Authentication and integrity in outsourced databases

ABSTRACTIn order to verify the integrity of the query results in outsourced database model, we first present a new authenticated data structure by combining skip lists with polynomial functions and accumulators and then construct a data integrity verification scheme for range query. Our scheme can verify the integrity of the query results with constant time verification and constant size proof and support dynamic maintenance with constant computational cost. Compared with that of previous schemes, the communication cost in our scheme is independent of the size of the authenticated dataset and is lower. When dataset size gets larger enough, our scheme outperforms previous schemes in terms of the computational cost and verification cost. In addition, we introduce the designated verifier idea into our scheme, so our scheme achieves the result that none but subscribers can verify the integrity of the query results and then meets the practical demands such as the payment service. The proof of security and analysis of experiment performance show that our scheme is secure and efficient for larger outsourced databases. Copyright © 2013 John Wiley & Sons, Ltd.

The recent advancement in wireless body area networks (WBAN) plays an important role in remote health care systems. However, these networks are suffering from data security and privacy threats. Lack of anonymous authentication and secure data communication leads to operation failure in WBAN. Computational cost and privacy preservation are the two major hindrances for anonymous authentication in many existing schemes. Therefore, a secure and efficient privacy-preserving anonymous authentication scheme is proposed to provide data security and privacy to the users with low computational and communication cost. The performance analysis and experimental simulation results ensure that our proposed anonymous authentication method outperforms the existing systems in terms of providing data security and privacy with less computational overhead.

( r , QI)-Transform: Reversible Data Anonymity Based on Numeric Type of Data in Outsourced Database

A provably secure and lightweight authentication scheme for Internet of Drones for smart city surveillance

Multicopy provable data possession scheme supporting data dynamics for cloud-based Electronic Medical Record system

BD-D1Sec: Protocol of security authentication for BeiDou D1 civil navigation message based on certificateless signature

Given a set of moving objects as well as their friend relationships, a time-aware road network, and a time threshold per friend pair, the proximity detection problem in time-aware road networks is to find each pair of moving objects such that the time distance (defined as the shortest time needed for two moving objects to meet each other) between them is within the given threshold. The problem of proximity detection is often encountered in autonomous driving and traffic safety related applications, which require low-latency, real time proximity detection with relatively low communication cost. However, (i) most existing proximity detection solutions focus on the Euclidean space which cannot be used in road network space, (ii) the solutions for road networks focus on static road networks and do not consider time distance and thus cannot be applied in time-aware road networks, and (iii) there are no works aiming to simultaneously reduce the communication cost, the communication latency, and computational cost. Motivated by these, we first design a low-latency proximity detection architecture based on Mobile Edge Computing (MEC) with the purpose of achieving low communication latency, then propose a proximity detection method including a client-side algorithm and a server-side algorithm, aiming at reducing the communication cost, and subsequently propose server-side computational cost optimization techniques to reduce the computational cost. Experimental results show that our MEC enhanced proximity detection architecture, our proximity detection method, and the server-side computational cost optimization techniques can reduce the communication latency, the communication cost, and the computational cost effectively.

To localize mobile target timely and improve the accuracy of the target state estimation in wireless sensor networks, this paper presents a novel mobile target localization algorithm. By using the mean shift algorithm to construct the proposal distribution to make use of the current measurements, and weighting particles according to the virtual hamming distances in the particle filter, this proposed algorithm improves the accuracy of the target state estimation and reduces the necessary number of samples. It has lower computation and communication cost than the conventional particle filter because of more accurate state estimate of samples. Extensive simulation results confirm that this localization scheme outperforms conventional particle filter and its localization accuracy is comparable to the unscented particle filter, but its computation cost is 50% less than that of UPF.

Attribute-based encryption with keyword search (ABEKS) is a novel cryptographic paradigm that can be used to implement fine-grained access control and retrieve ciphertexts without disclosing the sensitive information. It is a perfect combination of attribute-based encryption (ABE) and public key encryption with keyword search (PEKS). Nevertheless, most of the existing ABEKS schemes have limited search capabilities and only support single or simple conjunctive keyword search. Due to the weak search capability and inaccurate search results, it is difficult to apply these schemes to practical applications. In this paper, an efficient expressive ABEKS (EABEKS) scheme supporting unbounded keyword universe over prime-order groups is designed, which supplies the expressive keyword search function supporting the logical connectives of “AND” and “OR”. The proposed scheme not only leads to low computation and communication costs, but also supports unbounded keyword universe. In the standard model, the scheme is proven to be secure under the chosen keyword attack and the chosen plaintext attack. The comparison analysis and experimental results show that it has better performance than the existing EABEKS schemes in the storage, computation and communication costs.

