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Multimedia Encryption and Information Security

Submission Deadline: 31 December 2023 (closed)

Guest Editors

Dr. Jawad Ahmad, Edinburgh Napier University, UK.
Dr. Mujeeb Ur Rehman, University of Glasgow, Scotland.
Prof. Muazzam A Khan, Quaid-i-Azam University, Pakistan.

Summary

The practice of transferring digital data via the Internet is expanding exponentially. While this boosts convenience and accessibility, each technological advancement also introduces additional obstacles. Providing proper security for data transmission via insecure communication networks is one of the unavoidable concerns. The number of connected users and their different Internet activities increase daily. Consequently, the quantity and variety of potential cyberattacks have risen. In today's world, data is an organization's most valuable asset, posing additional issues. Because attackers may utilise the open public Internet for exploitative or criminal objectives, protecting sensitive data from unauthorised access has become a top responsibility. Before sensitive data may be communicated across unencrypted networks, it must be converted into cipherable forms to prevent such attacks. In this regard, we encourage academics to submit original research articles as well as review articles that will aim to explore novel solutions for multimedia encryption and information security.


Keywords

Information Security; Image Encryption; Network Security; Cybersecurity, Cryptography

Published Papers


  • Open Access

    ARTICLE

    Securing Cloud-Encrypted Data: Detecting Ransomware-as-a-Service (RaaS) Attacks through Deep Learning Ensemble

    Amardeep Singh, Hamad Ali Abosaq, Saad Arif, Zohaib Mushtaq, Muhammad Irfan, Ghulam Abbas, Arshad Ali, Alanoud Al Mazroa
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2024.048036
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries, especially in light of the growing number of cybersecurity threats. A major and ever-present threat is Ransomware-as-a-Service (RaaS) assaults, which enable even individuals with minimal technical knowledge to conduct ransomware operations. This study provides a new approach for RaaS attack detection which uses an ensemble of deep learning models. For this purpose, the network intrusion detection dataset “UNSW-NB15” from the Intelligent Security Group of the University of New South Wales, Australia is analyzed. In the initial phase, the rectified linear… More >

  • Open Access

    ARTICLE

    A Hybrid and Lightweight Device-to-Server Authentication Technique for the Internet of Things

    Shaha Al-Otaibi, Rahim Khan, Hashim Ali, Aftab Ahmed Khan, Amir Saeed, Jehad Ali
    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3805-3823, 2024, DOI:10.32604/cmc.2024.049017
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract The Internet of Things (IoT) is a smart networking infrastructure of physical devices, i.e., things, that are embedded with sensors, actuators, software, and other technologies, to connect and share data with the respective server module. Although IoTs are cornerstones in different application domains, the device’s authenticity, i.e., of server(s) and ordinary devices, is the most crucial issue and must be resolved on a priority basis. Therefore, various field-proven methodologies were presented to streamline the verification process of the communicating devices; however, location-aware authentication has not been reported as per our knowledge, which is a crucial metric, especially in scenarios where… More >

  • Open Access

    ARTICLE

    Applying an Improved Dung Beetle Optimizer Algorithm to Network Traffic Identification

    Qinyue Wu, Hui Xu, Mengran Liu
    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4091-4107, 2024, DOI:10.32604/cmc.2024.048461
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract Network traffic identification is critical for maintaining network security and further meeting various demands of network applications. However, network traffic data typically possesses high dimensionality and complexity, leading to practical problems in traffic identification data analytics. Since the original Dung Beetle Optimizer (DBO) algorithm, Grey Wolf Optimization (GWO) algorithm, Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) algorithm have the shortcomings of slow convergence and easily fall into the local optimal solution, an Improved Dung Beetle Optimizer (IDBO) algorithm is proposed for network traffic identification. Firstly, the Sobol sequence is utilized to initialize the dung beetle population, laying the… More >

  • Open Access

    ARTICLE

    Secure Transmission of Compressed Medical Image Sequences on Communication Networks Using Motion Vector Watermarking

