Accountable privacy preserving attribute based framework for authenticated encrypted access in clouds

In this paper, we propose an accountable privacy preserving attribute-based framework, called Ins-PAbAC, that combines attribute based encryption and attribute based signature techniques for securely sharing outsourced data contents via public cloud servers. The proposed framework presents several advantages. First, it provides an encrypted access control feature, enforced at the data owner’s side, while providing the desired expressiveness of access control policies. Second, Ins-PAbAC preserves users’ privacy, relying on an anonymous authentication mechanism, derived from a privacy preserving attribute based signature scheme that hides the users’ identifying information. Furthermore, our proposal introduces an accountable attribute based signature that enables an inspection authority to reveal the identity of the anonymously-authenticated user if needed. Third, Ins-PAbAC is provably secure, as it is resistant to both curious cloud providers and malicious users adversaries. Finally, experimental results, built upon OpenStack Swift testbed, point out the applicability of the proposed scheme in real world scenarios

A Review on Cloud Data Security Challenges and existing Countermeasures in Cloud Computing

Cloud computing (CC) is among the most rapidly evolving computer technologies. That is the required accessibility of network assets, mainly information storage with processing authority without the requirement for particular and direct user administration. CC is a collection of public and private data centers that provide a single platform for clients throughout the Internet. The growing volume of personal and sensitive information acquired through supervisory authorities demands the usage of the cloud not just for information storage and for data processing at cloud assets. Nevertheless, due to safety issues raised by recent data leaks, it is recommended that unprotected sensitive data not be sent to public clouds. This document provides a detailed appraisal of the research regarding data protection and privacy problems, data encrypting, and data obfuscation, including remedies for cloud data storage. The most up-to-date technologies and approaches for cloud data security are examined. This research also examines several current strategies for addressing cloud security concerns. The performance of each approach is then compared based on its characteristics, benefits, and shortcomings. Finally, go at a few active cloud storage data security study fields

An Application for Decentralized Access Control Mechanism on Cloud Data using Anonymous Authentication

In the last few years, Cloud computing has gained a lot of popularity and technology analysts believe it will be the future, but only if the security problems are solved from time-to-time. For those who are unfamiliar with cloud computing, it is a practice wherein users can access the data from the servers that are located in remote places. Users can do so through the Internet to manage, process and store the relevant data, instead of depending on the personal computer or a local server. Many firms and organizations are using cloud computing, which eventually is faster, cheaper and easy to maintain. Even the regular Internet users are also relying on cloud computing services to access their files whenever and wherever they wish. There are also numerous challenges associated with cloud computing like abuse of cloud services, data security and cyber-attacks. When clients outsource sensitive data through cloud servers, access control is one of the fundamental requirements among all security requirements which ensures that no unauthorized access to secured data will be avoided. Hence, cloud computing has to build a feature that provides privacy, access control challenges and security to the user data. A suitable and reliable encryption technique with enhanced key management should be developed and applied to the user data before loading into the cloud with the goal to achieve secured storage. It also has to support file access control and all other files related functions in a policy-based manner for any file stored in a cloud environment. This research paper proposes a decentralized access control mechanism for the data storage security in clouds which also provides anonymous authentication. This mechanism allows the decryption of the stored information only by the valid users, which is an additional feature of access control. Access control mechanism are decentralized which makes it robust when compared to centralized access control schemes meant for clouds

ENABLING ANONYMOUS ENDORSEMENT IN CLOUDS WITH DECENTRALIZED ACCESS CONTROL

A decentralized access control scheme for data storage in clouds that supports anonymous authentication authentication. In this scheme, the cloud checks the validity of the series without knowing the user's identity before storing data. It also has the added feature of access control in which only valid users are able to decrypt the stored information. This prevents replay attacks and supports conception, variation, and reading data stored in the cloud. It also supports user revocation . This is an important property because a user, revoked of its attributes, might no longer be able to write to the cloud. Moreover, our authentication and access control scheme is decentralized and robust, unlike other access control schemes designed for clouds which are centralized. The communication, computation, and storage overheads are comparable to centralized approaches