BPADTA: Blockchain-based privacy-preserving authentication scheme for digital twin empowered aerospace industry

We propose a new optimal data placement technique to improve the performance of MapReduce in cloud data centers by considering not only the data locality but also the global data access costs. We first conducted an analytical and experimental study to identify the performance issues of MapReduce in data centers and to show that MapReduce tasks that are involved in unexpected remote data access have much greater communication costs and execution time, and can significantly deteriorate the overall performance. Next, we formulated the problem of optimal data placement and proposed a generative model to minimize global data access cost in data centers and showed that the optimal data placement problem is NP-hard. To solve the optimal data placement problem, we propose a topology-aware heuristic algorithm by first constructing a replica-balanced distribution tree for the abstract tree structure, and then building a replica-similarity distribution tree for detail tree construction, to construct an optimal replica distribution tree. The experimental results demonstrated that our optimal data placement approach can improve the performance of MapReduce with lower communication and computation costs by effectively minimizing global data access costs, more specifically reducing unexpected remote data access.

In deduplication, index-lookup disk bottleneck is a major obstacle which limits the throughput of backup processes. One way to minimize the effect of this issue and boost speed is to use very high course-grained chunks for deduplication at a cost of low storage saving and limited scalability. Another way is to distribute the deduplication process among multiple nodes but this approach introduces storage node island effect and also incurs high communication cost. In this paper, we explore dCACH, a content-aware clustered and hierarchical deduplication system, which implements a hybrid of inline course grained and offline fine-grained distributed deduplication where routing decisions are made for a set of files instead of single files. It utilizes bloom filters for detecting similarity between a data stream and previous data streams and performs stateful routing which solves the storage node island problem. Moreover, it exploits the negligibly small amount of content shared among chunks from different file types to create groups of files and deduplicate each group in their own fingerprint index space. It implements hierarchical deduplication to reduce the size of fingerprint indexes at the global level, where only files and big sized segments are deduplicated. Locality is created and exploited first using the big sized segments deduplicated at the global level and second by routing a set of consecutive files together to one storage node. Furthermore, the use of bloom filter for similarity detection between streams has low communication and computation cost while it enables to achieve duplicate elimination performance comparable to single node deduplication. dCACH is evaluated using a prototype deployed on a server environment distributed over four separate machines. It is shown to have 10× the speed of Extreme_Binn with a minimal communication overhead, while its duplicate elimination effectiveness is on a par with a single node deduplication system.

A complete remote authentication scheme should provide the following security properties: (1) mutual authentication, (2) session key exchange, (3) protection of user anonymity, (4) support of immediate revocation capability, (5) low communication and computation cost, (6) resistance to various kinds of attacks, (7) freely choosing and securely changing passwords by users, and (8) without storing password or verification tables in servers. However, none of the existing schemes meets all the requirements. In this paper, along the line of cost effective approach using hash functions for authentication, we propose an efficient and practical remote user authentication scheme with smart cards to support the above complete security properties.

Vehicular ad-hoc networks (VANETs) are one of the most important components in an Intelligent Transportation System (ITS), which aims to provide information communication between vehicles. Safety-critical vehicular communication requires security, privacy, auditability and efficiency. To satisfy these requirements simultaneously, several conditional privacy-preserving authentication schemes are proposed by employing ring signatures. However, these methods have been paid too little attention to the issues like how to choose the valid ring members or how to set up a ring. In this paper, we introduce an efficient conditional privacy-preserving scheme which provides an appropriate approach establishing the list of ring members. Moreover, our proposed scheme also supports batch verification to significantly reduce the computational cost. According to the analysis of security, our scheme is sufficiently resistant against several common attacks in VANETs. The performance results show that the proposed scheme is efficient and practical with both low computation and communication cost.

Signal fusion-based radar target detection algorithms are studied in this article for spatial diversity multiple input multiple output (MIMO) radar based on the generalised likelihood ratio test (GLRT) algorithm, under the assumption that covariance matrices of clutter signals received by different radar sites are different. Two signal fusion-based target detection algorithms are proposed, which can be applied in signal fusion networks (SFNs) with typical structures, at a low communication and computation cost. Simulation experiments in several scenarios indicate that two proposed signal fusion algorithms have better detection performances than decision fusion algorithms.