    Rafi Ullah, Mohd Hilmi bin Hasan, Sultan Daud Khan, Mussadiq Abdul Rahim
    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3283-3301, 2024, DOI:10.32604/cmc.2024.046305
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract Medical imaging plays a key role within modern hospital management systems for diagnostic purposes. Compression methodologies are extensively employed to mitigate storage demands and enhance transmission speed, all while upholding image quality. Moreover, an increasing number of hospitals are embracing cloud computing for patient data storage, necessitating meticulous scrutiny of server security and privacy protocols. Nevertheless, considering the widespread availability of multimedia tools, the preservation of digital data integrity surpasses the significance of compression alone. In response to this concern, we propose a secure storage and transmission solution for compressed medical image sequences, such as ultrasound images, utilizing a motion… More >

  • Open Access

    REVIEW

    A Comprehensive Survey for Privacy-Preserving Biometrics: Recent Approaches, Challenges, and Future Directions

    Shahriar Md Arman, Tao Yang, Shahadat Shahed, Alanoud Al Mazroa, Afraa Attiah, Linda Mohaisen
    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2087-2110, 2024, DOI:10.32604/cmc.2024.047870
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract The rapid growth of smart technologies and services has intensified the challenges surrounding identity authentication techniques. Biometric credentials are increasingly being used for verification due to their advantages over traditional methods, making it crucial to safeguard the privacy of people’s biometric data in various scenarios. This paper offers an in-depth exploration for privacy-preserving techniques and potential threats to biometric systems. It proposes a noble and thorough taxonomy survey for privacy-preserving techniques, as well as a systematic framework for categorizing the field’s existing literature. We review the state-of-the-art methods and address their advantages and limitations in the context of various biometric… More >

  • Open Access

    ARTICLE

    Performance Comparison of Hyper-V and KVM for Cryptographic Tasks in Cloud Computing

    Nader Abdel Karim, Osama A. Khashan, Waleed K. Abdulraheem, Moutaz Alazab, Hasan Kanaker, Mahmoud E. Farfoura, Mohammad Alshinwan
    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2023-2045, 2024, DOI:10.32604/cmc.2023.044304
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract As the extensive use of cloud computing raises questions about the security of any personal data stored there, cryptography is being used more frequently as a security tool to protect data confidentiality and privacy in the cloud environment. A hypervisor is a virtualization software used in cloud hosting to divide and allocate resources on various pieces of hardware. The choice of hypervisor can significantly impact the performance of cryptographic operations in the cloud environment. An important issue that must be carefully examined is that no hypervisor is completely superior in terms of performance; Each hypervisor should be examined to meet… More >

  • Open Access

    ARTICLE

    Utilizing Machine Learning with Unique Pentaplet Data Structure to Enhance Data Integrity

    Abdulwahab Alazeb
    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2995-3014, 2023, DOI:10.32604/cmc.2023.043173
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract Data protection in databases is critical for any organization, as unauthorized access or manipulation can have severe negative consequences. Intrusion detection systems are essential for keeping databases secure. Advancements in technology will lead to significant changes in the medical field, improving healthcare services through real-time information sharing. However, reliability and consistency still need to be solved. Safeguards against cyber-attacks are necessary due to the risk of unauthorized access to sensitive information and potential data corruption. Disruptions to data items can propagate throughout the database, making it crucial to reverse fraudulent transactions without delay, especially in the healthcare industry, where real-time… More >

  • Open Access

    ARTICLE

    Intrusion Detection System with Customized Machine Learning Techniques for NSL-KDD Dataset

    Mohammed Zakariah, Salman A. AlQahtani, Abdulaziz M. Alawwad, Abdullilah A. Alotaibi
    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 4025-4054, 2023, DOI:10.32604/cmc.2023.043752
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract Modern networks are at risk from a variety of threats as a result of the enormous growth in internet-based traffic. By consuming time and resources, intrusive traffic hampers the efficient operation of network infrastructure. An effective strategy for preventing, detecting, and mitigating intrusion incidents will increase productivity. A crucial element of secure network traffic is Intrusion Detection System (IDS). An IDS system may be host-based or network-based to monitor intrusive network activity. Finding unusual internet traffic has become a severe security risk for intelligent devices. These systems are negatively impacted by several attacks, which are slowing computation. In addition, networked… More >

  • Open Access

    ARTICLE

    A Mathematical Approach for Generating a Highly Non-Linear Substitution Box Using Quadratic Fractional Transformation

