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Big data analytics has been regarded as a promising technology to yield better insights into future development by government and industry. Data collection and aggregation are necessary pre-steps to enable data analysis. However, data may be dispersed across multiple places and in different formats. Even worse, data can be encrypted under various encryption mechanisms when data owners try to secure the confidentiality of the data. This makes data aggregation extremely challenging, if not impossible, especially when the encryption keys cannot be shared for various reasons. In this paper, we take the first step in addressing this problem. More specifically, we propose a new notion of cross-domain encryption switching service that securely bridges two well-studied encryption mechanisms, namely traditional public key encryption and identity-based encryption. As of independent interest, our notion supports keyword search over encrypted data, i.e., after encryption switching one may search over the (outsourced) data without loss of data and query secrecy. We provide a provably-secure instantiation satisfying the notion, and further present the efficiency analysis to show the scalability. Our proposed scheme may be applicable in multi-domain cloud storage system.

The demands for the fairness, security, and efficiency of the supply chain have grown significantly due to the rise of globalization. However, some problems of the information flow, logistics, and capital flow in the supply chain remain a challenge, such as the information asymmetry between upstream and downstream, substandard quality of goods, difficulty in traceability, and default of payment. Therefore, this paper proposes a blockchain-based supply chain framework (SESCF), which solves the supply chain problems securely and efficiently. First, the use of blockchain and smart contracts ensures the information symmetry in the supply chain system. Second, the radio frequency identification (RFID) provides a unique identity of goods, which helps in real-time quality monitoring. Additionally, the immutability and distributed storage of the blockchain play an important role in tracking the origin of goods. Third, the efficient payment channel is used to solve the problem of payment defaults. Furthermore, simulations of smart contracts along with the security analyses are presented in this paper. We also implement a blockchain-based supply chain system (SescfDapp), which is built upon a Consortium blockchain. Large-scale experiments and detailed analysis prove the feasibility and efficiency of our proposed system.

ABKS has drawn much attention from research and industry in recent years, an ABKS scheme is an encryption scheme that supports keyword search and access control. Attribute-Based Encryption is a public key encryption that enables users to encrypt and decrypt message based on attributes. In a typical implementation, the size of the ciphertext is proportional to the number of attributes associated with it and the decryption time is proportional to the number of attributes used during decryption. Inherit from ABE technology, the computation cost and ciphertext size in most ABKS schemes grow with the complexity of the access policy. On the other hand, we found that the traditional ABKS schemes cannot resist our secret-key-recovery attack. To deal with the above problems, we present new ciphertext policy attribute based encryption with fast keyword search constructions. Our constructions preserve the fine-grained access control inherited from the ABE system while supporting hidden policy and fast keyword search. Our constructions feature multi-value-independent compared with the existing attribute based searchable encryption schemes. The performance analysis demonstrates the efficiency of our constructions. We offer rigorous security proof of our second scheme, which is IND-CKA and IND-CPA secure.

Blockchain can be utilized to enhance both security and efficiency for location-based service (LBS) in vehicular social networks (VSNs), due to its inherent decentralization, anonymity, and trust properties. Unfortunately, the existing approaches either lack effective authentication, which is vulnerable to the man-in-the-middle attack, or require an online certificate authority (CA) where frequent interactions with resource-constrained vehicles are required. To address these challenging issues, in this article, a lightweight threshold CA for consortium blockchain along with a privacy-preserving LBS protocol in blockchain enforced VSNs is proposed. First, a lightweight threshold CA framework LTCA is proposed by devising a threshold proxy signature, where the proxy signing key is issued by a coalition of threshold number of CAs playing the roles of authorized nodes in the consortium blockchain. Without the intervene of an online CA, each vehicle in the online phase can authenticate its identity by itself each time its blockchain address (i.e., account address) is updated. Then, based on the proposed LTCA, an efficient privacy-preserving LBS protocol PPVC is contrived to protect each vehicle’s conditional identity privacy with a moderate cost. Finally, both security analysis and performance evaluation demonstrate the effectiveness and efficiency of our proposed LTCA and PPVC in blockchain enforced VSNs.

Incorporation of fog computing with low latency, preprocession (e.g., data aggregation) and location awareness, can facilitate fine-grained collection of smart metering data in smart grid and promotes the sustainability and efficiency of the grid. Recently, much attention has been paid to the research on smart grid, especially in protecting privacy and data aggregation. However, most previous works do not focus on privacy-preserving data aggregation and function computation query on enormous data simultaneously in smart grid based on fog computation. In this paper, we construct a novel verifiable privacy-preserving data collection scheme supporting multi-party computation(MPC), named VPDC-MPC, to achieve both functions simultaneously in smart grid based on fog computing. VPDC-MPC realizes verifiable secret sharing of users’ data and data aggregation without revealing individual reports via practical cryptosystem and verifiable secret sharing scheme. Besides, we propose an efficient algorithm for batch verification of share consistency and detection of error reports if the external adversaries modify the SMs’ report. Furthermore, VPDC-MPC allows both the control center and users with limited resources to obtain arbitrary arithmetic analysis (not only data aggregation) via secure multi-party computation between cloud servers in smart grid. Besides, VPDC-MPC tolerates fault of cloud servers and resists collusion. We also present security analysis and performance evaluation of our scheme, which indicates that even with tradeoff on computation and communication overhead, VPDC-MPC is practical with above features.

