Qiong Yang¹, Li Ma^1,2,*, Shanshan Tu¹, Sami Ullah³, Muhammad Waqas^4,5, Hisham Alasmary⁶

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2035-2062, 2024, DOI:10.32604/cmc.2024.049970

Abstract Border Gateway Protocol (BGP) is a standard inter-domain routing protocol for the Internet that conveys network layer reachability information and establishes routes to different destinations. The BGP protocol exhibits security design defects, such as an unconditional trust mechanism and the default acceptance of BGP route announcements from peers by BGP neighboring nodes, easily triggering prefix hijacking, path forgery, route leakage, and other BGP security threats. Meanwhile, the traditional BGP security mechanism, relying on a public key infrastructure, faces issues like a single point of failure and a single point of trust. The decentralization, anti-tampering, and traceability advantages of blockchain offer… More >

Hang Sun, Changsheng Li^*, He Zhang

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2505-2522, 2024, DOI:10.32604/cmc.2024.049898

Abstract Brain–computer interface (BCI) systems, such as the P300 speller, enable patients to express intentions without necessitating extensive training. However, the complexity of operational instructions and the slow pace of character spelling pose challenges for some patients. In this paper, an image segmentation P300 selector based on YOLOv7-mask and DeepSORT is proposed. The proposed system utilizes a camera to capture real-world objects for classification and tracking. By applying predefined stimulation rules and object-specific masks, the proposed system triggers stimuli associated with the objects displayed on the screen, inducing the generation of P300 signals in the patient’s brain. Its video processing mechanism… More >

Meenakshi Aggarwal¹, Vikas Khullar¹, Sunita Rani², Thomas André Prola^3,4,5, Shyama Barna Bhattacharjee⁶, Sarowar Morshed Shawon⁷, Nitin Goyal^8,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1795-1834, 2024, DOI:10.32604/cmc.2024.049846

Abstract The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data generation. However, FL development for IoT is still in its infancy and needs to be explored in various areas to understand the key challenges for deployment in real-world scenarios. The paper systematically reviewed the available literature using the PRISMA guiding principle. The study aims to provide a detailed overview of the increasing use of FL in IoT networks, including the architecture and challenges. A systematic review approach is used to collect, categorize and analyze FL-IoT-based articles. A search was performed in… More >

Zakir Hussain Ahmed^1,*, Habibollah Haron², Abdullah Al-Tameem³

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2399-2425, 2024, DOI:10.32604/cmc.2024.049704

Abstract Genetic algorithms (GAs) are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems. A simple GA begins with a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes. It uses a crossover operator to create better offspring chromosomes and thus, converges the population. Also, it uses a mutation operator to explore the unexplored areas by the crossover operator, and thus, diversifies the GA search space. A combination of crossover and mutation operators makes the GA search strong… More >

Mahmood Ul Haq¹, Muhammad Athar Javed Sethi¹, Najib Ben Aoun^2,3, Ala Saleh Alluhaidan^4,*, Sadique Ahmad^5,6, Zahid farid⁷

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2169-2186, 2024, DOI:10.32604/cmc.2024.049645

Abstract Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security, authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neural networks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since they do not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networks as a more robust design capable of retaining pose information and spatial correlations to recognize objects more like the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, and so on, which are routed to higher-level capsules via… More >

Muhammad Ahmad Nawaz Ul Ghani¹, Kun She^1,*, Muhammad Arslan Rauf¹, Shumaila Khan², Javed Ali Khan³, Eman Abdullah Aldakheel⁴, Doaa Sami Khafaga⁴

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2609-2623, 2024, DOI:10.32604/cmc.2024.049611

Abstract The use of privacy-enhanced facial recognition has increased in response to growing concerns about data security and privacy in the digital age. This trend is spurred by rising demand for face recognition technology in a variety of industries, including access control, law enforcement, surveillance, and internet communication. However, the growing usage of face recognition technology has created serious concerns about data monitoring and user privacy preferences, especially in context-aware systems. In response to these problems, this study provides a novel framework that integrates sophisticated approaches such as Generative Adversarial Networks (GANs), Blockchain, and distributed computing to solve privacy concerns while… More >

Kamlesh Kumar Soothar^1,2, Yuanxiang Chen^1,2,*, Arif Hussain Magsi³, Cong Hu¹, Hussain Shah¹

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2697-2721, 2024, DOI:10.32604/cmc.2024.049607

Abstract Efficient optical network management poses significant importance in backhaul and access network communication for preventing service disruptions and ensuring Quality of Service (QoS) satisfaction. The emerging faults in optical networks introduce challenges that can jeopardize the network with a variety of faults. The existing literature witnessed various partial or inadequate solutions. On the other hand, Machine Learning (ML) has revolutionized as a promising technique for fault detection and prevention. Unlike traditional fault management systems, this research has three-fold contributions. First, this research leverages the ML and Deep Learning (DL) multi-classification system and evaluates their accuracy in detecting six distinct fault… More >

Zewen Zhang¹, Sheng Zhou¹, Chunzheng Cao^1,2,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2465-2480, 2024, DOI:10.32604/cmc.2024.049605

Abstract The classification of functional data has drawn much attention in recent years. The main challenge is representing infinite-dimensional functional data by finite-dimensional features while utilizing those features to achieve better classification accuracy. In this paper, we propose a mean-variance-based (MV) feature weighting method for classifying functional data or functional curves. In the feature extraction stage, each sample curve is approximated by B-splines to transfer features to the coefficients of the spline basis. After that, a feature weighting approach based on statistical principles is introduced by comprehensively considering the between-class differences and within-class variations of the coefficients. We also introduce a… More >

Arnab Dey^1,*, Samit Biswas¹, Dac-Nhuong Le²

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3067-3087, 2024, DOI:10.32604/cmc.2024.049512

Abstract Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers the likelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in video streams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enable instant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing action datasets often lack diversity and specificity for workout actions, hindering the development of accurate recognition models. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significant contribution. WAVd comprises a diverse… More >

Di Wang, Yuefei Zhu, Jinlong Fei^*, Maohua Guo

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2253-2276, 2024, DOI:10.32604/cmc.2024.049504

Abstract Website fingerprinting, also known as WF, is a traffic analysis attack that enables local eavesdroppers to infer a user’s browsing destination, even when using the Tor anonymity network. While advanced attacks based on deep neural network (DNN) can perform feature engineering and attain accuracy rates of over 98%, research has demonstrated that DNN is vulnerable to adversarial samples. As a result, many researchers have explored using adversarial samples as a defense mechanism against DNN-based WF attacks and have achieved considerable success. However, these methods suffer from high bandwidth overhead or require access to the target model, which is unrealistic. This… More >