    Abid Mahboob, Muhammad Asif, Rana Muhammad Zulqarnain, Imran Saddique, Hijaz Ahmad, Sameh Askar
    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2565-2578, 2023, DOI:10.32604/cmc.2023.040371
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract Nowadays, one of the most important difficulties is the protection and privacy of confidential data. To address these problems, numerous organizations rely on the use of cryptographic techniques to secure data from illegal activities and assaults. Modern cryptographic ciphers use the non-linear component of block cipher to ensure the robust encryption process and lawful decoding of plain data during the decryption phase. For the designing of a secure substitution box (S-box), non-linearity (NL) which is an algebraic property of the S-box has great importance. Consequently, the main focus of cryptographers is to achieve the S-box with a high value of… More >

  • Open Access

    ARTICLE

    A Novel Approach for Image Encryption with Chaos-RNA

    Yan Hong, Shihui Fang, Jingming Su, Wanqiu Xu, Yuhao Wei, Juan Wu, Zhen Yang
    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 139-160, 2023, DOI:10.32604/cmc.2023.043424
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract In today’s information society, image encryption technology is crucial to protecting Internet security. However, traditional image encryption algorithms have problems such as insufficient chaotic characteristics, insufficient randomness of keys, and insecure Ribonucleic Acid (RNA) encoding. To address these issues, a chaos-RNA encryption scheme that combines chaotic maps and RNA encoding was proposed in this research. The initial values and parameters of the chaotic system are first generated using the Secure Hash Algorithm 384 (SHA-384) function and the plaintext image. Next, the Lü hyperchaotic system sequence was introduced to change the image’s pixel values to realize block scrambling, and further disturbance… More >

    Graphic Abstract

    A Novel Approach for Image Encryption with Chaos-RNA

  • Open Access

    ARTICLE

    A New S-Box Design System for Data Encryption Using Artificial Bee Colony Algorithm

    Yazeed Yasin Ghadi, Mohammed S. Alshehri, Sultan Almakdi, Oumaima Saidani, Nazik Alturki, Fawad Masood, Muhammad Shahbaz Khan
    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 781-797, 2023, DOI:10.32604/cmc.2023.042777
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract Securing digital image data is a key concern in today’s information-driven society. Effective encryption techniques are required to protect sensitive image data, with the Substitution-box (S-box) often playing a pivotal role in many symmetric encryption systems. This study introduces an innovative approach to creating S-boxes for encryption algorithms. The proposed S-boxes are tested for validity and non-linearity by incorporating them into an image encryption scheme. The nonlinearity measure of the proposed S-boxes is 112. These qualities significantly enhance its resistance to common cryptographic attacks, ensuring high image data security. Furthermore, to assess the robustness of the S-boxes, an encryption system… More >

  • Open Access

    ARTICLE

    MEM-TET: Improved Triplet Network for Intrusion Detection System

    Weifei Wang, Jinguo Li, Na Zhao, Min Liu
    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 471-487, 2023, DOI:10.32604/cmc.2023.039733
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract With the advancement of network communication technology, network traffic shows explosive growth. Consequently, network attacks occur frequently. Network intrusion detection systems are still the primary means of detecting attacks. However, two challenges continue to stymie the development of a viable network intrusion detection system: imbalanced training data and new undiscovered attacks. Therefore, this study proposes a unique deep learning-based intrusion detection method. We use two independent in-memory autoencoders trained on regular network traffic and attacks to capture the dynamic relationship between traffic features in the presence of unbalanced training data. Then the original data is fed into the triplet network… More >

  • Open Access

    ARTICLE

    Anomalous Situations Recognition in Surveillance Images Using Deep Learning

    Qurat-ul-Ain Arshad, Mudassar Raza, Wazir Zada Khan, Ayesha Siddiqa, Abdul Muiz, Muhammad Attique Khan, Usman Tariq, Taerang Kim, Jae-Hyuk Cha
    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1103-1125, 2023, DOI:10.32604/cmc.2023.039752
    (This article belongs to this Special Issue: Multimedia Encryption and Information Security)
    Abstract Anomalous situations in surveillance videos or images that may result in security issues, such as disasters, accidents, crime, violence, or terrorism, can be identified through video anomaly detection. However, differentiating anomalous situations from normal can be challenging due to variations in human activity in complex environments such as train stations, busy sporting fields, airports, shopping areas, military bases, care centers, etc. Deep learning models’ learning capability is leveraged to identify abnormal situations with improved accuracy. This work proposes a deep learning architecture called Anomalous Situation Recognition Network (ASRNet) for deep feature extraction to improve the detection accuracy of various anomalous… More >

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