In recent years, the sharing economy is developing rapidly and has become a popular economic model. For example, sharing platforms such as Airbnb have gradually entered people ’s field of vision and obtained high economic benefits. However, the information managed by such a centralized platform may be used by criminals and people’s privacy may be violated. In order to achieve the goal of decentralization, we propose a blockchain-based house sharing platform. Users can directly conduct transactions on the blockchain by running smart contracts. Our scheme guarantees the anonymity of users through commitment scheme and zero-knowledge technology. In order to deal with the problems that may be encountered in reality, we propose a trusted authority to trace malicious users. In addition, our platform has reputation mechanism to restrict the behavior of users. We analyze its security and performance, and the result shows that it is feasible in reality.

Privacy-protected signal and image processing for outsourced computing has hence recently been popular. We present a framework for privacy-preserving outsourced image feature Extraction(POIFE) in the semi-honest setting. Also we prove that the construction is simulation-based secure under the semi-honest adversaries. In our scheme, the user can be flexible to outsource his computation to the cloud without real-time online. Compared with the previous works, our solution improves privacy.

Ride-hailing service is gaining an increasing popularity due to its great advantages on fare estimation, automatic payments, and reputation ratings. However, how to build the trust between the driver and the passenger and achieve the secure billing still remains an open challenge. This paper proposes a novel secure billing protocol which removes the presence of the online third party by a smart contract on a publicly-verifiable two-party blockchain. In the proposed secure billing protocol, the driver and the passenger generate a blockchain which contains information about the ride. The driver and the passenger measure their own trajectories respectively in rounds. At the end of each round, they exchange their trajectories of the current round. If the difference of trajectories is within a threshold, they jointly compute the fare of current round. After completing the computation, the passenger pays the driver the fare of the current round via a micropayment channel. The driver and the passenger end each round by adding the information generated in this round into the blockchain. The blockchain can be considered as an evidence of the ride since it contains all the information of the ride. We evaluate the performance and the effectiveness of the proposed protocol via extensive experiments and detailed analysis.

Searchable Symmetric Encryption(SSE) remains to be one of the hot topics in the field of cloud storage technology. However, malicious servers may return incorrect search results intentionally, which will bring significant security risks to users. Therefore, verifiable searchable encryption emerged. In the meantime, single-keyword query limits the applications of searchable encryption. Accordingly, more expressive searchable encryption schemes are desirable. In this paper, we propose a verifiable conjunctive keyword search scheme based on Cuckoo filter (VCKSCF), which significantly reduces verification and storage overhead. Security analysis indicates that the proposed scheme achieves security in the face of indistinguishability under chosen keyword attack and the unforgeability of proofs and search tokens. Meanwhile, the experimental evaluation demonstrates that it achieves preferable performance in real-world settings.

Attribute-based encryption received widespread attention as soon as it proposes. However, due to its specific characteristics, the attribute-based access control method is not flexible enough in actual operation. In addition, since access authorities are determined according to users' attributes, users sharing the same attributes are difficult to distinguish. Once a malicious user makes illicit gains by their decryption authorities, it is difficult to trace specific users. This paper follows the practical demand to propose a more flexible key-policy attribute-based encryption scheme with black-box traceability. The scheme has a constant number of constant parameters which can be utilized to construct attribute-related parameters flexibly, and the method of traitor tracing in broadcast encryption is introduced to achieve effective malicious user tracing. In addition, the security and feasibility can be proved by the security proofs and performance evaluation in this paper.

Images play an increasingly important role in our lives as carriers of Information. At the same time, personal devices are increasingly unable to store and compute large amounts of images, so it is necessary to outsource to cloud servers. However, this also brings privacy issues, such as personal photos, medical photos, map mapping, etc. In this paper, we present a content-based image retrieval (CBIR) scheme that can be performed on ciphertext images. In order to better represent the Lage, instead of the traditional algorithms such as SIFT and HOG, image features are extracted using fine-tuned convolutional neural networks, and then outsources the encrypted feature vector and ciphertext image to cloud server. Considering the efficiency of the search, this paper uses the k-means algorithm to and local sensitive hash function to build a secure tree index. This paper proposes a new functional encryption of the inner product to calculate the Euclidean distance between the feature vectors to obtain the similarity between the images, and finally return the ciphertext image satisfying the condition to the user. The experimental results show the efficiency of our program, in addition, the paper gives security analysis to prove that our solution can against Chosen-Plaintext Attack (CPA).

The application of smart grids helps optimize electric dispatching and troubleshoot power interruption. Although it provides convenience to our lives, it also causes certain security risks. At present, open wireless sensor network is adopted in smart grids and is vulnerable to cyber attacks, resulting in network congestion and leakage of users' private information. Therefore, an attacker may infer users' identities, behavior and preferences by analyzing the real-time power consumption, which is an immediate threat to the users' privacy. To address this issue, we propose a privacy-preserving scheme based on blockchain and group signature to protect the privacy of users' identities while enhancing the security of power systems. On one hand, smart meters serve as nodes in the blockchain system and ensure data consistency through consensus mechanism. On the other hand, as group members, smart meters make sure of the anonymity of end-users by generating group signatures for power data. Security analysis shows that, our scheme achieves security in terms of privacy preserving, transaction verification and traceability, and is secure against common cyber attacks. In addition, the performance analysis shows that the proposed scheme is practical in the sense of consensus delay and throughput.

With the development of technology, the preservation of digital evidence becomes increasingly important in case investigations. To maintain the authenticity of an evidence, its entire lifecycle has to be recorded. In addition, traditional database technologies are not able to maintain the integrity and authenticity of digital evidence. In order to achieve authentication and integrity, as well as confidentiality, of digital evidence, we propose a protocol for digital evidence chain of custody based on revocable ciphertextpolicy attribute-based encryption, BLS signature, and blockchain technology. In our protocol, attribute-based encryption is used to achieve fine-grained access control and BLS signature is used to verify digital evidence. Besides, we use blockchain technology to ensure the integrity and traceability of digital evidence. Analysis and experimental results show that the proposed protocol, which well balances the privacy and the traceability, guarantees the integrity and validity of evidence.

