An efficient PHR service system supporting fuzzy keyword search and fine-grained access control

Outsourcing of personal health record (PHR) has attracted considerable interest recently. It can not only bring much convenience to patients, it also allows efficient sharing of medical information among researchers. As the medical data in PHR is sensitive, it has to be encrypted before outsourcing. To achieve fine-grained access control over the encrypted PHR data becomes a challenging problem. In this paper, we provide an affirmative solution to this problem. We propose a novel PHR service system which supports efficient searching and fine-grained access control for PHR data in a hybrid cloud environment, where a private cloud is used to assist the user to interact with the public cloud for processing PHR data. In our proposed solution, we make use of attribute-based encryption (ABE) technique to obtain fine-grained access control for PHR data. In order to protect the privacy of PHR owners, our ABE is anonymous. That is, it can hide the access policy information in ciphertexts. Meanwhile, our solution can also allow efficient fuzzy search over PHR data, which can greatly improve the system usability. We also provide security analysis to show that the proposed solution is secure and privacy-preserving. The experimental results demonstrate the efficiency of the proposed scheme.Peer ReviewedPostprint (author's final draft

BMSQABSE: Design of a Bioinspired Model to Improve Security & QoS Performance for Blockchain-Powered Attribute-based Searchable Encryption Applications

Attribute-based searchable encryption (ABSE) is a sub-field of security models that allow intensive searching capabilities for cloud-based shared storage applications. ABSE Models require higher computational power, which limits their application to high-performance computing devices. Moreover, ABSE uses linear secret sharing scheme (LSSS), which requires larger storage when compared with traditional encryption models. To reduce computational complexity, and optimize storage cost, various researchers have proposed use of Machine Learning Models (MLMs), that assist in identification & removal of storage & computational redundancies. But most of these models use static reconfiguration, thus cannot be applied to large-scale deployments. To overcome this limitation, a novel combination of Grey Wolf Optimization (GWO) with Particle Swarm Optimization (PSO) model to improve Security & QoS performance for Blockchain-powered Attribute-based Searchable Encryption deployments is proposed in this text. The proposed model augments ABSE parameters to reduce its complexity and improve QoS performance under different real-time user request scenarios. It intelligently selects cyclic source groups with prime order & generator values to create bilinear maps that are used for ABSE operations. The PSO Model assists in generation of initial cyclic population, and verifies its security levels, QoS levels, and deployment costs under multiple real-time cloud scenarios. Based on this initial analysis, the GWO Model continuously tunes ABSE parameters in order to achieve better QoS & security performance levels via stochastic operations. The proposed BMSQABSE model was tested under different cloud configurations, and its performance was evaluated for healthcare deployments. Based on this evaluation, it was observed that the proposed model achieved 8.3% lower delay, with 4.9% lower energy consumption, 14.5% lower storage requirements when compared with standard ABSE models. It was able to mitigate Distributed Denial of Service (DDoS), Masquerading, Finney, and Sybil attacks, which assists in deploying the proposed model for QoS-aware highly secure deployments

Longitude : a privacy-preserving location sharing protocol for mobile applications

Location sharing services are becoming increasingly popular. Although many location sharing services allow users to set up privacy policies to control who can access their location, the use made by service providers remains a source of concern. Ideally, location sharing providers and middleware should not be able to access users’ location data without their consent. In this paper, we propose a new location sharing protocol called Longitude that eases privacy concerns by making it possible to share a user’s location data blindly and allowing the user to control who can access her location, when and to what degree of precision. The underlying cryptographic algorithms are designed for GPS-enabled mobile phones. We describe and evaluate our implementation for the Nexus One Android mobile phone

Privacy-preserving data search with fine-grained dynamic search right management in fog-assisted Internet of Things

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Fog computing, as an assisted method for cloud computing, collects Internet of Things (IoT) data to multiple fog nodes on the edge of IoT and outsources them to the cloud for data search, and it reduces the computation cost on IoT nodes and provides fine-grained search right management. However, to provide privacy-preserving IoT data search, the existing searchable encryptions are very inefficient as the computation cost is too high for the resource-constrained IoT ends. Moreover, to provide dynamic search right management, the users need to be online all the time in the existing schemes, which is impractical. In this paper, we first present a new fog-assisted privacy-preserving IoT data search framework, where the data from each IoT device is collected by a fog node, stored in a determined document and outsourced to the cloud, the users search the data through the fog nodes, and the fine-grained search right management is maintained at document level. Under this framework, two searchable encryption schemes are proposed, i.e., Credible Fog Nodes assisted Searchable Encryption (CFN-SE) and Semi-trusted Fog Nodes assisted Searchable Encryption (STFN-SE). In CFN-SE scheme, the indexes and trapdoors are generated by the fog nodes, which greatly reduce the computation costs at the IoT devices and user ends, and fog nodes are used to support offline users’ key update. In STFN-SE scheme, the semi-trusted fog nodes are used to provide storage of encrypted key update information to assist offline users’ search right update. In both schemes, no re-encryption of the keywords is needed in search right updates. The performance evaluations of our schemes demonstrate the feasibility and high efficiency of our system.National Key Research and Development ProgramNational Natural Science Foundation of ChinaSichuan Provincial Major Frontier IssuesState Key Laboratory of Integrated Services Networks, Xidian Universit

Privacy Enhanced Access Control by Means of Policy Blinding

Traditional techniques of enforcing an access control policy\ud rely on an honest reference monitor to enforce the policy. However, for\ud applications where the resources are sensitive, the access control policy\ud might also be sensitive. As a result, an honest-but-curious reference monitor would glean some interesting information from the requests that it\ud processes. For example if a requestor in a role psychiatrist is granted access to a document, the patient associated with that document probably\ud has a psychiatric problem. The patient would consider this sensitive in-\ud formation, and she might prefer the honest-but-curious reference monitor\ud to remain oblivious of her mental problem.\ud We present a high level framework for querying and enforcing a role\ud based access control policy that identifies where sensitive information\ud might be disclosed. We then propose a construction which enforces a\ud role based access control policy cryptographically, in such a way that the\ud reference monitor learns as little as possible about the policy. (The reference monitor only learns something from repeated queries). We prove\ud the security of our scheme showing that it works in theory, but that it\ud has a practical drawback. However, the practical drawback is common\ud to all cryptographically enforced access policy schemes. We identify several approaches to mitigate the drawback and conclude by arguing that\ud there is an underlying fundamental problem that cannot be solved. We\ud also show why attribute based encryption techniques do not not solve the\ud problem of enforcing policy by an honest but curious reference monitor

A Comprehensive Study on Crypto-Algorithms

In the field of computer network and security, cryptography plays a vital role for secure data transmission as it follows the principle of data confidentiality, integrity, non-repudiation, authentication. By using several cryptographic algorithms, a user can deliver and receive the message in more convenient way. In this paper, we have collaborated on various cryptographic algorithms, several types of cryptographic techniques along with different types of security attacks prevailing in case of cryptography. During the exchanging of any sort of information, the key generation, encryption and decryption processes are examined in more details in the current paper. We have discussed regarding RSA (Ron Rives, Adi Shamir and Len Adelman), which is one of the most secure algorithm in the context of data and information sharing, that has been analysed clearly in our work along with the basic concepts of DES(Data Encryption Standard) , conventional encryption model, ECC(Elliptic curve cryptography), Digital signature, ABE(Attribute based Encryption), KP-ABE(Key policy Attribute based encryption), CP-ABE(Ciphertext policy attribute based encryption), IBE(Identity based Encryption). We have elaborated various cryptograhic concepts for keeping the message confidential and secure while considering secured data communication in case of networks