Co-Check: Collaborative Outsourced Data Auditing in Multicloud Environment

With the increasing demand for ubiquitous connectivity, wireless technology has significantly improved our daily lives. Meanwhile, together with cloud-computing technology (e.g., cloud storage services and big data processing), new wireless networking technology becomes the foundation infrastructure of emerging communication networks. Particularly, cloud storage has been widely used in services, such as data outsourcing and resource sharing, among the heterogeneous wireless environments because of its convenience, low cost, and flexibility. However, users/clients lose the physical control of their data after outsourcing. Consequently, ensuring the integrity of the outsourced data becomes an important security requirement of cloud storage applications. In this paper, we present Co-Check, a collaborative multicloud data integrity audition scheme, which is based on BLS (Boneh-Lynn-Shacham) signature and homomorphic tags. According to the proposed scheme, clients can audit their outsourced data in a one-round challenge-response interaction with low performance overhead. Our scheme also supports dynamic data maintenance. The theoretical analysis and experiment results illustrate that our scheme is provably secure and efficient

ACTIVE-HASH-TABLE BASED PUBLIC AUDITING FOR SECURE CLOUD STORAGE

Public auditing scheme for secure cloud storage based on dynamic hash table, which is a new two-dimensional data structure located at a third-party auditor (TPA) to record the data property information for dynamic auditing. Differing form the existing works, the proposed scheme migrates the authorized information from the cloud services provider to the TPA and thereby significantly reduces the computational cost and communication overhead. Our scheme can also achieve higher updating efficiency than the state of the art schemes. In addition, we extend our scheme to support privacy preservation by combining the homomorphic authenticator based on the public key with the random masking generated by the TPA and achieve batch auditing by employing the aggregate BLS signature technique. We formally prove the security of the proposed scheme and evaluate the auditing performance by detailed experiments and comparisons with the existing ones. The results demonstrate that the proposed scheme can effectively achieve secure auditing for cloud storage and outperform the previous schemes’ in computation complexity, storage costs, and communication overhead

A Hybrid Multi-user Cloud Access Control based Block Chain Framework for Privacy Preserving Distributed Databases

Most of the traditional medical applications are insecure and difficult to compute the data integrity with variable hash size. Traditional medical data security systems are insecure and it depend on static parameters for data security. Also, distributed based cloud storage systems are independent of integrity computational and data security due to unstructured data and computational memory. As the size of the data and its dimensions are increasing in the public and private cloud servers, it is difficult to provide the machine learning based privacy preserving in cloud computing environment. Block-chain technology plays a vital role for large cloud databases. Most of the conventional block-chain frameworks are based on the existing integrity and confidentiality models. Also, these models are based on the data size and file format. In this model, a novel integrity verification and encryption framework is designed and implemented in cloud environment.  In order to overcome these problems in the cloud computing environment, a hybrid integrity and security-based block-chain framework is designed and implemented on the large distributed databases. In this framework,a novel decision tree classifier is used along with non-linear mathematical hash algorithm and advanced attribute-based encryption models are used to improve the privacy of multiple users on the large cloud datasets. Experimental results proved that the proposed advanced privacy preserving based block-chain technology has better efficiency than the traditional block-chain based privacy preserving systems on large distributed databases

Attribute Based Encryption for Secure Data Access in Cloud

Cloud computing is a progressive computing worldview, which empowers adaptable, on-request, and ease use of Information Technology assets. However, the information transmitted to some cloud servers, and various protection concerns are arising out of it. Different plans given the property-based encryption have been proposed to secure the Cloud Storage. In any case, most work spotlights on the information substance security and the get to control, while less consideration towards the benefit control and the character protection. In this paper, a semi-anonymous benefit control conspires AnonyControl to address the information protection, as well as the client character security in existing access control plans. AnonyControl decentralizes the central authority to restrain the character spillage and accordingly accomplishes semi-anonymity. Furthermore, it likewise sums up the document get to control to the benefit control, by which advantages of all operations on the cloud information managed in a fine-grained way. Along these lines, display the AnonyControl-F, which ultimately keeps the character spillage and accomplish the full secrecy. Our security assessment demonstrates that both AnonyControl and AnonyControl-F are secure under the decisional bilinear Diffie-Hellman presumption, and our execution assessment shows the attainability of our plans. Index Terms: Anonymity, multi-authority, attribute-based encryption

On the continuous processing of health data in edge-fog-cloud computing by using micro/nanoservice composition

The edge, the fog, the cloud, and even the end-user's devices play a key role in the management of the health sensitive content/data lifecycle. However, the creation and management of solutions including multiple applications executed by multiple users in multiple environments (edge, the fog, and the cloud) to process multiple health repositories that, at the same time, fulfilling non-functional requirements (NFRs) represents a complex challenge for health care organizations. This paper presents the design, development, and implementation of an architectural model to create, on-demand, edge-fog-cloud processing structures to continuously handle big health data and, at the same time, to execute services for fulfilling NFRs. In this model, constructive and modular $blocks$ , implemented as microservices and nanoservices, are recursively interconnected to create edge-fog-cloud processing structures as ¿This work was supported in part by the Council for Science and Technology of Mexico (CONACYT) through the Basic Scientific Research under Grant 2016-01-285276, and in part by the Project CABAHLA-CM: Convergencia Big data-Hpc: de los sensores a las Aplicaciones from Madrid Regional Government under Grant S2018/TCS-4423