Quan Zhou^1,*, Yulong Zheng¹, Minhui Chen², Kaijun Wei²

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2851-2867, 2023, DOI:10.32604/csse.2023.039908

Abstract In recent years, the issue of preserving the privacy of parties involved in blockchain transactions has garnered significant attention. To ensure privacy protection for both sides of the transaction, many researchers are using ring signature technology instead of the original signature technology. However, in practice, identifying the signer of an illegal blockchain transaction once it has been placed on the chain necessitates a signature technique that offers conditional anonymity. Some illegals can conduct illegal transactions and evade the law using ring signatures, which offer perfect anonymity. This paper firstly constructs a conditionally anonymous linkable ring signature using the Diffie-Hellman key… More >

Shahina Anwarul¹, Sunil Kumar², Ashok Bhansali³, Hammam Alshazly^4,*, Hany S. Hussein^5,6

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3145-3163, 2023, DOI:10.32604/csse.2023.041061

Abstract Security systems are the need of the hour to protect data from unauthorized access. The dissemination of confidential information over the public network requires a high level of security. The security approach such as steganography ensures confidentiality, authentication, integrity, and non-repudiation. Steganography helps in hiding the secret data inside the cover media so that the attacker can be confused during the transmission process of secret data between sender and receiver. Therefore, we present an efficient hybrid security model that provides multifold security assurance. To this end, a rectified Advanced Encryption Standard (AES) algorithm is proposed to overcome the problems existing… More >

ZHAOXU YAO^*, HAIBIN MA, LIN LIU, QIAN ZHAO, LONGCHAO QIN, XUEYAN REN, CHUANJUN WU, KAILI SUN

BIOCELL, Vol.47, No.9, pp. 1965-1975, 2023, DOI:10.32604/biocell.2023.030796

Abstract Objective: Through integrated bioinformatics analysis, the goal of this work was to find new, characterised N7-methylguanosine modification-related long non-coding RNAs (m7G-lncRNAs) that might be used to predict the prognosis of laryngeal squamous cell carcinoma (LSCC). Methods: The clinical data and LSCC gene expression data for the current investigation were initially retrieved from the TCGA database & sanitised. Then, using co-expression analysis of m7G-associated mRNAs & lncRNAs & differential expression analysis (DEA) among LSCC & normal sample categories, we discovered lncRNAs that were connected to m7G. The prognosis prediction model was built for the training category using univariate & multivariate COX… More >

Senshan Ouyang^1,2, Xiang Liu², Lei Liu², Shangchao Wang², Baichuan Shao³, Yang Zhao^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 903-915, 2024, DOI:10.32604/cmes.2023.028895

Abstract With the continuous expansion of the Industrial Internet of Things (IIoT), more and more organisations are placing large amounts of data in the cloud to reduce overheads. However, the channel between cloud servers and smart equipment is not trustworthy, so the issue of data authenticity needs to be addressed. The SM2 digital signature algorithm can provide an authentication mechanism for data to solve such problems. Unfortunately, it still suffers from the problem of key exposure. In order to address this concern, this study first introduces a key-insulated scheme, SM2-KI-SIGN, based on the SM2 algorithm. This scheme boasts strong key insulation… More >

WUYAO LIU, CHANGBAO QU, XIAOLU WANG^*

Oncology Research, Vol.31, No.4, pp. 543-567, 2023, DOI:10.32604/or.2023.029563

Abstract The high immune infiltration and heterogeneity of the microenvironment in clear cell renal cell carcinoma (ccRCC) result in the variability of prognosis and clinical response. While PANoptosis has strong immunogenicity and is worthy of further study. In this study, data from The Cancer Genome Atlas database was used to obtain immune-related PANoptosis lncRNAs with prognostic value. Subsequently, the role of these lncRNAs in cancer immunity, progression and the therapeutic response was analyzed, and a new prediction model was constructed. Additionally, we further explored the biological value of PANoptosis-related lncRNAs using single-cell data from the Gene Expression Omnibus database. PANoptosis-associated lncRNAs… More >