Ciphertext-policy attribute-based encryption (CP-ABE) has been proposed to enable fine-grained access control on encrypted data for cloud storage service. In the context of CP-ABE, since the decryption privilege is shared by multiple users who have the same attributes, it is difficult to identify the original key owner when given an exposed key. This leaves the malicious cloud users a chance to leak their access credentials to outsourced data in clouds for profits without the risk of being caught, which severely damages data security. To address this problem, we add the property of traceability to the conventional CP-ABE. To catch people leaking their access credentials to outsourced data in clouds for profits effectively, in this paper, we first propose two kinds of non-interactive commitments for traitor tracing. Then we present a fully secure traceable CP-ABE system for cloud storage service from the proposed commitment. Our proposed commitments for traitor tracing may be of independent interest, as they are both pairing-friendly and homomorphic. We also provide extensive experimental results to confirm the feasibility and efficiency of the proposed solution.

With the booming Internet industry, users' demand for resources is also increasing. In order to meet the needs of users, cloud computing came into being. In today's era, cloud storage is already the most popular application in cloud computing, and users are increasingly inclined to store important and private information in the cloud. One of the most common methods is to encrypt the information before uploading it to the cloud, but searching the information it needs in the cloud server becomes an obstacle, and symmetric searchable encryption can help users achieve this. In this paper, we design a verifiable method based on an efficient symmetric searchable encryption scheme to verify the correctness of search results returned by the cloud server. Through safety analysis and performance evaluation tests, we demonstrate that our solutions are safe and effective.

With the increasing popularity of publish-subscribe systems in the cloud environment, it is of great value to implement an efficient and secure searchable and encrypted publishing subscription scheme with dynamic attributes in a cloud environment. In a publish-subscribe system, it is very important that the user's attributes can be dynamically changed. Most existing schemes which combine searchable encryption with attribute base encryption do not take real-time changes to user attributes into account or are inefficient. To address these problems, we propose a revocable publish-subscribe scheme (RPS) using CP-ABE with efficient attribute and user revocation capability for cloud systems. RPS supports multiple publishers and subscribers, and protects data from access of unauthorized users and cloud server. In addition, it also protects the privacy of the subscription policy, privacy of the uploaded data and keywords, and is forward and backward secure.

A key challenge to design searchable encryption in multi-user setting lies in the efficient management of encryption and search keys. Existing multi-user searchable encryption schemes either extend the single-user searchable encryption framework with broadcast encryption or require search user refers to the data owner and get the search token. However, this implies the necessity that the data owner distributes a single shared secret key among the group of users or requires the data owner stay online to authorize other users to search. In this paper, we address this practical problem, which is neglected in the literature. We also study secret-key-recovery attack where a malicious user can deduce a valid secret when given a search token. We show such attack violates secret key privacy, which is important in the whole system. Inspired by asymmetric group key agreement and multilinear map technology, we provide a secure and efficient encrypted keyword search scheme for multi-user setting, in which a data owner can share data with a group users without knowing which user in the group. In the proposed scheme, (a) each user has his own secret key, (b) each user generates trapdoors without getting any help from data owner or the third party, (c) our scheme features constant communication overhead, and (d) our scheme resist the secret-key-recovery attack. Our scheme preserves the traceability inherited from the asymmetric group key agreement system. We offer rigorous security proof of our scheme, and the performance analysis demonstrates the efficiency of our scheme.

As a sophisticated mechanism for secure fine-grained access control over encrypted data, ciphertext-policy attribute-based encryption (CP-ABE) is one of the highly promising candidates for cloud computing applications. However, there exist two main long-lasting open problems of CP-ABE that may limit its wide deployment in commercial applications. One is that decryption yields expensive pairing cost which often grows with the increase of access policy size. The other is that one is granted access privilege for unlimited times as long as his attribute set satisfies the access policy of a given ciphertext. Such powerful access rights, which are provided by CP-ABE, may be undesirable in real-world applications (e.g., pay-as-you-use). To address the above drawbacks, in this paper, we propose a new notion called auditable $\sigma $ -time outsourced CP-ABE , which is believed to be applicable to cloud computing. In our notion, expensive pairing operation incurred by decryption is offloaded to cloud and meanwhile, the correctness of the operation can be audited efficiently. Moreover, the notion provides $\sigma $ -time fine-grained access control . The cloud service provider may limit a particular set of users to enjoy access privilege for at most $\sigma $ times within a specified period. As of independent interest, the notion also captures key-leakage resistance . The leakage of a user’s decryption key does not help a malicious third party in decrypting the ciphertexts belonging to the user. We design a concrete construction (satisfying our notion) in the key encapsulation mechanism setting based on Rouselakis and Waters (prime order) CP-ABE, and further present security and extensive experimental analysis to highlight the scalability and efficiency of our construction.

