Efficient Compressed Ciphertext Length Scheme Using Multi-Authority CP-ABE for Hierarchical Attributes

Zhang, Zhiyong; Li, Cheng; Gupta, Brij B.; Niu, Danmei

doi:10.1109/access.2018.2854600

Cited by 26 publications

(7 citation statements)

References 23 publications

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“…Our suggested structure does not include any background knowledge or preparation data and will define core concepts (or topics) depending on the nature of the conversation with the aid of the WorldNet vocabulary database [8]. In comparison, the term extraction method depends on the conceptual similarity of terms rather than on the frequency of terms [9]. Our technology is also in a role to determine the most important terms that can best reflect and interpret the knowledge in the chat session.…”

Section: Existing Methodologiesmentioning

confidence: 99%

Detecting and Analyzing the Malicious Social Bots by using Data Mining and Naïve Bayesian Classifier

M¹

2020

IJETER

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With the huge increase in the number, speed, and variety of customer information (such as customer-generated information) in online interpersonal organizations, people have worked hard to construct better methods to collect and inspect such large information. For example, social robots have been used to perform scientific management of robots and provide customers with improved management attributes. Even so, harmful social robots are used to spread false data (for example, false news), which may bring real results. Therefore, identifying and evacuating harmful social robots in online informal communities is crucial. The latest discovery technology of resentful social robots undermines the quantitative focus of its behavior. These highlights are easily imitated by social robots. This leads to a reduction in the accuracy of the investigation. This article describes an epic strategy for identifying malicious social robots, which includes two key options, depending on the possibility of snapshot stream grouping and semi-hosted binding changes. The technology not only investigates the possibility of changes in the click stream of customer behavior, but also takes into account the temporal highlights of the behavior.

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Section: Existing Methodologiesmentioning

confidence: 99%

Detecting and Analyzing the Malicious Social Bots by using Data Mining and Naïve Bayesian Classifier

M¹

2020

IJETER

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“…Numerous works of research such as revocable CP-ABE [25], lightweight CP-ABE [26], multi-authority CP-ABE [4,27], and large universe CP-ABE [28] have been developed in response to upgrading the competency of the Ciphertext Policy Attribute-based Encryption (CP-ABE) scheme. However, most of the schemes exposed the access policy in plaintext, which incurred privacy leakage.…”

Section: Related Workmentioning

confidence: 99%

Towards Virtuous Cloud Data Storage Using Access Policy Hiding in Ciphertext Policy Attribute-Based Encryption

et al. 2021

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Managing and controlling access to the tremendous data in Cloud storage is very challenging. Due to various entities engaged in the Cloud environment, there is a high possibility of data tampering. Cloud encryption is being employed to control data access while securing Cloud data. The encrypted data are sent to Cloud storage with an access policy defined by the data owner. Only authorized users can decrypt the encrypted data. However, the access policy of the encrypted data is in readable form, which results in privacy leakage. To address this issue, we proposed a reinforcement hiding in access policy over Cloud storage by enhancing the Ciphertext Policy Attribute-based Encryption (CP-ABE) algorithm. Besides the encryption process, the reinforced CP-ABE used logical connective operations to hide the attribute value of data in the access policy. These attributes were converted into scrambled data along with a ciphertext form that provides a better unreadability feature. It means that a two-level concealed tactic is employed to secure data from any unauthorized access during a data transaction. Experimental results revealed that our reinforced CP-ABE had a low computational overhead and consumed low storage costs. Furthermore, a case study on security analysis shows that our approach is secure against a passive attack such as traffic analysis.

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“…Furthermore, an intelligent wearable vital sensor engine supported by an abstract framework was developed. Due to high sensitivity of these data being exchanged by means of communication systems, data protection and security perspectives [4][5][6] have climbed the priority list for smart health mechanisms emphasizing on the importance of data being transferred securely and quickly.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Data Privacy and Anonymization Algorithms for Smart Health Applications

Fakeeroodeen

Beeharry

2021

SN COMPUT. SCI.

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In line with the concept of Smart cities and Smart World, there have been bewildering developments in the field of Internet of Things (IoT) and Big Data Analytics where one most noteworthy territory is that of Smart Health. Private Health data are required to be transmitted over wireless communication systems where the main problem arising is that of data security and privacy. Various algorithms have been implemented to achieve data privacy. In this work, k-anonymity, differential privacy, k-map,-diversity and a hybrid of the three algorithms combined with ℓ-diversity have been analyzed using algorithms running on a raspberry pi (edge) for a breast cancer dataset. The results demonstrated a difference in using stand-alone algorithms in terms of output anonymized dataset, execution time, information loss, risk analysis, and statistical analysis. If solely based on its execution time, the hybrids took less than 20 s in comparison to the stand-alone taking nearly 90 s, leading to conclusion that hybrid algorithms are much more suitable in terms of efficiency. Having the option to share anonymized information quicker will reduce financial and admin costs indicating that hybrids should be the main focus even if all algorithms fulfilled their objective of achieving data privacy.

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Efficient Compressed Ciphertext Length Scheme Using Multi-Authority CP-ABE for Hierarchical Attributes

Cited by 26 publications

References 23 publications

Detecting and Analyzing the Malicious Social Bots by using Data Mining and Naïve Bayesian Classifier

Detecting and Analyzing the Malicious Social Bots by using Data Mining and Naïve Bayesian Classifier

Towards Virtuous Cloud Data Storage Using Access Policy Hiding in Ciphertext Policy Attribute-Based Encryption

Hybrid Data Privacy and Anonymization Algorithms for Smart Health Applications

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