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  • Open Access

    ARTICLE

    A Cross Language Code Security Audit Framework Based on Normalized Representation

    Yong Chen1,*, 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 >

  • Open Access

    ARTICLE

    Spatial Multi-Presence System to Increase Security Awareness for Remote Collaboration in an Extended Reality Environment

    Jun Lee1, Hyun Kwon2,*

    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 >

  • Open Access

    ARTICLE

    Intrusion Detection System Through Deep Learning in Routing MANET Networks

    Zainab Ali Abbood1,2,*, Doğu Çağdaş Atilla3,4, 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 >

  • Open Access

    ARTICLE

    Multi-Attack Intrusion Detection System for Software-Defined Internet of Things Network

    Tarcízio Ferrão1,*, 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 >

  • Open Access

    ARTICLE

    An Effective Security Comparison Protocol in Cloud Computing

    Yuling Chen1,2, Junhong Tao1, Tao Li1,*, 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 >

  • Open Access

    ARTICLE

    A Secure Energy Internet Scheme for IoV Based on Post-Quantum Blockchain

    Jiansheng Zhang1, Yang Xin1,*, 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 >

  • Open Access

    ARTICLE

    Biometric Finger Vein Recognition Using Evolutionary Algorithm with Deep Learning

    Mohammad Yamin1,*, 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 >

  • Open Access

    ARTICLE

    A Novel Approach for Security Enhancement of Data Encryption Standard

    Dawood Shah1,*, 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 >

  • Open Access

    ARTICLE

    Vulnerability Detection of Ethereum Smart Contract Based on SolBERT-BiGRU-Attention Hybrid Neural Model

    Guangxia Xu1,*, 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 >

  • Open Access

    ARTICLE

    Feature Selection with Deep Reinforcement Learning for Intrusion Detection System

    S. Priya1,*, 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 >

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