditing scheme for file integrity verification when a group user leaves the group. We also prove the security of the proposed scheme and evaluate the performance at the end of this paper. Our experimental results demonstrate the efficiency of public auditing for user leaving.

In data sharing schemes, the file owners should obtain rewards by sharing files with others as they put energy in these files. Therefore, we proposed an incentive data sharing scheme in this paper which encourages users to share data and also supports customization. Customization allows the owners to decide the threshold of access, the importance of each attributive classification which determines users' priority level of file modification and file ownership obtaining when the original owner leaves according to the priority level value. To support a convincing customized data sharing scheme, we introduce the knowledge of blockchain and construct a suitable access structure based on weighted attributes. The blockchain is used to ensure the fairness in incentive. Based on weighted attributes, an attribute set is disposed to a numerical value and the owner of the attribute set is able to obtain the file when the value is not less than the threshold, which is different from the normal access control policy. We prove the security from integrity, privacy and the availability of access key. The performance of the proposed scheme is evaluated at the end of this paper.

Cloud data privacy-preserving and integrity verification have become major research areas. Many existing schemes use group signatures to make sure that the data stored in cloud is unbroken for the purpose of privacy and anonymity. However, group signatures do not consider user equality and the framing caused by manager. Therefore, we propose data sharing scheme for non-manager groups, which reconstructs democratic group signature with threshold traceability to homomorphic authentication. We further present a public auditing scheme for non-manager shared data. In our scheme, group manager's rights are distributed to all members equally and some of them can work together to trace the signer if it is necessary. Besides identity privacy, data privacy, traceability and non-frameability, our scheme also ensures the efficiency and the feasibility. The experimental results show the overhead of the auditing is independent of the group user numbers and effectiveness of our approach. And thanks to the low overhead, our scheme can be further used in mobile cloud storage.