Ciphertext-policy attribute-based encryption, denoted by CP-ABE, extends identity based encryption by taking a set of attributes as users’ public key which enables scalable access control over outsourced data in cloud storage services. However, a decryption key corresponding to an attribute set may be owned by multiple users. Then, malicious users are subjectively willing to share their decryption keys for profits. In addition, the authority who issues decryption keys in CP-ABE system is able to generate arbitrary decryption key for any (including unauthorized) user. Key abuses of both malicious users and the authority have been regarded as one of the major obstacles to deploy CP-ABE system in real-world commercial applications. In this paper, we try to solve these two kinds of key abuses in CP-ABE system, and propose two accountable CP-ABE schemes supporting any LSSS realizable access structures. Two proposed accountable CP-ABE schemes allow any third party (with the help of authorities if necessary) to publicly verify the identity of an exposed decryption key, allow an auditor to publicly audit whether a malicious user or authorities should be responsible for an exposed decryption key, and the key abuser can’t deny it. At last, we prove the two schemes can achieve publicly verifiable traceability and accountability.

The Internet of Things is increasingly becoming a ubiquitous computing service, requiring huge volumes of data storage and processing. Unfortunately, due to the unique characteristics of resource constraints, self-organization, and shortrange communication in IoT, it always resorts to the cloud for outsourced storage and computation, which has brought about a series of new challenging security and privacy threats. In this article, we introduce the architecture and unique security and privacy requirements for the next generation mobile technologies on cloud-based IoT, identify the inappropriateness of most existing work, and address the challenging issues of secure packet forwarding and efficient privacy preserving authentication by proposing new efficient privacy preserving data aggregation without public key homomorphic encryption. Finally, several interesting open problems are suggested with promising ideas to trigger more research efforts in this emerging area.

In our previous work, we explored the possibility of applying machine learning technique to graph partition. We use some metrics to describe the graph, rank the execution time of some graph algorithm and feed them into the machine learning models. We proved that decision tree and KNN and good models of this problem. In the paper, we go on to investigate more metrics to describe the graph after partitioning. We found that AverageDegreeNotCut is also an important metric. We improve the precision score of original machine learning models by 4.9 percent.

In this paper, we propose a revocable public key encryption with authorized keyword search (RPEAKS) scheme. In RPEAKS, data and keywords are encrypted with one public key, users without corresponding private key need authorization from the manager if they want to search through the ciphertexts. The manager authorizes users by distributing authorized tokens to them and is able to revoke a user’s search right when needed. Then we present a concrete RPEAKS construction, which is featured with constant size tokens and efficient revocation. Security analysis shows that the scheme is semantically secure against chosen keyword attack and is trapdoor unforgeability.

International audience; A number of searchable encryption schemes have been widely proposed to solve the search problem in ciphertext domain. However, most existing searchable encryption schemes are vulnerable to keyword guessing attacks. During keyword guessing attacks, with the help of the cloud, an adversary will learn what keyword a given trapdoor is searching for, which leads to the disclosure of users’ privacy information. To address this issue, we propose SDKSE-KGA: a secure dynamic keyword searchable encryption scheme which resists keyword guessing attacks. SDKSE-KGA has constant-size indexes and trapdoors and supports functionalities such as dynamic updating of keywords and files. Formal proofs show that it is Trapdoor-IND-CKA and Index-IND-CKA secure in the standard model.

The highly development of Internet and cloud computing technology makes it possible to share computing power, storage and data. Cloud computing makes users with limited computing resources be able to carry out large computational tasks with the help of cloud. but security is a major concern that hinders the widespread use of outsourcing computing. We focus on outsourcing large matrix multiplication in this paper. Firstly, we exploit Chinese Remainder Theorem(CRT) to construct a large matrix multiplication outsourcing protocol which is highly efficient in the malicious cloud model. Then formal security proof and extensive performance evaluation show that our protocol achieves a higher security level i.e., information-theoretic security for input privacy and adaptive chosen ciphertext attack (CCA2) security for output privacy). Compared with previous works, users in the proposed protocol are able to verify the results received from the cloud with tiny error rate.

Cloud computing has an significant impact on both academia and industry with its rapid development. by moving expensive operations like search to cloud, we are able to carry out complicated tasks efficiently. At the same time, cloud security has become a major concern. Malicious clouds are likely to sell privacy information for extra benefit. In order to protect privacy, data are encrypted before being uploaded to cloud. So how to handle encrypted data becomes a new challenge. In this paper we propose SDKSE: a secure dynamic keyword searchable encryption scheme for email systems under cloud computing environment. It is able to update files and keywords at any time. The indexes and the trapdoors generated in the scheme are constant size. In addition, we prove that it is adaptively Trapdoor-IND-CKA and Index-IND-CKA in the standard model.

For the first time, one new conception, multi-proxy multi-signature binding positioning protocol, is proposed. Based on the secure positioning protocol, one model of multi-proxy multi-signature binding positioning protocol is proposed. In the model, positioning protocol is bound to multi-proxy multi-signature tightly, not loosely. Further, we propose one scheme of multi-proxy multi-signature binding positioning protocol, its correctness is proved, and its security is analyzed. Copyright © 2016 John Wiley & Sons, Ltd.

Nowaday, secure cloud computation has become more and more attractive. We propose a protocol for privacy-preserving pattern matching. Then, we prove that the construction is simulation-based secure in the semi-honest setting. Finally, the efficiency analysis shows our scheme outperforms the previous works. Specially, compared with Fast' protocol our scheme is more efficient and the text owner does not need real-time online in the query phase. Thus, this protocol is flexible to query by light weight equipments such as mobile phones. Copyright © 2016 John Wiley & Sons, Ltd.

Attribute-based signcryption (ABSC) can fulfill the functionality of attribute-based signature (ABS) and attribute-based encryption (ABE) in a logical step. Depending on whether the access policy is embedded in the keys or ciphertexts, ABS and ABE are generally divided into two types: key policy and ciphertext policy. In this paper, we propose an ABSC scheme supporting key policy signature and ciphertext policy encryption, called KCP-ABSC, which is the first ABSC scheme with hybrid access policy to our known. The proposed KCP-ABSC scheme is proven to be ciphertext indistinguishability under chosen ciphertext attacks and achieves existential unforgeability under chosen message attack in the standard model. Furthermore, the size of the ciphertext in the new KCP-ABSC scheme is constant, i.e., independent of the number of attributes used in the system.

