Optimal and Efficient Searchable Encryption with Single Trapdoor for Multi-Owner Data Sharing in Federated Cloud Computing

Cloud computing, an Internet based computing model, has changed the way of data owners store and manage data. In such environment, data sharing is very important with more efficient data access control. Issuing an aggregate key to users on data enables and authorizes them to search for data of select encrypted files using trapdoor or encrypted keyword. The existing schemes defined for this purpose do have certain limitations. For instance, Cui et al. scheme is elegant but lacks in flexibility in access control in presence of multiple data owners sharing data to users. Its single trapdoor approach needs transformation into individual trapdoors to access data of specific data owner. Moreover, the existing schemes including that of Cui et al. does not support federated cloud.  In this paper we proposed an efficient key aggregate searchable encryption scheme which enables multiple featuressuch as support for truly single aggregate key to access data of many data owners, federated cloud support,query privacy, controlled search process and security against cross-pairing attack. It has algorithms for setup, keygen, encrypt, extract, aggregate, trapdoor, test and federator. In multi-user setting it is designed to serve data owners and users with secure data sharing through key aggregate searchable encryption The proposed scheme supports federated cloud. Experimental results revealed that the proposed scheme is provably secure withrelatively less computational overhead and time complexity when compared with the state of the art

Survey on securing data storage in the cloud

Cloud Computing has become a well-known primitive nowadays; many researchers and companies are embracing this fascinating technology with feverish haste. In the meantime, security and privacy challenges are brought forward while the number of cloud storage user increases expeditiously. In this work, we conduct an in-depth survey on recent research activities of cloud storage security in association with cloud computing. After an overview of the cloud storage system and its security problem, we focus on the key security requirement triad, i.e., data integrity, data confidentiality, and availability. For each of the three security objectives, we discuss the new unique challenges faced by the cloud storage services, summarize key issues discussed in the current literature, examine, and compare the existing and emerging approaches proposed to meet those new challenges, and point out possible extensions and futuristic research opportunities. The goal of our paper is to provide a state-of-the-art knowledge to new researchers who would like to join this exciting new field

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

Novel Proposed Work for Empirical Word Searching in Cloud Environment

People's lives have become much more convenient as a result of the development of cloud storage. The third-party server has received a lot of data from many people and businesses for storage. Therefore, it is necessary to ensure that the user's data is protected from prying eyes. In the cloud environment, searchable encryption technology is used to protect user information when retrieving data. The versatility of the scheme is, however, constrained by the fact that the majority of them only offer single-keyword searches and do not permit file changes.A novel empirical multi-keyword search in the cloud environment technique is offered as a solution to these issues. Additionally, it prevents the involvement of a third party in the transaction between data holder and user and guarantees integrity. Our system achieves authenticity at the data storage stage by numbering the files, verifying that the user receives a complete ciphertext. Our technique outperforms previous analogous schemes in terms of security and performance and is resistant to inside keyword guessing attacks.The server cannot detect if the same set of keywords is being looked for by several queries because our system generates randomized search queries. Both the number of keywords in a search query and the number of keywords in an encrypted document can be hidden. Our searchable encryption method is effective and protected from the adaptive chosen keywords threat at the same time

AAQ-PEKS: An Attribute-based Anti-Quantum Public-Key Encryption Scheme with Keyword Search for E-healthcare Scenarios

Electronic Medical Records (EMRs) have been utilized in plentiful medical institutions due to their superior convenience and low storage overhead. Nevertheless, it is difficult for medical departments with disparate management regulations to share EMRs through secure communication channels since sensitive EMRs are prone to be tampered with. Therefore, the EMRs should be encrypted before being outsourced to the network servers. Public key Encryption with Keyword Search (PEKS) has the ability for doctors to search encrypted EMRs, but traditional PEKS algorithms are susceptible to quantum computing attacks and without considering access control. To address the aforementioned issues, we proposed AAQ-PEKS scheme, named an attribute-based anti-quantum public-key encryption scheme with keyword search. Initially, based on the LWE hardness, we first introduce the attribute-based PEKS that can resist quantum attacks in E-health scenarios. Secondly, we combine Attribute-Based Encryption (ABE) into AAQ-PEKS to realize access control for sensitive EMRs. Thirdly, the computational security analysis illustrates that our scheme achieves correctness, Indistinguishability against Chosen Plaintext Attack (IND-CPA) and Indistinguishability against Chosen Keyword Attack (IND-CKA). Lastly, comprehensive performance evaluation in practice elaborates that our AAQ-PEKS is more efficient compared with other existing top-tier schemes. To conclude, our scheme has the characteristics of resisting quantum attacks and fine-grained access control for E-health scenarios

