Zhe Sun¹, Jiyuan Feng¹, Lihua Yin^1,*, Zixu Zhang², Ran Li¹, Yu Hu¹, Chongning Na³

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1867-1886, 2022, DOI:10.32604/cmc.2022.022290 - 03 November 2021

Abstract Federated learning is a distributed learning framework which trains global models by passing model parameters instead of raw data. However, the training mechanism for passing model parameters is still threatened by gradient inversion, inference attacks, etc. With a lightweight encryption overhead, function encryption is a viable secure aggregation technique in federation learning, which is often used in combination with differential privacy. The function encryption in federal learning still has the following problems: a) Traditional function encryption usually requires a trust third party (TTP) to assign the keys. If a TTP colludes with a server, the… More >

R. Dhaya^1,*, R. Kanthavel²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1625-1639, 2022, DOI:10.32604/cmc.2022.022213 - 03 November 2021

Abstract We propose a dynamic automated infrastructure model for the cloud data centre which is aimed as an efficient service stipulation for the enormous number of users. The data center and cloud computing technologies have been at the moment rendering attention to major research and development efforts by companies, governments, and academic and other research institutions. In that, the difficult task is to facilitate the infrastructure to construct the information available to application-driven services and make business-smart decisions. On the other hand, the challenges that remain are the provision of dynamic infrastructure for applications and information More >

A. S. Anakath^1,*, R. Kannadasan², Niju P. Joseph³, P. Boominathan⁴, G. R. Sreekanth⁵

Computer Systems Science and Engineering, Vol.41, No.2, pp. 479-492, 2022, DOI:10.32604/csse.2022.019940 - 25 October 2021

Abstract Cloud computing is a high network infrastructure where users, owners, third users, authorized users, and customers can access and store their information quickly. The use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing efficiently. This cloud is nowadays highly affected by internal threats of the user. Sensitive applications such as banking, hospital, and business are more likely affected by real user threats. An intruder is presented as a user and set as a member of the network. After becoming an insider… More >

Sana Ben Hamida^1,2, Hichem Mrabet^3,4, Sana Belguith^5,*, Adeeb Alhomoud⁶, Abderrazak Jemai⁷

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4897-4919, 2022, DOI:10.32604/cmc.2022.019709 - 11 October 2021

Abstract From fraud detection to speech recognition, including price prediction, Machine Learning (ML) applications are manifold and can significantly improve different areas. Nevertheless, machine learning models are vulnerable and are exposed to different security and privacy attacks. Hence, these issues should be addressed while using ML models to preserve the security and privacy of the data used. There is a need to secure ML models, especially in the training phase to preserve the privacy of the training datasets and to minimise the information leakage. In this paper, we present an overview of ML threats and vulnerabilities,… More >

Mamoon M. Saeed¹, Mohammad Kamrul Hasan^2,*, Rosilah Hassan² , Rania Mokhtar³ , Rashid A. Saeed^3,4, Elsadig Saeid¹, Manoj Gupta⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5551-5568, 2022, DOI:10.32604/cmc.2022.017338 - 11 October 2021

Abstract

The fifth generation (5G) system is the forthcoming generation of the mobile communication system. It has numerous additional features and offers an extensively high data rate, more capacity, and low latency. However, these features and applications have many problems and issues in terms of security, which has become a great challenge in the telecommunication industry. This paper aimed to propose a solution to preserve the user identity privacy in the 5G system that can identify permanent identity by using Variable Mobile Subscriber Identity, which randomly changes and does not use the permanent identity between the user

… More >

K. Ambika^1,*, M. Balasingh Moses²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1809-1823, 2022, DOI:10.32604/iasc.2022.018580 - 09 October 2021

Abstract In addition to replacing desktop-based methods, cloud computing is playing a significant role in several areas of data management. The health care industry, where so much data is needed to be handled correctly, is another arena in which artificial intelligence has a big role to play. The upshot of this innovation led to the creation of multiple healthcare clouds. The challenge of data privacy and confidentiality is the same for different clouds. Many existing works has provided security framework to ensure the security of data in clouds but still the drawback on revocation, resisting collusion… More >

K. Venkatachalam¹, P. Prabu², B. Saravana Balaji³, Byeong-Gwon Kang⁴, Yunyoung Nam^4,*, Mohamed Abouhawwash^5,6

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3685-3700, 2022, DOI:10.32604/cmc.2022.019502 - 27 September 2021

Abstract Ad hoc mobile cloud computing networks are affected by various issues, like delay, energy consumption, flexibility, infrastructure, network lifetime, security, stability, data transition, and link accomplishment. Given the issues above, route failure is prevalent in ad hoc mobile cloud computing networks, which increases energy consumption and delay and reduces stability. These issues may affect several interconnected nodes in an ad hoc mobile cloud computing network. To address these weaknesses, which raise many concerns about privacy and security, this study formulated clustering-based storage and search optimization approaches using cross-layer analysis. The proposed approaches were formed by cross-layer analysis based… More >

Jinsu Kim¹, Sungwook Ryu², Namje Park^1,3,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4169-4184, 2022, DOI:10.32604/cmc.2022.019277 - 27 September 2021

Abstract A significant number of cloud storage environments are already implementing deduplication technology. Due to the nature of the cloud environment, a storage server capable of accommodating large-capacity storage is required. As storage capacity increases, additional storage solutions are required. By leveraging deduplication, you can fundamentally solve the cost problem. However, deduplication poses privacy concerns due to the structure itself. In this paper, we point out the privacy infringement problem and propose a new deduplication technique to solve it. In the proposed technique, since the user’s map structure and files are not stored on the server, More >

U. Selvi^*, S. Pushpa

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1185-1196, 2022, DOI:10.32604/iasc.2022.020164 - 22 September 2021

Abstract Due to the recent advancement in technologies, a huge amount of data is generated where individual private information needs to be preserved. A proper Anonymization algorithm with increased Data utility is required to protect individual privacy. However, preserving privacy of individuals whileprocessing huge amount of data is a challenging task, as the data contains certain sensitive information. Moreover, scalability issue in handling a large dataset is found in using existing framework. Many an Anonymization algorithm for Big Data have been developed and under research. We propose a method of applying Machine Learning techniques to protect More >

Raniyah Wazirali^*

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 767-779, 2022, DOI:10.32604/iasc.2022.019243 - 22 September 2021

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… More >