E-healthcare systems have been increasingly facilitating health condition monitoring, disease modeling and early intervention, and evidence-based medical treatment by medical text mining and image feature extraction. Owing to the resource constraint of wearable mobile devices, it is required to outsource the frequently collected personal health information (PHI) into the cloud. Unfortunately, delegating both storage and computation to the untrusted entity would bring a series of security and privacy issues. The existing work mainly focused on fine-grained privacy-preserving static medical text access and analysis, which can hardly afford the dynamic health condition fluctuation and medical image analysis. In this paper, a secure and efficient privacy-preserving dynamic medical text mining and image feature extraction scheme PPDM in cloud-assisted e-healthcare systems is proposed. Firstly, an efficient privacy-preserving fully homomorphic data aggregation is proposed, which serves the basis for our proposed PPDM. Then, an outsourced disease modeling and early intervention is achieved, respectively by devising an efficient privacy-preserving function correlation matching PPDM1 from dynamic medical text mining and designing a privacy-preserving medical image feature extraction PPDM2. Finally, the formal security proof and extensive performance evaluation demonstrate our proposed PPDM achieves a higher security level (i.e., information-theoretic security for input privacy and adaptive chosen ciphertext attack (CCA2) security for output privacy) in the honest but curious model with optimized efficiency advantage over the state-of-the-art in terms of both computational and communication overhead.

With the emerging techniques of wireless communication and cloud computing, large volumes of multimedia data are outsourced from resource-constrained users to the cloud with abundant resource for both delegated storage and computation. Unfortunately, there exists a risk of users’ image privacy leakage in the process of outsourcing to the cloud in the malicious setting. Most of the existing work achieved privacy-preserving verifiable image feature extraction and matching by using public key (fully) homomorphic encryption (FHE), and the heavy computational overhead and communication overhead cannot adapt to resource-constrained mobile devices. Other works disabled to achieve image denoising in the encrypted domain or only focused on the scale-invariant feature transform (SIFT) descriptor that is inappropriate for position-sensitive feature extraction. To address these issues, in this paper, a privacy-preserving verifiable shape context based image denoising and matching protocol PVIDM with efficient outsourcing in the malicious setting is proposed. To achieve this end, by exploiting any one-way trapdoor permutation, an efficient privacy-preserving verifiable image denoising scheme PPVID is firstly proposed to improve the accuracy of image matching, without exploiting public key FHE. Then, based on PPVID, a lightweight shape context based privacy-preserving verifiable image feature extraction and matching protocol PPVIM is devised, where secure and efficient comparison and counting protocols in the encrypted domain are respectively proposed. Both image privacy and image matching result privacy are well protected, and the correctness of image matching result can be efficiently verified. Finally, formal security proof and extensive simulations on real-world data sets demonstrate the efficiency and practicability of our proposed PVIDM. Especially, both the computational complexity for the usage of any one-way trapdoor permutation at data owner’s/user’s end and the size of the authentication tag generated by the cloud are O(1), independent to both the number of database images and the number of pixels in each image.

With rapid development and wide application of vehicular networks, data security is gradually valued. CP-ABE could be adopted based on the characteristics of vehicular networks data transmission. And short decryption keys generated in CP-ABE can reduce storage and transmission costs, as vehicles have limited storage capacity. In addition, the decryption keys are shared by multiple users whose attributes satisfy access policy in CP-ABE. So there may exist malicious key owners who have the intention to leak their decryption privilege for profit, especially when traitors cannot be traced. In this paper, we propose a traceable CP-ABE with short keys for vehicular networks. Our scheme not only provides short decryption keys and traceability of traitors, the cost of implementing traceability is also very low. Therefore, it is particularly appropriate for vehicular networks.

With highly development of cloud computing, data owners wish to outsource their data to clouds for computational and storage resource at a lower price. In order to protect the privacy of sensitive information, they should be encrypted before being uploaded to the cloud server. However, in this way, it is hard to find data in encrypted form according to search criticisms. To solve this problem, searchable encryption has merged. In this paper, we propose a secure and efficient searchable encryption scheme supporting multi-keyword search in 1-to-n setting. The scheme is mainly applicable to the scenes that the number of keywords is limited but the number of files is huge such as sharing a comprehensive knowledge base of a certain field. By tactfully leveraging multi-input inner-product functional encryption, the cloud server is able to complete search processes with search tokens which consist of only two items. It reduces communication and transportation overhead significantly. By using an inverted index structure and super-incremental sequence, our scheme achieves efficient multi-keyword search. In addition, our scheme avoids per-query interaction between the data owner and data users. That is to say, the data owner does not need to stay online waiting for data users to search in his archives. On the other hand, the scheme also achieves partial token privacy, index privacy and token privacy at the same time.

Ciphertext-policy attribute-based encryption (CP-ABE) is a promising primitive for enforcing access control policies defined by data owner on outsourced data. We propose a novel primitive called server-aided directly revocable CP-ABE with verifiable delegation, denoted by sarCP-ABE. In sarCP-ABE, the workloads about revocation are delegated to an aide-server, and the data owner only needs to generate a normal ciphertext as in a pure CP-ABE system. A user can be directly revoked by updating a public revocation list. To prevent a revoked user from decrypting, the aide server can update the aide-ciphertext with current revocation list, and an auditor can publicly check the correctness of the updated aide-ciphertext. At last, the proposed scheme can be proved selectively secure against chosen-plaintext attack on both original and updated ciphertext.

