Yong Chen^1,*, Chao Xu¹, Jing Selena He², Sheng Xiao³

Journal of Quantum Computing, Vol.4, No.2, pp. 75-84, 2022, DOI:10.32604/jqc.2022.031312

Abstract With the rapid development of information technology, audit objects and audit itself are more and more inseparable from software. As an important means of software security audit, code security audit will become an important aspect of future audit that cannot be ignored. However, the existing code security audit is mainly based on source code, which is difficult to meet the audit needs of more and more programming languages and binary commercial software. Based on the idea of normalized transformation, this paper constructs a cross language code security audit framework (CLCSA). CLCSA first uses compile/decompile technology to convert different high-level programming… More >

Jun Lee¹, Hyun Kwon^2,*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 369-384, 2023, DOI:10.32604/iasc.2023.036052

Abstract Enhancing the sense of presence of participants is an important issue in terms of security awareness for remote collaboration in extended reality. However, conventional methods are insufficient to be aware of remote situations and to search for and control remote workspaces. This study proposes a spatial multi-presence system that simultaneously provides multiple spaces while rapidly exploring these spaces as users perform collaborative work in an extended reality environment. The proposed system provides methods for arranging and manipulating remote and personal spaces by creating an annular screen that is invisible to the user. The user can freely arrange remote participants and… More >

Zainab Ali Abbood^1,2,*, Doğu Çağdaş Atilla^3,4, Çağatay Aydin⁵

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 269-281, 2023, DOI:10.32604/iasc.2023.035276

Abstract Deep learning (DL) is a subdivision of machine learning (ML) that employs numerous algorithms, each of which provides various explanations of the data it consumes; mobile ad-hoc networks (MANET) are growing in prominence. For reasons including node mobility, due to MANET’s potential to provide small-cost solutions for real-world contact challenges, decentralized management, and restricted bandwidth, MANETs are more vulnerable to security threats. When protecting MANETs from attack, encryption and authentication schemes have their limits. However, deep learning (DL) approaches in intrusion detection systems (IDS) can adapt to the changing environment of MANETs and allow a system to make intrusion decisions… More >

Tarcízio Ferrão^1,*, Franklin Manene², Adeyemi Abel Ajibesin³

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4985-5007, 2023, DOI:10.32604/cmc.2023.038276

Abstract Currently, the Internet of Things (IoT) is revolutionizing communication technology by facilitating the sharing of information between different physical devices connected to a network. To improve control, customization, flexibility, and reduce network maintenance costs, a new Software-Defined Network (SDN) technology must be used in this infrastructure. Despite the various advantages of combining SDN and IoT, this environment is more vulnerable to various attacks due to the centralization of control. Most methods to ensure IoT security are designed to detect Distributed Denial-of-Service (DDoS) attacks, but they often lack mechanisms to mitigate their severity. This paper proposes a Multi-Attack Intrusion Detection System… More >

Yuling Chen^1,2, Junhong Tao¹, Tao Li^1,*, Jiangyuan Cai³, Xiaojun Ren⁴

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5141-5158, 2023, DOI:10.32604/cmc.2023.037783

Abstract With the development of cloud computing technology, more and more data owners upload their local data to the public cloud server for storage and calculation. While this can save customers’ operating costs, it also poses privacy and security challenges. Such challenges can be solved using secure multi-party computation (SMPC), but this still exposes more security issues. In cloud computing using SMPC, clients need to process their data and submit the processed data to the cloud server, which then performs the calculation and returns the results to each client. Each client and server must be honest. If there is cooperation or… More >

Jiansheng Zhang¹, Yang Xin^1,*, Yuyan Wang², Xiaohui Lei², Yixian Yang¹

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6323-6336, 2023, DOI:10.32604/cmc.2023.034668

Abstract With the increasing use of distributed electric vehicles (EV), energy management in the Internet of vehicles (IoV) has attracted more attention, especially demand response (DR) management to achieve efficient energy management in IoV. Therefore, it is a tendency to introduce distributed energy such as renewable energy into the existing supply system. For optimizing the energy internet (EI) for IoV, in this paper, we introduce blockchain into energy internet and propose a secure EI scheme for IoV based on post-quantum blockchain, which provides the new information services and an incentive cooperation mechanism for the current energy IoV system. Firstly, based on… More >

Mohammad Yamin^1,*, Tom Gedeon², Saleh Bajaba³, Mona M. Abusurrah⁴

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5659-5674, 2023, DOI:10.32604/cmc.2023.034005

Abstract In recent years, the demand for biometric-based human recognition methods has drastically increased to meet the privacy and security requirements. Palm prints, palm veins, finger veins, fingerprints, hand veins and other anatomic and behavioral features are utilized in the development of different biometric recognition techniques. Amongst the available biometric recognition techniques, Finger Vein Recognition (FVR) is a general technique that analyzes the patterns of finger veins to authenticate the individuals. Deep Learning (DL)-based techniques have gained immense attention in the recent years, since it accomplishes excellent outcomes in various challenging domains such as computer vision, speech detection and Natural Language… More >

Dawood Shah^1,*, Tariq Shah¹, Sajjad Shaukat Jamal², Mohammad Mazyad Hazzazi², Amer Aljaedi³, Adel R. Alharbi³

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5073-5086, 2023, DOI:10.32604/cmc.2023.020513

Abstract Data Encryption Standard (DES) is a symmetric key cryptosystem that is applied in different cryptosystems of recent times. However, researchers found defects in the main assembling of the DES and declared it insecure against linear and differential cryptanalysis. In this paper, we have studied the faults and made improvements in their internal structure and get the new algorithm for Improved DES. The improvement is being made in the substitution step, which is the only nonlinear component of the algorithm. This alteration provided us with great outcomes and increase the strength of DES. Accordingly, a novel good quality S-box construction scheme… More >

Guangxia Xu^1,*, Lei Liu², Jingnan Dong³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 903-922, 2023, DOI:10.32604/cmes.2023.026627

Abstract In recent years, with the great success of pre-trained language models, the pre-trained BERT model has been gradually applied to the field of source code understanding. However, the time cost of training a language model from zero is very high, and how to transfer the pre-trained language model to the field of smart contract vulnerability detection is a hot research direction at present. In this paper, we propose a hybrid model to detect common vulnerabilities in smart contracts based on a lightweight pre-trained language model BERT and connected to a bidirectional gate recurrent unit model. The downstream neural network adopts… More >

S. Priya^1,*, K. Pradeep Mohan Kumar²

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3339-3353, 2023, DOI:10.32604/csse.2023.030630

Abstract An intrusion detection system (IDS) becomes an important tool for ensuring security in the network. In recent times, machine learning (ML) and deep learning (DL) models can be applied for the identification of intrusions over the network effectively. To resolve the security issues, this paper presents a new Binary Butterfly Optimization algorithm based on Feature Selection with DRL technique, called BBOFS-DRL for intrusion detection. The proposed BBOFSDRL model mainly accomplishes the recognition of intrusions in the network. To attain this, the BBOFS-DRL model initially designs the BBOFS algorithm based on the traditional butterfly optimization algorithm (BOA) to elect feature subsets.… More >