Walid El-Shafai^1,2, Hayam A. Abd El-Hameed³, Noha A. El-Hag⁴, Ashraf A. M. Khalaf³, Naglaa F. Soliman⁵, Hussah Nasser AlEisa^6,*, Fathi E. Abd El-Samie¹

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 719-732, 2023, DOI:10.32604/iasc.2023.031079

Abstract Nowadays, the security of images or information is very important. This paper introduces a proposed hybrid watermarking and encryption technique for increasing medical image security. First, the secret medical image is encrypted using Advanced Encryption Standard (AES) algorithm. Then, the secret report of the patient is embedded into the encrypted secret medical image with the Least Significant Bit (LSB) watermarking algorithm. After that, the encrypted secret medical image with the secret report is concealed in a cover medical image, using Kekre’s Median Codebook Generation (KMCG) algorithm. Afterwards, the stego-image obtained is split into 16 parts. Finally, it is sent to… More >

Mohammed BinJubier¹, Mohd Arfian Ismail¹, Abdulghani Ali Ahmed^2,*, Ali Safaa Sadiq³

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3665-3686, 2022, DOI:10.32604/cmc.2022.024663

Abstract Publishing big data and making it accessible to researchers is important for knowledge building as it helps in applying highly efficient methods to plan, conduct, and assess scientific research. However, publishing and processing big data poses a privacy concern related to protecting individuals’ sensitive information while maintaining the usability of the published data. Several anonymization methods, such as slicing and merging, have been designed as solutions to the privacy concerns for publishing big data. However, the major drawback of merging and slicing is the random permutation procedure, which does not always guarantee complete protection against attribute or membership disclosure. Moreover,… More >

S. Nithyanantham^1,*, G. Singaravel²

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1905-1919, 2022, DOI:10.32604/iasc.2022.022499

Abstract In recent times, a huge amount of data is being created from different sources and the size of the data generated on the Internet has already surpassed two Exabytes. Big Data processing and analysis can be employed in many disciplines which can aid the decision-making process with privacy preservation of users’ private data. To store large quantity of data, Geo-Distributed Data Centres (GDDC) are developed. In recent times, several applications comprising data analytics and machine learning have been designed for GDDC. In this view, this paper presents a hybrid deep learning framework for privacy preservation in distributed DCs. The proposed… More >

Raniyah Wazirali^*

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 767-779, 2022, DOI:10.32604/iasc.2022.019243

Abstract Internet of Things (IoT) has become popular with the rapid development of sensing devices, and it offers a large number of services. Location data is one of the most important information required for IoT systems. With the widespread of Location Based Services (LBS) applications, the privacy and security threats are also emerging. Recently, a large number of studies focused on localization and positioning functionalities, however, the risk associated with user privacy has not been sufficiently addressed so far. Therefore, privacy and security of device location in IoT systems is an active area of research. Since LBS is often exposed to… More >

Lewis Nkenyereye^1,*, S. M. Riazul Islam², Mahmud Hossain³, M. Abdullah-Al-Wadud⁴, Atif Alamri⁴

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 211-221, 2021, DOI:10.32604/cmc.2021.013796

Abstract The Internet of Medical Things (IoMT) offers an infrastructure made of smart medical equipment and software applications for healthcare services. Through the internet, the IoMT is capable of providing remote medical diagnosis and timely health services. The patients can use their smart devices to create, store and share their electronic health records (EHR) with a variety of medical personnel including medical doctors and nurses. However, unless the underlying commination within IoMT is secured, malicious users can intercept, modify and even delete the sensitive EHR data of patients. Patients also lose full control of their EHR since most healthcare services within… More >

Hongyu Chen¹, Shuyu Li^{1, *}, Zhaosheng Zhang¹

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2665-2685, 2020, DOI:10.32604/cmc.2020.010965

Abstract In recent years, mobile Internet technology and location based services have wide application. Application providers and users have accumulated huge amount of trajectory data. While publishing and analyzing user trajectory data have brought great convenience for people, the disclosure risks of user privacy caused by the trajectory data publishing are also becoming more and more prominent. Traditional k-anonymous trajectory data publishing technologies cannot effectively protect user privacy against attackers with strong background knowledge. For privacy preserving trajectory data publishing, we propose a differential privacy based (k-Ψ)-anonymity method to defend against re-identification and probabilistic inference attack. The proposed method is divided… More >

Jun Li^{1, 2}, Jieren Cheng^{2, *}, Naixue Xiong³, Lougao Zhan⁴, Yuan Zhang¹

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 723-741, 2020, DOI:10.32604/cmc.2020.011272

Abstract Security and privacy issues have become a rapidly growing problem with the fast development of big data in public health. However, big data faces many ongoing serious challenges in the process of collection, storage, and use. Among them, data security and privacy problems have attracted extensive interest. In an effort to overcome this challenge, this article aims to present a distributed privacy preservation approach based on smart contracts and Intel Software Guard Extensions (SGX). First of all, we define SGX as a trusted edge computing node, design data access module, data protection module, and data integrity check module, to achieve… More >

Jinlin Wang¹, Xing Wang^{1, *}, Yuchen Yang¹, Hongli Zhang¹, Binxing Fang¹

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1053-1075, 2020, DOI:10.32604/cmc.2020.08675

Abstract Web information system (WIS) is frequently-used and indispensable in daily social life. WIS provides information services in many scenarios, such as electronic commerce, communities, and edutainment. Data cleaning plays an essential role in various WIS scenarios to improve the quality of data service. In this paper, we present a review of the state-of-the-art methods for data cleaning in WIS. According to the characteristics of data cleaning, we extract the critical elements of WIS, such as interactive objects, application scenarios, and core technology, to classify the existing works. Then, after elaborating and analyzing each category, we summarize the descriptions and challenges… More >