With the emerging techniques of wireless communication and cloud computing, large volumes of multimedia data are outsourced from resource constrained users to the cloud with abundant resource for both delegated storage and computation. Unfortunately, there is a risk of users’ image privacy leakage in the process of outsourcing to untrusted cloud. Most of the existing work achieved privacy-preserving image feature extraction and matching by using public key (fully) homomorphic encryption (FHE), but the heavy computational overhead and communication overhead cannot adapt to resource-constrained mobile devices. Other works disabled to realize image denoising in the encrypted domain or only focused on the scale-invariant feature transform (SIFT) descriptor that is inappropriate for position-sensitive feature extraction. To address these issues, in this paper, a privacy-preserving shape context based image denoising and matching protocol PPOIM with efficient outsourcing is proposed. Firstly, to improve the accuracy of image matching, a privacy-preserving image denoising scheme PPID is proposed without exploiting public key FHE. Then, based on PPID, a privacy-preserving image matching protocol PPOIM adopting shape context descriptor is devised, where two secure and efficient comparison and counting protocols in the encrypted domain are presented. All the original image privacy, query image privacy and image matching result privacy are well protected. Finally, formal security proof and extensive simulations on real-world data sets demonstrate the efficiency and practicability of our proposed PPOIM.

Cloud-assisted wireless body area networks (WBANs) significantly facilitate efficient patient treatment of high quality, unfortunately in the meanwhile greatly challenge the patient’s data confidentiality and privacy. The existing work mainly focused on the traditional scenario where patients securely stay indoors. In this paper, we consider a more practical situation of cloud-assisted WBANs in m-healthcare social networks where patients traverse among blocks outdoors and WBANs are more vulnerable to sophisticated attacks including even node compromise attack. To solve the problem, a secure and privacy-preserving key management scheme resilient to both time-based and location-based mobile attacks is proposed by the cooperation of the mobile patients in the same social group for both hierarchical and distributed environment. It also protects patient’s identity privacy, sensor deployment privacy and location privacy by exploiting the blinding technique and embedding human body’s symmetric structure into Blom’s symmetric key mechanism with modified proactive secret sharing. Especially, the computationally-intensive privacy-preserving key material updating is outsourced to the cloud server and the unchanged pairwise keys after key material updating dramatically saves the resources for energy-constrained WBANs. Finally, the security analysis and simulation results show our scheme far outperforms the previous ones in terms of resisting mobile attacks and storage, computation and communication overhead.

Ciphertext-policy attribute-based encryption (CP-ABE) enables fine-grained access control to the encrypted data for commercial applications. There has been significant progress in CP-ABE over the recent years because of two properties called traceability and large universe, greatly enriching the commercial applications of CP-ABE. Traceability is the ability of ABE to trace the malicious users or traitors who intentionally leak the partial or modified decryption keys for profits. Nevertheless, due to the nature of CP-ABE, it is difficult to identify the original key owner from an exposed key since the decryption privilege is shared by multiple users who have the same attributes. On the other hand, the property of large universe in ABE enlarges the practical applications by supporting flexible number of attributes. Several systems have been proposed to obtain either of the above properties. However, none of them achieve the two properties simultaneously in practice, which limits the commercial applications of CP-ABE to a certain extent. In this paper, we propose two practical large universe CP-ABE systems supporting white-box traceability. Compared with existing systems, both the two proposed systems have two advantages: 1) the number of attributes is not polynomially bounded and 2) malicious users who leak their decryption keys could be traced. Moreover, another remarkable advantage of the second proposed system is that the storage overhead for traitor tracing is constant, which are suitable for commercial applications.

Distributed m-healthcare cloud computing system significantly facilitates efficient patient treatment for medical consultation by sharing personal health information among healthcare providers. However, it brings about the challenge of keeping both the data confidentiality and patients’ identity privacy simultaneously. Many existing access control and anonymous authentication schemes cannot be straightforwardly exploited. To solve the problem, in this paper, a novel authorized accessible privacy model (AAPM) is established. Patients can authorize physicians by setting an access tree supporting flexible threshold predicates. Then, based on it, by devising a new technique of attribute-based designated verifier signature, a patient self-controllable multi-level privacy-preserving cooperative authentication scheme (PSMPA) realizing three levels of security and privacy requirement in distributed m-healthcare cloud computing system is proposed. The directly authorized physicians, the indirectly authorized physicians and the unauthorized persons in medical consultation can respectively decipher the personal health information and/or verify patients’ identities by satisfying the access tree with their own attribute sets. Finally, the formal security proof and simulation results illustrate our scheme can resist various kinds of attacks and far outperforms the previous ones in terms of computational, communication and storage overhead.

Cloud-assisted wireless wearable communications have been increasingly pervasive with the profound development of sensor, wireless communication, and cloud computing technologies, in addition to the wide adoption of e-health, location-based service, and mobile smart communities. In this article we mainly focus on the goals and tactics of privacy-preserving data aggregation in cloud-assisted wireless wearable communications. With respect to the unique security and privacy requirements and the efficiency consideration for resource-constrained wearable devices, we identify the inappropriateness of secure multiparty computation and fully homomorphic encryption and give new generalized solutions to tackle the challenging issue of efficient privacy-preserving data aggregation and outsourced computation in wireless wearable communications. Last but not least, a series of interesting open problems are suggested along with potential solutions to cast light on the research in this emerging area.

