Muhammad Sibtain¹, Mehdi Hussain^1,*, Qaiser Riaz¹, Sana Qadir¹, Naveed Riaz¹, Ki-Hyun Jung^2,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5177-5199, 2025, DOI:10.32604/cmc.2025.066198 - 30 July 2025

Abstract Ransomware is malware that encrypts data without permission, demanding payment for access. Detecting ransomware on Android platforms is challenging due to evolving malicious techniques and diverse application behaviors. Traditional methods, such as static and dynamic analysis, suffer from polymorphism, code obfuscation, and high resource demands. This paper introduces a multi-stage approach to enhance behavioral analysis for Android ransomware detection, focusing on a reduced set of distinguishing features. The approach includes ransomware app collection, behavioral profile generation, dataset creation, feature identification, reduction, and classification. Experiments were conducted on ∼3300 Android-based ransomware samples, despite the challenges posed… More >

Ishaani Priyadarshini^*

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 635-659, 2025, DOI:10.32604/cmc.2025.061062 - 26 March 2025

Abstract Predictive maintenance plays a crucial role in preventing equipment failures and minimizing operational downtime in modern industries. However, traditional predictive maintenance methods often face challenges in adapting to diverse industrial environments and ensuring the transparency and fairness of their predictions. This paper presents a novel predictive maintenance framework that integrates deep learning and optimization techniques while addressing key ethical considerations, such as transparency, fairness, and explainability, in artificial intelligence driven decision-making. The framework employs an Autoencoder for feature reduction, a Convolutional Neural Network for pattern recognition, and a Long Short-Term Memory network for temporal analysis.… More >

Mesut Ulu^1,*, Yusuf Sait Türkan², Kenan Mengüç³, Ersin Namlı², Tarık Küçükdeniz²

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2259-2281, 2024, DOI:10.32604/cmc.2024.052323 - 15 August 2024

Abstract Today, urban traffic, growing populations, and dense transportation networks are contributing to an increase in traffic incidents. These incidents include traffic accidents, vehicle breakdowns, fires, and traffic disputes, resulting in long waiting times, high carbon emissions, and other undesirable situations. It is vital to estimate incident response times quickly and accurately after traffic incidents occur for the success of incident-related planning and response activities. This study presents a model for forecasting the traffic incident duration of traffic events with high precision. The proposed model goes through a 4-stage process using various features to predict the… More >

Fayez Alfayez^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1539-1560, 2024, DOI:10.32604/cmc.2024.046443 - 25 April 2024

Abstract This paper emphasizes a faster digital processing time while presenting an accurate method for identifying spine fractures in X-ray pictures. The study focuses on efficiency by utilizing many methods that include picture segmentation, feature reduction, and image classification. Two important elements are investigated to reduce the classification time: Using feature reduction software and leveraging the capabilities of sophisticated digital processing hardware. The researchers use different algorithms for picture enhancement, including the Wiener and Kalman filters, and they look into two background correction techniques. The article presents a technique for extracting textural features and evaluates three… More >

R. Gopi^1,*, S. Veena², S. Balasubramanian³, D. Ramya⁴, P. Ilanchezhian⁵, A. Harshavardhan⁶, Zatin Gupta⁷

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1215-1230, 2022, DOI:10.32604/iasc.2022.025792 - 03 May 2022

Abstract In this modern era, the transformation of conventional objects into smart ones via internet vitality, data management, together with many more are the main aim of the Internet of Things (IoT) centered Big Data (BD) analysis. In the past few years, significant augmentation in the IoT-centered Healthcare (HC) monitoring can be seen. Nevertheless, the merging of health-specific parameters along with IoT-centric Health Monitoring (HM) systems with BD handling ability is turned out to be a complicated research scope. With the aid of Map-Reduce and LSQN³ techniques, this paper proposed IoT devices in Wireless Sensors Networks (WSN)… More >

Wahidur Rahman¹, Naif Al Mudawi^2,*, Abdulwahab Alazeb², Muhammad Minoar Hossain¹, Saima Siddique Tashfia¹, Md. Tarequl Islam¹, Shisir Mia¹, Mohammad Motiur Rahman¹

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2033-2053, 2022, DOI:10.32604/cmc.2022.025025 - 24 February 2022

Abstract On the edge of the worldwide public health crisis, the COVID-19 disease has become a serious headache for its destructive nature on humanity worldwide. Wearing a facial mask can be an effective possible solution to mitigate the spreading of the virus and reduce the death rate. Thus, wearing a face mask in public places such as shopping malls, hotels, restaurants, homes, and offices needs to be enforced. This research work comes up with a solution of mask surveillance system utilizing the mechanism of modern computations like Deep Learning (DL), Internet of things (IoT), and Blockchain.… More >

Kriti¹, Mohd Anul Haq², Urvashi Garg¹, Mohd Abdul Rahim Khan^2,*, V. Rajinikanth³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 939-957, 2022, DOI:10.32604/cmc.2022.023169 - 24 February 2022

Abstract A crucial task in hyperspectral image (HSI) taxonomy is exploring effective methodologies to effusively practice the 3-D and spectral data delivered by the statistics cube. For classification of images, 3-D data is adjudged in the phases of pre-cataloging, an assortment of a sample, classifiers, post-cataloging, and accurateness estimation. Lastly, a viewpoint on imminent examination directions for proceeding 3-D and spectral approaches is untaken. In topical years, sparse representation is acknowledged as a dominant classification tool to effectually labels deviating difficulties and extensively exploited in several imagery dispensation errands. Encouraged by those efficacious solicitations, sparse representation… More >