Hongliang Tian, Meiruo Li^*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5539-5559, 2025, DOI:10.32604/cmc.2025.060297 - 19 May 2025

Abstract The accelerated advancement of the Internet of Things (IoT) has generated substantial data, including sensitive and private information. Consequently, it is imperative to guarantee the security of data sharing. While facilitating fine-grained access control, Ciphertext Policy Attribute-Based Encryption (CP-ABE) can effectively ensure the confidentiality of shared data. Nevertheless, the conventional centralized CP-ABE scheme is plagued by the issues of key misuse, key escrow, and large computation, which will result in security risks. This paper suggests a lightweight IoT data security sharing scheme that integrates blockchain technology and CP-ABE to address the abovementioned issues. The integrity… More >

Reshma Siyal¹, Muhammad Asim^2,*, Long Jun¹, Mohammed Elaffendi², Sundas Iftikhar³, Rana Alnashwan⁴, Samia Allaoua Chelloug^4,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2637-2664, 2025, DOI:10.32604/cmc.2025.058717 - 17 February 2025

Abstract A basic procedure for transforming readable data into encoded forms is encryption, which ensures security when the right decryption keys are used. Hadoop is susceptible to possible cyber-attacks because it lacks built-in security measures, even though it can effectively handle and store enormous datasets using the Hadoop Distributed File System (HDFS). The increasing number of data breaches emphasizes how urgently creative encryption techniques are needed in cloud-based big data settings. This paper presents Adaptive Attribute-Based Honey Encryption (AABHE), a state-of-the-art technique that combines honey encryption with Ciphertext-Policy Attribute-Based Encryption (CP-ABE) to provide improved data security. More >

Congcong Wang¹, Chen Wang^2,3,*, Wenying Zheng^4,*, Wei Gu⁵

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 799-816, 2025, DOI:10.32604/cmc.2024.057975 - 03 January 2025

Abstract As smart grid technology rapidly advances, the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection. Current research emphasizes data security and user privacy concerns within smart grids. However, existing methods struggle with efficiency and security when processing large-scale data. Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge. This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities. The approach optimizes data preprocessing, More >

Khadija El Fellah^1,*, Ikram El Azami^2,*, Adil El Makrani², Habiba Bouijij³, Oussama El Azzouzy⁴

Computer Systems Science and Engineering, Vol.49, pp. 99-122, 2025, DOI:10.32604/csse.2024.057754 - 03 January 2025

Abstract The rapid growth of the automotive industry has raised significant concerns about the security of connected vehicles and their integrated supply chains, which are increasingly vulnerable to advanced cyber threats. Traditional authentication methods have proven insufficient, exposing systems to risks such as Sybil, Denial of Service (DoS), and Eclipse attacks. This study critically examines the limitations of current security protocols, focusing on authentication and data exchange vulnerabilities, and explores blockchain technology as a potential solution. Blockchain’s decentralized and cryptographically secure framework can significantly enhance Vehicle-to-Vehicle (V2V) communication, ensure data integrity, and enable transparent, immutable transactions More >

Nagaraju Pacharla, K. Srinivasa Reddy^*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3089-3110, 2024, DOI:10.32604/cmc.2024.048133 - 15 May 2024

Abstract With the recent technological developments, massive vehicular ad hoc networks (VANETs) have been established, enabling numerous vehicles and their respective Road Side Unit (RSU) components to communicate with one another. The best way to enhance traffic flow for vehicles and traffic management departments is to share the data they receive. There needs to be more protection for the VANET systems. An effective and safe method of outsourcing is suggested, which reduces computation costs by achieving data security using a homomorphic mapping based on the conjugate operation of matrices. This research proposes a VANET-based data outsourcing… More >

Umi Salma Basha¹, Shashi Kant Gupta², Wedad Alawad³, SeongKi Kim^4,*, Salil Bharany^5,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3397-3416, 2024, DOI:10.32604/cmc.2024.046265 - 15 May 2024

Abstract A new era of data access and management has begun with the use of cloud computing in the healthcare industry. Despite the efficiency and scalability that the cloud provides, the security of private patient data is still a major concern. Encryption, network security, and adherence to data protection laws are key to ensuring the confidentiality and integrity of healthcare data in the cloud. The computational overhead of encryption technologies could lead to delays in data access and processing rates. To address these challenges, we introduced the Enhanced Parallel Multi-Key Encryption Algorithm (EPM-KEA), aiming to bolster… More >

Aodi Liu, Na Wang^*, Xuehui Du, Dibin Shan, Xiangyu Wu, Wenjuan Wang

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1705-1726, 2024, DOI:10.32604/cmc.2024.049011 - 25 April 2024

Abstract Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access control mechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policy management efficiency and difficulty in accurately describing the access control policy. To overcome these problems, this paper proposes a big data access control mechanism based on a two-layer permission decision structure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes are introduced in the ABAC model as business constraints between entities. The proposed mechanism implements a two-layer permission decision structure composed… More >

Nannan Wu¹, Xianyi Chen^1,*, James Msughter Adeke², Junjie Zhao²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3001-3019, 2024, DOI:10.32604/cmc.2023.045311 - 26 March 2024

Abstract Recently, deep image-hiding techniques have attracted considerable attention in covert communication and high-capacity information hiding. However, these approaches have some limitations. For example, a cover image lacks self-adaptability, information leakage, or weak concealment. To address these issues, this study proposes a universal and adaptable image-hiding method. First, a domain attention mechanism is designed by combining the Atrous convolution, which makes better use of the relationship between the secret image domain and the cover image domain. Second, to improve perceived human similarity, perceptual loss is incorporated into the training process. The experimental results are promising, with More >

Syeda Wajiha Zahra¹, Muhammad Nadeem², Ali Arshad^3,*, Saman Riaz³, Muhammad Abu Bakr⁴, Ashit Kumar Dutta⁵, Zaid Alzaid⁶, Badr Almutairi⁷, Sultan Almotairi⁸

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 589-616, 2024, DOI:10.32604/cmc.2023.042386 - 30 January 2024

Abstract Various organizations store data online rather than on physical servers. As the number of user’s data stored in cloud servers increases, the attack rate to access data from cloud servers also increases. Different researchers worked on different algorithms to protect cloud data from replay attacks. None of the papers used a technique that simultaneously detects a full-message and partial-message replay attack. This study presents the development of a TKN (Text, Key and Name) cryptographic algorithm aimed at protecting data from replay attacks. The program employs distinct ways to encrypt plain text [P], a user-defined Key… More >

Sanxiu Jiao¹, Lecai Cai^2,*, Jintao Meng³, Yue Zhao³, Kui Cheng²

Computer Systems Science and Engineering, Vol.48, No.1, pp. 247-265, 2024, DOI:10.32604/csse.2023.040194 - 26 January 2024

Abstract Federated learning is a distributed machine learning framework that solves data security and data island problems faced by artificial intelligence. However, federated learning frameworks are not always secure, and attackers can attack customer privacy information by analyzing parameters in the training process of federated learning models. To solve the problems of data security and availability during federated learning training, this paper proposes an Efficient Differential Privacy Federated Learning Algorithm based on early stopping mechanism (Efficient DP-FL). This method inherits the advantages of differential privacy and federated learning and improves the performance of model training while More >