In Ciphertext-policy attribute-based encrypt- ion (CP-ABE), ciphertexts are associated with access policies, which do not have to contain the identities of eligible receivers, and attributes are shared by multiple users. CP-ABE is useful for providing fine-grained access control on encrypted data. However, it also has a practicality concern that a malicious user, with his attributes shared with other users, might leak his decryption privilege as a decryption blackbox, for some financial gain or other incentives, as there is little risk of getting caught. There are two types of decryption blackboxes that reflect different practical scenarios. A key-like decryption blackbox is associated with an attribute set $S_{\cal D}$ and can decrypt ciphertexts with access policies satisfied by $S_{\cal D}$ . A policy-specific decryption blackbox is associated with an access policy $\mathbb {A}_{\cal D}$ and can decrypt ciphertexts with ${\mathbb {A}}_{\cal D}$ . Policy-specific decryption blackbox has weaker decryption capacity than key-like decryption blackbox, but tracing it is deemed to be more difficult. In the preliminary version (in CCS 2013) of this paper, we proposed a new CP-ABE scheme which is adaptively traceable against key-like decryption blackbox. The scheme has sublinear overhead, which is the most efficient one to date supporting fully collusion-resistant blackbox traceability. The scheme is fully secure in the standard model, and supports any monotonic access structures. In this paper, we further show that the scheme is also selectively traceable against policy-specific decryption blackbox. Furthermore, and more importantly, we prove a general statement that if a CP-ABE scheme is (selectively) traceable against policy-specific decryption blackbox, it is also (selectively) traceable against key-like decryption blackbox, which implies that we now only need to focus on building CP-ABE schemes which are traceable against policy-specific decryption blackbox.

Ciphertext-policy attribute-based encryption (CP-ABE) is a promising public key encryption primitive enabling fine-grained access control on shared data in public cloud. However, two quite challenging issues, the prevention of key escrow and key abuse, still exist in CP-ABE system. In this paper, we propose a multi-authority CP-ABE scheme without key escrow and key abuse. To prevent key escrow, multiple authorities are employed to perform the same procedure of key generation for an attribute. Thus, no individual authority or colluded authorities that manage no common attribute can decrypt any ciphertext, and it can also resist collusion attack from curious authority with the help of dishonest users. To prevent key abuse of dishonest users, user’s global identifier along with a signature is embedded into the secret key. Thus, any third party can learn the identity from a shared secret key and publicly verify its validity. An advantage of simultaneously preventing key escrow and key abuse is that the proposed scheme can achieve accountability, i.e. an auditor can publicly audit a user or authorities abuse the secret key. At last, the proposed scheme is fully secure in the random oracle model, and due to a key aggregate algorithm its efficiency is comparable to the decentralizing CP-ABE scheme [18] on which it is based.

Mobile social network (MSN), which is built upon popular smart phone devices and enables mobile users with similar interests to connect with one another, has received considerable attention in recent years. A common phenomenon that makes the MSN vivid today is mobile users often like to share attractive things to their friends in MSN. In this paper, based on this common phenomenon, we propose an efficient recommendation-based data dissemination (ReDD) protocol for MSN, which can efficiently disseminate high-quality messages in a privacy-preserving way. Specifically, in the proposed ReDD protocol, each mobile user, based on both his or her own view and his or her friends' recommendations, will form his or her personal estimation on the quality of a message. Only if the estimation of quality reaches a threshold, the message will be disseminated. In this way, high-quality messages can be widely spread in the network and occupy more network resources than low-quality ones. In order to check the validity of friends' recommendations, ReDD also employs an efficient anonymous authentication technique, which ensures that only the friends of a user can verify recommendations made by the user. Detailed security analysis demonstrates that ReDD can effectively resist various attacks launched by attackers and ensure identity privacy of nodes, confidentiality of shared keys and integrity of data packets. In addition, extensive simulations are also conducted to evaluate the performance of ReDD in terms of the number of active nodes and the average active time, and the simulation results show that high-quality messages can be disseminated widely and efficiently, while low-quality ones will be eliminated shortly to avoid occupying network resources. Copyright © 2014 John Wiley & Sons, Ltd.

Privacy-preserving metering aggregation is regarded as an important research topic in securing a smart grid. In this paper, we first identify and formalize a new attack, in which the attacker could exploit the information about the presence or absence of a specific person to infer his meter readings. This attack, coined as human-factor-aware differential aggregation (HDA) attack, cannot be addressed in existing privacy-preserving aggregation protocols proposed for smart grids. We give a formal definition on it and propose two novel protocols, including basic scheme and advanced scheme, to achieve privacy-preserving smart metering data aggregation and to resist the HDA attack. Our protocol ensures that smart meters periodically upload encrypted measurements to a (electricity) supplier/aggregator such that the aggregator is able to derive the aggregated statistics of all meter measurements but is unable to learn any information about the human activities. We present the formal security analysis for the proposed protocol to guarantee the strong privacy. Moreover, we evaluate the performance of our protocol in a Java-based implementation under different parameters. The performance and utility analysis shows that our protocol is simple, efficient, and practical.

Smart grid, as the next generation of power grid featured with efficient, reliable, and flexible characteristics, has received considerable attention in recent years. However, the full flourish of smart grid is still hindered by how to efficiently and effectively tackle with its security and privacy challenges. In this paper, we propose a privacy-preserving data aggregation scheme with fault tolerance, named PDAFT, for secure smart grid communications. Specifically, PDAFT uses the homomorphic Paillier Encryption technique to encrypt sensitive user data such that the control center can obtain the aggregated data without knowing individual ones, and a strong adversary who aims to threaten user privacy can learn nothing even though he has already compromised a few servers at the control center. In addition, PDAFT also supports the fault-tolerant feature, i.e., PDAFT can still work well even when some user failures and server malfunctions occur. Through extensive analysis, we demonstrate that PDAFT not only resists various security threats and preserves user privacy, but also has significantly less communication overhead compared with those previously reported competitive approaches.

