D. Dhinakaran^1,*, P. M. Joe Prathap²

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1877-1892, 2022, DOI:10.32604/iasc.2022.024509

Abstract These days, investigations of information are becoming essential for various associations all over the globe. By and large, different associations need to perform information examinations on their joined data sets. Privacy and security have become a relentless concern wherein business experts do not desire to contribute their classified transaction data. Therefore, there is a requirement to build a proficient methodology that can process the broad mixture of data and convert those data into meaningful knowledge to the user without forfeiting the security and privacy of individuals’ crude information. We devised two unique protocols for frequent mining itemsets in horizontally partitioned… More >

Yichuan Liu¹, Chungen Xu^1,*, Lei Xu¹, Lin Mei¹, Xing Zhang², Cong Zuo³

Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 151-164, 2021, DOI:10.32604/jihpp.2021.026944

Abstract The widespread acceptance of machine learning, particularly of neural networks leads to great success in many areas, such as recommender systems, medical predictions, and recognition. It is becoming possible for any individual with a personal electronic device and Internet access to complete complex machine learning tasks using cloud servers. However, it must be taken into consideration that the data from clients may be exposed to cloud servers. Recent work to preserve data confidentiality has allowed for the outsourcing of services using homomorphic encryption schemes. But these architectures are based on honest but curious cloud servers, which are unable to tell… More >

G. Tamilarasi^1,*, K. Rajiv Gandhi², V. Palanisamy¹

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1273-1288, 2022, DOI:10.32604/iasc.2022.024687

Abstract In recent years, vehicle ad hoc networks (VANETs) have garnered considerable interest in the field of intelligent transportation systems (ITS) due to the added safety and preventive measures for drivers and passengers. Regardless of the benefits provided by VANET, it confronts various challenges, most notably in terms of user/message security and privacy. Due to the decentralised nature of VANET and its changeable topologies, it is difficult to detect rogue or malfunctioning nodes or users. Using an improved grasshopper optimization algorithm (IGOA-PHE) technique in VANETs, this research develops a new privacy-preserving partly homomorphic encryption with optimal key generation. The suggested IGOA-PHE… More >

Aitizaz Ali¹, Mehedi Masud², Ateeq ur Rehman³, Can Chen¹, Mehmood⁴, Mohammad A. AlZain⁵, Jehad Ali^6,*

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1183-1195, 2022, DOI:10.32604/iasc.2022.023930

Abstract Security of Patient health records (PHR) is the most important aspect of cryptography over the Internet due to its value and importance preferably in the medical Internet of Things (IoT). Search keywords access mechanism is one of the common approaches which is used to access PHR from database, but it is susceptible to various security vulnerabilities. Although Blockchain-enabled healthcare systems provide security, but it may lead to some loopholes in the existing schemes. However, these methods primarily focused on data storage, and blockchain is used as a database. In this paper, Blockchain as a distributed database is proposed with homomorphic… More >

Amira Baumy¹, Abeer D. Algarni^2,*, Mahmoud Abdalla³, Walid El-Shafai^4,5, Fathi E. Abd El-Samie^3,4, Naglaa F. Soliman^2,3

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3257-3276, 2022, DOI:10.32604/cmc.2022.021047

Abstract This paper is concerned with a vital topic in image processing: color image forgery detection. The development of computing capabilities has led to a breakthrough in hacking and forgery attacks on signal, image, and data communicated over networks. Hence, there is an urgent need for developing efficient image forgery detection algorithms. Two main types of forgery are considered in this paper: splicing and copy-move. Splicing is performed by inserting a part of an image into another image. On the other hand, copy-move forgery is performed by copying a part of the image into another position in the same image. The… More >

Hao Yan^1,2, Yanan Liu¹, Shuo Qiu¹, Shengzhou Hu³, Weijian Zhang^4,*, Jinyue Xia⁵

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1129-1142, 2022, DOI:10.32604/csse.2022.022317

Abstract With the rapidly developing of Internet of Things (IoT), the volume of data generated by IoT systems is increasing quickly. To release the pressure of data management and storage, more and more enterprises and individuals prefer to integrate cloud service with IoT systems, in which the IoT data can be outsourced to cloud server. Since cloud service provider (CSP) is not fully trusted, a variety of methods have been proposed to deal with the problem of data integrity checking. In traditional data integrity audition schemes, the task of data auditing is usually performed by Third Party Auditor (TPA) which is… More >

Haining Yu¹, Lailai Yin^1,*, Hongli Zhang¹, Dongyang Zhan^1,2, Jiaxing Qu³, Guangyao Zhang⁴

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3445-3458, 2021, DOI:10.32604/cmc.2021.019462

Abstract Road networks have been used in a wide range of applications to reduces the cost of transportation and improve the quality of related services. The shortest road distance computation has been considered as one of the most fundamental operations of road networks computation. To alleviate privacy concerns about location privacy leaks during road distance computation, it is desirable to have a secure and efficient road distance computation approach. In this paper, we propose two secure road distance computation approaches, which can compute road distance over encrypted data efficiently. An approximate road distance computation approach is designed by using Partially Homomorphic… More >

Jianping Yu^1,2,3, Zhuqing Qiao¹, Wensheng Tang^1,2,3,*, Danni Wang¹, Xiaojun Cao⁴

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 713-728, 2021, DOI:10.32604/iasc.2021.017154

Abstract In a distributed system such as Internet of things, the data volume from each node may be limited. Such limited data volume may constrain the performance of the machine learning classification model. How to effectively improve the performance of the classification in a distributed system has been a challenging problem in the field of data mining. Sharing data in the distributed network can enlarge the training data volume and improve the machine learning classification model’s accuracy. In this work, we take data sharing and the quality of shared data into consideration and propose an efficient Blockchain-based ID3 Decision Tree Classification… More >

Muhammad Tayyab^1,*, Mohsen Marjani¹, N. Z. Jhanjhi¹, Ibrahim Abaker Targio Hashim², Abdulwahab Ali Almazroi³, Abdulaleem Ali Almazroi⁴

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1183-1200, 2021, DOI:10.32604/cmc.2021.017199

Abstract Deep learning (DL) algorithms have been widely used in various security applications to enhance the performances of decision-based models. Malicious data added by an attacker can cause several security and privacy problems in the operation of DL models. The two most common active attacks are poisoning and evasion attacks, which can cause various problems, including wrong prediction and misclassification of decision-based models. Therefore, to design an efficient DL model, it is crucial to mitigate these attacks. In this regard, this study proposes a secure neural network (NN) model that provides data security during model training and testing phases. The main… More >

Xin Chen¹, Ying Zhang², Lang Lin¹, Junxiang Wang^2,*, Jiangqun Ni³

Computer Systems Science and Engineering, Vol.36, No.3, pp. 551-564, 2021, DOI:10.32604/csse.2021.014495

Abstract Nowadays the computer vision technique has widely found applications in industrial manufacturing process to improve their efficiency. However, it is hardly applied in the field of daily ceramic detection due to the following two key reasons: (1) Low detection accuracy as a result of ceramic glare, and (2) Lack of efficient detection algorithms. To tackle these problems, a homomorphic filtering based anti-glare ceramic decals defect detection technique is proposed in this paper. Considering that smooth ceramic surface usually causes glare effects and leads to low detection results, in our approach, the ceramic samples are taken in low light environment and… More >