Efficient Public Key Searchable Encryption Schemes from Standard Hard Lattice Problems for Cloud Computing

Cloud storage and computing offers significant convenience and management efficiency in the information era. Privacy protection is a major challenge in cloud computing. Public key encryption with keyword search (PEKS) is an ingenious tool for ensuring privacy and functionality in certain scenario, such as ensuring privacy for data retrieval appearing in the cloud computing. Despite many attentions received, PEKS schemes still face several challenges in practical applications, such as low computational efficiency, high end-to-end delay, vulnerability to inside keyword guessing attacks(IKGA) and key management defects in the multi-user environment. In this work, we introduce three Ring-LWE/ISIS based PEKS schemes: (1) Our basic PEKS scheme achieves high level security in the standard model. (2) Our PAEKS scheme utilizes the sender\u27s private key to generate an authentication when encrypting, which can resist IKGA. (3) Our IB-PAEKS scheme not only can resist IKGA, but also significantly reduces the complexity of key management in practical applications. Experimental results indicate that the first scheme provides lower end-to-end delay and higher computational efficiency compared to similar ones, and that our last two schemes can provide more secure properties with little additional overhead

A Practical Framework for Storing and Searching Encrypted Data on Cloud Storage

Security has become a significant concern with the increased popularity of cloud storage services. It comes with the vulnerability of being accessed by third parties. Security is one of the major hurdles in the cloud server for the user when the user data that reside in local storage is outsourced to the cloud. It has given rise to security concerns involved in data confidentiality even after the deletion of data from cloud storage. Though, it raises a serious problem when the encrypted data needs to be shared with more people than the data owner initially designated. However, searching on encrypted data is a fundamental issue in cloud storage. The method of searching over encrypted data represents a significant challenge in the cloud. Searchable encryption allows a cloud server to conduct a search over encrypted data on behalf of the data users without learning the underlying plaintexts. While many academic SE schemes show provable security, they usually expose some query information, making them less practical, weak in usability, and challenging to deploy. Also, sharing encrypted data with other authorized users must provide each document's secret key. However, this way has many limitations due to the difficulty of key management and distribution. We have designed the system using the existing cryptographic approaches, ensuring the search on encrypted data over the cloud. The primary focus of our proposed model is to ensure user privacy and security through a less computationally intensive, user-friendly system with a trusted third party entity. To demonstrate our proposed model, we have implemented a web application called CryptoSearch as an overlay system on top of a well-known cloud storage domain. It exhibits secure search on encrypted data with no compromise to the user-friendliness and the scheme's functional performance in real-world applications.Comment: 146 Pages, Master's Thesis, 6 Chapters, 96 Figures, 11 Table

Lattice-Based Public Key Searchable Encryption from Experimental Perspectives

Public key Encryption with Keyword Search (PEKS) aims in mitigating the impacts of data privacy versus utilization dilemma by allowing {\em any user in the system} to send encrypted files to the server to be searched by a receiver. The receiver can retrieve the encrypted files containing specific keywords by providing the corresponding trapdoors of these keywords to the server. Despite their merits, the existing PEKS schemes introduce a high end-to-end delay that may hinder their adoption in practice. Moreover, they do not scale well for large security parameters and provide no post-quantum security promises. In this paper, we propose two novel lattice-based PEKS schemes that offer a high computational efficiency along with better security assurances than that of the existing alternatives. Specifically, our NTRU-PEKS scheme achieves 18 times lower end-to-end delay than the most efficient pairing-based alternatives. Our LWE-PEKS offers provable security in the standard model with a reduction to the worst-case lattice problems. We fully implemented our NTRU-PEKS scheme and benchmarked its performance as deployed on Amazon Web Services cloud infrastructures

Privacy-preserving ciphertext-policy attribute-based search over encrypted data in cloud storage

This thesis presents Privacy-Preserving Ciphertext-Policy Attribute-Based Searchable encryption schemes to achieve data privacy, keyword searchability, and fine-grained access control. The works related to this thesis address the issues with the existing related schemes like Data Authentication, Inefficient encryption and decryption, Inefficient traceability and revocation, Key-escrow problems, Prone to quantum attacks, and Lack of semantic search. The performance of all the proposed schemes was evaluated on a local machine.Resumen de la tesis presentada para acceder al título de Ph.D. in Computer Science de la National Institute of Technology-Warangal, Telangana, India.Facultad de Informátic