BOWEN PENG¹, YUN GE¹, GANG YIN^2,3,*

BIOCELL, Vol.47, No.7, pp. 1519-1535, 2023, DOI:10.32604/biocell.2023.027026

Abstract Background: Tanshinone IIA, one of the main ingredients of Danshen, is used to treat hepatocellular carcinoma (HCC). However, potential targets of the molecule in the therapy of HCC are unknown. Methods: In this study, we collected the tanshinone IIA targets from public databases for investigation. We screened differentially expressed genes (DEGs) across HCC and normal tissues using mRNA expression profiles from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression models were used to identify and construct the prognostic gene signature. Results: Finally, we discovered common genes across tanshinone IIA… More >

Mansoor Farooq^1,*, Mubashir Hassan Khan²

Journal on Internet of Things, Vol.4, No.3, pp. 155-168, 2022, DOI:10.32604/jiot.2022.039271

Abstract An “Intrusion Detection System” (IDS) is a security measure designed to perceive and be aware of unauthorized access or malicious activity on a computer system or network. Signature-based IDSs employ an attack signature database to identify intrusions. This indicates that the system can only identify known attacks and cannot identify brand-new or unidentified assaults. In Wireless 6G IoT networks, signature-based IDSs can be useful to detect a wide range of known attacks such as viruses, worms, and Trojans. However, these networks have specific requirements and constraints, such as the need for real-time detection and low-power operation. To meet these requirements,… More >

Ang Liu^1,2, Xiu-Bo Chen^1,*, Gang Xu³, Zhuo Wang⁴, Xuefen Feng⁵, Huamin Feng⁶

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 259-277, 2023, DOI:10.32604/cmc.2023.039397

Abstract The rapid advancement of quantum technology poses significant security risks to blockchain systems. However, quantum technology can also provide solutions for enhancing blockchain security. In this paper, we propose a quantum-enhanced blockchain scheme to achieve a high level of security against quantum computing attacks. We first discuss quantum computing attacks on classic blockchains, including attacks on hash functions, digital signatures, and consensus mechanisms. We then introduce quantum technologies, such as a quantum hash function (QHF), a quantum digital signature (QDS), and proof of authority (PoA) consensus mechanism, into our scheme to improve the security of the blockchain system. Our security… More >

Chaoyang Li^*, Bohao Jiang, Yanbu Guo, Xiangjun Xin

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 591-606, 2023, DOI:10.32604/cmc.2023.038129

Abstract Blockchain technology promotes the development of the Internet of medical things (IoMT) from the centralized form to distributed trust mode as blockchain-based Internet of medical things (BIoMT). Although blockchain improves the cross-institution data sharing ability, there still exist the problems of authentication difficulty and privacy leakage. This paper first describes the architecture of the BIoMT system and designs an anonymous authentication model for medical data sharing. This BIoMT system is divided into four layers: perceptual, network, platform, and application. The model integrates an anonymous authentication scheme to guarantee secure data sharing in the network ledger. Utilizing the untampered blockchain ledger… More >

M. Muzaffar Hameed^1,2, Rodina Ahmad^1,*, Laiha Mat Kiah¹, Ghulam Murtaza³, Noman Mazhar¹

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1267-1289, 2023, DOI:10.32604/cmc.2023.035063

Abstract Offline signature verification (OfSV) is essential in preventing the falsification of documents. Deep learning (DL) based OfSVs require a high number of signature images to attain acceptable performance. However, a limited number of signature samples are available to train these models in a real-world scenario. Several researchers have proposed models to augment new signature images by applying various transformations. Others, on the other hand, have used human neuromotor and cognitive-inspired augmentation models to address the demand for more signature samples. Hence, augmenting a sufficient number of signatures with variations is still a challenging task. This study proposed OffSig-SinGAN: a deep… More >