B. Murugeshwari^1,*, S. Rajalakshmi¹, K. Sudharson²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2293-2307, 2023, DOI:10.32604/csse.2023.029074

Abstract Imagine numerous clients, each with personal data; individual inputs are severely corrupt, and a server only concerns the collective, statistically essential facets of this data. In several data mining methods, privacy has become highly critical. As a result, various privacy-preserving data analysis technologies have emerged. Hence, we use the randomization process to reconstruct composite data attributes accurately. Also, we use privacy measures to estimate how much deception is required to guarantee privacy. There are several viable privacy protections; however, determining which one is the best is still a work in progress. This paper discusses the difficulty of measuring privacy while… More >

S. Stewart Kirubakaran^1,*, V. P. Arunachalam¹, S. Karthik¹, S. Kannan²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 1881-1895, 2023, DOI:10.32604/csse.2023.026690

Abstract In the present scenario of rapid growth in cloud computing models, several companies and users started to share their data on cloud servers. However, when the model is not completely trusted, the data owners face several security-related problems, such as user privacy breaches, data disclosure, data corruption, and so on, during the process of data outsourcing. For addressing and handling the security-related issues on Cloud, several models were proposed. With that concern, this paper develops a Privacy-Preserved Data Security Approach (PP-DSA) to provide the data security and data integrity for the outsourcing data in Cloud Environment. Privacy preservation is ensured… More >

Hong Lei^1,2,3, Jun Li^1,*, Suozai Li⁴, Ming Huang⁴, Jieren Cheng⁵, Yirui Bai¹, Xinman Luo¹, Chao Liu⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5687-5702, 2022, DOI:10.32604/cmc.2022.030995

Abstract The past decade has seen the rapid development of data in many areas. Data has enormous commercial potential as a new strategic resource that may efficiently boost technical growth and service innovation. However, individuals are becoming increasingly concerned about data misuse and leaks. To address these issues, in this paper, we propose TrustControl, a trusted data usage control system to control, process, and protect data usage without revealing privacy. A trusted execution environment (TEE) is exploited to process confidential user data. First of all, we design a secure and reliable remote attestation mechanism for ARM TrustZone, which can verify the… More >

K. Pradeep Mohan Kumar¹, Jenifer Mahilraj², D. Swathi³, R. Rajavarman⁴, Subhi R. M. Zeebaree⁵, Rizgar R. Zebari⁶, Zryan Najat Rashid⁷, Ahmed Alkhayyat^8,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5299-5314, 2022, DOI:10.32604/cmc.2022.030825

Abstract Recently, smart cities have emerged as an effective approach to deliver high-quality services to the people through adaptive optimization of the available resources. Despite the advantages of smart cities, security remains a huge challenge to be overcome. Simultaneously, Intrusion Detection System (IDS) is the most proficient tool to accomplish security in this scenario. Besides, blockchain exhibits significance in promoting smart city designing, due to its effective characteristics like immutability, transparency, and decentralization. In order to address the security problems in smart cities, the current study designs a Privacy Preserving Secure Framework using Blockchain with Optimal Deep Learning (PPSF-BODL) model. The… More >

Neetika Bhandari^1,*, Payal Pahwa²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2043-2055, 2023, DOI:10.32604/iasc.2023.028368

Abstract Data is humongous today because of the extensive use of World Wide Web, Social Media and Intelligent Systems. This data can be very important and useful if it is harnessed carefully and correctly. Useful information can be extracted from this massive data using the Data Mining process. The information extracted can be used to make vital decisions in various industries. Clustering is a very popular Data Mining method which divides the data points into different groups such that all similar data points form a part of the same group. Clustering methods are of various types. Many parameters and indexes exist… More >

K. Saranya^*, K. Premalatha

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2029-2042, 2023, DOI:10.32604/iasc.2023.027949

Abstract Medical data mining has become an essential task in healthcare sector to secure the personal and medical data of patients using privacy policy. In this background, several authentication and accessibility issues emerge with an intention to protect the sensitive details of the patients over getting published in open domain. To solve this problem, Multi Attribute Case based Privacy Preservation (MACPP) technique is proposed in this study to enhance the security of privacy-preserving data. Private information can be any attribute information which is categorized as sensitive logs in a patient’s records. The semantic relation between transactional patient records and access rights… More >

Vivekraj Mannayee^1,*, Thirumalai Ramanathan²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1545-1563, 2023, DOI:10.32604/iasc.2023.027675

Abstract Blockchain has recently sparked interest in both the technological and business firms. The Internet of Things's (IoT) core principle emerged due to the connectivity of several new technologies, including wireless technology, the Internet, embedded automation systems, and micro-electromechanical devices. Manufacturing environments and operations have been successfully converted by implementing recent advanced technology like Cloud Computing (CC), Cyber-Physical System (CSP), Information and Communication Technologies (ICT) and Enterprise Model, and other technological innovations into the fourth industrial revolution referred to as Industry 4.0. Data management is defined as the process of accumulation in order to make better business decisions, and process, secure… More >

Kaifeng Zhang¹, Zhao Qiu^1,*, Gengquan Xie¹, Jiale Lin¹, Tingting Zhang¹, Yingsheng Lian¹, Tao Chen¹, Yunlong He², Yu Yang²

Journal of Cyber Security, Vol.4, No.2, pp. 95-107, 2022, DOI:10.32604/jcs.2022.029451

Abstract Due to its unique security, blockchain technology is widely used in the financial field. Under the background of the rapid development of information technology and the rapid improvement of medical level, it is also a general trend to integrate blockchain technology into the medical field. According to the characteristics of blockchain and the research contents of many scholars on the application of blockchain in the medical field, this paper analyzes and summarizes the problems existing in the current development of blockchain, puts forward corresponding solutions, and looks forward to the further application of blockchain technology in the medical field. More >

Maryam Abdulaziz Saad Bubukayr^1,*, Mounir Frikha²

Journal of Cyber Security, Vol.4, No.2, pp. 79-94, 2022, DOI:10.32604/jcs.2022.029020

Abstract Personal data are strongly linked to web browsing history. By visiting a certain website, a user can share her favorite items, location, employment status, financial information, preferences, gender, medical status, news, etc. Therefore, web tracking is considered as one of the most significant internet privacy threats that can have a serious impact on end-users. Usually, it is used by most websites to track visitors through the internet in order to enhance their services and improve search customization. Moreover, selling users’ data to the advertising companies without their permission. Although there are more research efforts focused on third-party tracking to protect… More >

B. Murugeshwari^1,*, D. Selvaraj², K. Sudharson³, S. Radhika⁴

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 839-851, 2023, DOI:10.32604/iasc.2023.028548

Abstract Protecting the privacy of data in the multi-cloud is a crucial task. Data mining is a technique that protects the privacy of individual data while mining those data. The most significant task entails obtaining data from numerous remote databases. Mining algorithms can obtain sensitive information once the data is in the data warehouse. Many traditional algorithms/techniques promise to provide safe data transfer, storing, and retrieving over the cloud platform. These strategies are primarily concerned with protecting the privacy of user data. This study aims to present data mining with privacy protection (DMPP) using precise elliptic curve cryptography (PECC), which builds… More >