Cloud computing emerges as a new computing paradigm that aims to provide reliable, customized and quality of service guaranteed computation environments for cloud users. Applications and databases are moved to the large centralized data centers, called cloud. Due to resource virtualization, global replication and migration, the physical absence of data and machine in the cloud, the stored data in the cloud and the computation results may not be well managed and fully trusted by the cloud users. Most of the previous work on the cloud security focuses on the storage security rather than taking the computation security into consideration together. In this paper, we propose a privacy cheating discouragement and secure computation auditing protocol, or SecCloud, which is a first protocol bridging secure storage and secure computation auditing in cloud and achieving privacy cheating discouragement by designated verifier signature, batch verification and probabilistic sampling techniques. The detailed analysis is given to obtain an optimal sampling size to minimize the cost. Another major contribution of this paper is that we build a practical secure-aware cloud computing experimental environment, or SecHDFS, as a test bed to implement SecCloud. Further experimental results have demonstrated the effectiveness and efficiency of the proposed SecCloud.

The articles in this special section focus on trust, network security, and privacy deployed in parallel and distributed systems.

With the increasing popularity of cloud computing, a huge amount of documents are stored on the cloud for reduced management cost and ease of access. Although data encryption offers help in some ways, it leaves other privacy concerns behind when users want to share documents with others. Otherwise, the users often share documents in the ABE settings in order to support broadcasting, error-tolerace, etc, however, the Attribute Authority will bear mounts of computations. In this paper, we combine the secure outsourced ABE systems with the keywords search while supporting multi-keyword search and search result ranking, which let the data owner securely uploads the data to a third organization and the data user can search over the ciphertext with multi-keywords and decrypt it without much computation with the help of a third server.

Ciphertext-policy attribute-based encryption is a promising mechanism with fine-grained access control for cloud storage system. However, there is a long-lasting problem of key abuse that a user may share its decryption key and a semi-honest authority may illegally issue decryption keys for unauthorized users for profits. To address this problem, we propose an accountable ciphertext-policy attribute-based encryption scheme. In our construction, there are two authorities to issue keys for users, but they cannot decrypt any ciphertexts without collusion. A shared key can be effectively traced, and if the traced identity claims that it is innocent, an auditor can publicly audit who will be responsible for the shared key. Compared with existing accountable ciphertext-policy attribute-based encryption schemes, the proposed scheme is more practical from the two aspects: (1) a user can normally request for a decryption key along with a short signature, and no additional interaction between users and authorities is needed; and (2) the complexity of tracing a masked secret key is reduced to | U | exponent computation, where | U | denotes the number of users in the system. At last, we give the security and experimental analysis.

Secure cloud storage, which is an emerging cloud service, is designed to protect the confidentiality of outsourced data but also to provide flexible data access for cloud users whose data is out of physical control. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is regarded as one of the most promising techniques that may be leveraged to secure the guarantee of the service. However, the use of CP-ABE may yield an inevitable security breach which is known as the misuse of access credential (i.e., decryption rights), due to the intrinsic “all-or-nothing” decryption feature of CP-ABE. In this paper, we investigate the two main cases of access credential misuse: one is on the semi-trusted authority side, and the other is on the side of cloud user. To mitigate the misuse, we propose the first accountable authority and revocable CP-ABE based cloud storage system with white-box traceability and auditing, referred to as CryptCloud $^+$ + . We also present the security analysis and further demonstrate the utility of our system via experiments.

In this work, we generalize the paradigm of the hash proof system HPS proposed by Cramer and Shoup EUROCRYPT 2002. In the center of our generalization, we lift a subset membership problem to a distribution-distinguishing problem. Our generalized HPS clarifies and encompasses all the known public-key encryption PKE schemes that essentially implement the idea of an HPS. Moreover, besides the existing smoothness property, we introduce an additional property named anonymity for HPS. As a natural application, we consider anonymity for PKE in the presence of key leakage and provide a generic construction of leakage-resilient anonymous PKE from an anonymous HPS. We then extend our generalization to the identity-based setting. Concretely, we generalize the paradigm of the identity-based HPS IB-HPS proposed by Bonehet al. FOCS 2007 and Alwenet al. EUROCRYPT 2010 and introduce anonymity for it. As an interesting application of the anonymous IB-HPS, we consider security for PKE with keyword search PEKS in the presence of token leakage and provide a generic construction of leakage-resilient secure PEKS from leakage-resilient anonymous identity-based encryption, which in turn is based on anonymous IB-HPS. Copyright © 2013 John Wiley & Sons, Ltd.

Very recently, Khan, Kim, and Alghathbar [6] proposed a dynamic ID-based remote user authentication scheme and claimed that their scheme can provide user anonymity. However, in this article, the authors demonstrate that either a malicious user or an adversary with a valid smart card can trace any user by eavesdropping on his normal authentication session over the public channel. Therefore, Khan et al.'s scheme fails to provide the privacy service as claimed. Hence, the authors present an improved scheme to overcome its flaw and examine the privacy of the improved scheme by using the smart card-based privacy model. In addition, the security and efficiency of the improved scheme are scrutinized. The conclusive result is that the design of the improved scheme is reasonable in not only both privacy and security aspects but also the performance aspect.