Prevention of Sensitive Information by Enhancing Cloud Access Control

the scheme prevents replay attacks and supports creation, modification, and reading data stored in the cloud. We also address user revocation. Moreover, our authentication, and storage overheads are comparable to centralized approaches. To better protect data security, this paper makes the first attempt to formally address and which are centralized. The communication, computation access control scheme is decentralized and robust; unlike other access control schemes designed for clouds the problem of authorized data. Different from traditional existing systems, the differential privileges of users are further considered in duplicate check besides the data itself by encrypting the file with differential privilege keys. Unauthorized users cannot decrypt the cipher text even collude with the S-CSP. Security analysis of the definitions specified in the demonstrates that our system is secure in terms proposed security model

ENABLING ANONYMOUS ENDORSEMENT IN CLOUDS WITH DECENTRALIZED ACCESS CONTROL

A decentralized access control scheme for data storage in clouds that supports anonymous authentication authentication. In this scheme, the cloud checks the validity of the series without knowing the user's identity before storing data. It also has the added feature of access control in which only valid users are able to decrypt the stored information. This prevents replay attacks and supports conception, variation, and reading data stored in the cloud. It also supports user revocation . This is an important property because a user, revoked of its attributes, might no longer be able to write to the cloud. Moreover, our authentication and access control scheme is decentralized and robust, unlike other access control schemes designed for clouds which are centralized. The communication, computation, and storage overheads are comparable to centralized approaches

Efficient data uncertainty management for health industrial internet of things using machine learning

[EN] In modern technologies, the industrial internet of things (IIoT) has gained rapid growth in the fields of medical, transportation, and engineering. It consists of a self-governing configuration and cooperated with sensors to collect, process, and analyze the processes of a real-time system. In the medical system, healthcare IIoT (HIIoT) provides analytics of a huge amount of data and offers low-cost storage systems with the collaboration of cloud systems for the monitoring of patient information. However, it faces certain connectivity, nodes failure, and rapid data delivery challenges in the development of e-health systems. Therefore, to address such concerns, this paper presents an efficient data uncertainty management model for HIIoT using machine learning (EDM-ML) with declining nodes prone and data irregularity. Its aim is to increase the efficacy for the collection and processing of real-time data along with smart functionality against anonymous nodes. It developed an algorithm for improving the health services against disruption of network status and overheads. Also, the multi-objective function decreases the uncertainty in the management of medical data. Furthermore, it expects the routing decisions using a machine learning-based algorithm and increases the uniformity in health operations by balancing the network resources and trust distribution. Finally, it deals with a security algorithm and established control methods to protect the distributed data in the exposed health industry. Extensive simulations are performed, and their results reveal the significant performance of the proposed model in the context of uncertainty and intelligence than benchmark algorithms.This research is supported by Artificial Intelligence & Data Analytics Lab (AIDA) CCIS Prince Sultan University, Riyadh Saudi Arabia. Authors are thankful for the support.Haseeb, K.; Saba, T.; Rehman, A.; Ahmed, I.; Lloret, J. (2021). Efficient data uncertainty management for health industrial internet of things using machine learning. International Journal of Communication Systems. 34(16):1-14. https://doi.org/10.1002/dac.4948114341

A survey on security issues and solutions at different layers of Cloud computing

Cloud computing offers scalable on-demand services to consumers with greater flexibility and lesser infrastructure investment. Since Cloud services are delivered using classical network protocols and formats over the Internet, implicit vulnerabilities existing in these protocols as well as threats introduced by newer architectures raise many security and privacy concerns. In this paper, we survey the factors affecting Cloud computing adoption, vulnerabilities and attacks, and identify relevant solution directives to strengthen security and privacy in the Cloud environment