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 >

Zhen Yang¹, Hongao Zhang¹, Haiyang Yu^1,*, Zheng Li¹, Bocheng Zhu¹, Richard O. Sinnott²

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 269-282, 2021, DOI:10.32604/cmes.2021.015210

Abstract To address privacy concerns, data in the blockchain should be encrypted in advance to avoid data access from all users in the blockchain. However, encrypted data cannot be directly retrieved, which hinders data sharing in the blockchain. Several works have been proposed to deal with this problem. However, the data retrieval in these schemes requires the participation of data owners and lacks finer-grained access control. In this paper, we propose an attribute-based keyword search scheme over the encrypted blockchain, which allows users to search encrypted files over the blockchain based on their attributes. In addition, we build a file chain… 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 >

Shiqi Wang¹, Mingfang Jiang^2,*, Jiaohua Qin¹, Hengfu Yang², Zhichen Gao³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2979-2993, 2021, DOI:10.32604/cmc.2021.017094

Abstract In the era of big data, outsourcing massive data to a remote cloud server is a promising approach. Outsourcing storage and computation services can reduce storage costs and computational burdens. However, public cloud storage brings about new privacy and security concerns since the cloud servers can be shared by multiple users. Privacy-preserving feature extraction techniques are an effective solution to this issue. Because the Rotation Invariant Local Binary Pattern (RILBP) has been widely used in various image processing fields, we propose a new privacy-preserving outsourcing computation of RILBP over encrypted images in this paper (called PPRILBP). To protect image content,… More >

Romany F. Mansour^1,*, Moheb R. Girgis²

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4069-4085, 2021, DOI:10.32604/cmc.2021.017064

Abstract Steganography is one of the best techniques to hide secret data. Several steganography methods are available that use an image as a cover object, which is called image steganography. In image steganography, the major features are the cover object quality and hiding data capacity. Due to poor image quality, attackers could easily hack the secret data. Therefore, the hidden data quantity should be improved, while keeping stego-image quality high. The main aim of this study is combining several steganography techniques, for secure transmission of data without leakage and unauthorized access. In this paper, a technique, which combines various steganography-based techniques,… More >

Chungen Xu^1,*, Lin Mei¹, Jinxue Cheng², Yu Zhao¹, Cong Zuo³

Journal of Cyber Security, Vol.3, No.1, pp. 55-67, 2021, DOI:10.32604/jcs.2021.017217

Abstract With the rapid development of wireless communication technology, the Internet of Things is playing an increasingly important role in our everyday. The amount of data generated by sensor devices is increasing as a large number of connectable devices are deployed in many fields, including the medical, agricultural, and industrial areas. Uploading data to the cloud solves the problem of data overhead but results in privacy issues. Therefore, the question of how to manage the privacy of uploading data and make it available to be interconnected between devices is a crucial issue. In this paper, we propose a scheme that supports… More >

Lin Mei¹, Chungen Xu^1,*, Lei Xu¹, Xiaoling Yu², Cong Zuo³

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2299-2314, 2021, DOI:10.32604/cmc.2021.017216

Abstract Internet of Things (IoT), which provides the solution of connecting things and devices, has increasingly developed as vital tools to realize intelligent life. Generally, source-limited IoT sensors outsource their data to the cloud, which arises the concerns that the transmission of IoT data is happening without appropriate consideration of the profound security challenges involved. Though encryption technology can guarantee the confidentiality of private data, it hinders the usability of data. Searchable encryption (SE) has been proposed to achieve secure data sharing and searching. However, most of existing SE schemes are designed under conventional hardness assumptions and may be vulnerable to… More >

Jianyi Liu¹, Ru Zhang^1,*, Jing Li², Lei Guan³, Cheng Jie², Jiaping Gui⁴

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2633-2649, 2021, DOI:10.32604/cmc.2021.016605

Abstract Reversible data hiding in encrypted image (RDHEI) is a widely used technique for privacy protection, which has been developed in many applications that require high confidentiality, authentication and integrity. Proposed RDHEI methods do not allow high embedding rate while ensuring losslessly recover the original image. Moreover, the ciphertext form of encrypted image in RDHEI framework is easy to cause the attention of attackers. This paper proposes a reversible data hiding algorithm based on image camouflage encryption and bit plane compression. A camouflage encryption algorithm is used to transform a secret image into another meaningful target image, which can cover both… More >

Alsehli Abrar¹, Wadood Abdul^1,*, Sanaa Ghouzali²

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 577-591, 2021, DOI:10.32604/iasc.2021.016382

Abstract Image authentication is an important field that employs many different approaches and has several significant applications. In the proposed approach, we used a combination of two techniques to achieve authentication. Image watermarking is one of the techniques that has been used in many studies but the authentication field still needs to be studied. Blockchain technology is a relatively new technology that has significant research potential related to image authentication. The watermark is embedded into the third-level discrete wavelet transform (DWT) in the middle frequency regions to achieve security and imperceptibility goals. Peak signal-to-noise ratio PSNR, structural similarity matrix (SSIM), normalized… More >

Jamal Kh-Madhloom^1,2,*, Mohd Khanapi Abd Ghani¹, Mohd Rizuan Baharon¹

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 493-512, 2021, DOI:10.32604/iasc.2021.015129

Abstract Over the decades, protecting the privacy of a health cloud using the design of a fog computing network is a very important field and will be more important in the near future. Current Internet of Things (IoT) research includes security and privacy due to their extreme importance in any growing technology that involves the implementation of cryptographic Internet communications (ICs) for protected IC applications such as fog computing and cloud computing devices. In addition, the implementation of public-key cryptography for IoT-based DNA sequence testing devices requires considerable expertise. Any key can be broken by using a brute-force attack with ample… More >