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  • Open Access

    ARTICLE

    Anomaly Detection in Imbalanced Encrypted Traffic with Few Packet Metadata-Based Feature Extraction

    Min-Gyu Kim1, Hwankuk Kim2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 585-607, 2024, DOI:10.32604/cmes.2024.051221 - 20 August 2024

    Abstract In the IoT (Internet of Things) domain, the increased use of encryption protocols such as SSL/TLS, VPN (Virtual Private Network), and Tor has led to a rise in attacks leveraging encrypted traffic. While research on anomaly detection using AI (Artificial Intelligence) is actively progressing, the encrypted nature of the data poses challenges for labeling, resulting in data imbalance and biased feature extraction toward specific nodes. This study proposes a reconstruction error-based anomaly detection method using an autoencoder (AE) that utilizes packet metadata excluding specific node information. The proposed method omits biased packet metadata such as… More >

  • Open Access

    ARTICLE

    PARE: Privacy-Preserving Data Reliability Evaluation for Spatial Crowdsourcing in Internet of Things

    Peicong He, Yang Xin*, Yixian Yang

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3067-3084, 2024, DOI:10.32604/cmc.2024.054777 - 15 August 2024

    Abstract The proliferation of intelligent, connected Internet of Things (IoT) devices facilitates data collection. However, task workers may be reluctant to participate in data collection due to privacy concerns, and task requesters may be concerned about the validity of the collected data. Hence, it is vital to evaluate the quality of the data collected by the task workers while protecting privacy in spatial crowdsourcing (SC) data collection tasks with IoT. To this end, this paper proposes a privacy-preserving data reliability evaluation for SC in IoT, named PARE. First, we design a data uploading format using blockchain More >

  • Open Access

    ARTICLE

    Detection of Real-Time Distributed Denial-of-Service (DDoS) Attacks on Internet of Things (IoT) Networks Using Machine Learning Algorithms

    Zaed Mahdi1,*, Nada Abdalhussien2, Naba Mahmood1, Rana Zaki3,*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2139-2159, 2024, DOI:10.32604/cmc.2024.053542 - 15 August 2024

    Abstract The primary concern of modern technology is cyber attacks targeting the Internet of Things. As it is one of the most widely used networks today and vulnerable to attacks. Real-time threats pose with modern cyber attacks that pose a great danger to the Internet of Things (IoT) networks, as devices can be monitored or service isolated from them and affect users in one way or another. Securing Internet of Things networks is an important matter, as it requires the use of modern technologies and methods, and real and up-to-date data to design and train systems… More >

  • Open Access

    ARTICLE

    Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

    Uddagiri Sirisha1,, Parvathaneni Naga Srinivasu2,3,*, Panguluri Padmavathi4, Seongki Kim5,, Aruna Pavate6, Jana Shafi7, Muhammad Fazal Ijaz8,*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2301-2330, 2024, DOI:10.32604/cmc.2024.053132 - 15 August 2024

    Abstract Fetal health care is vital in ensuring the health of pregnant women and the fetus. Regular check-ups need to be taken by the mother to determine the status of the fetus’ growth and identify any potential problems. To know the status of the fetus, doctors monitor blood reports, Ultrasounds, cardiotocography (CTG) data, etc. Still, in this research, we have considered CTG data, which provides information on heart rate and uterine contractions during pregnancy. Several researchers have proposed various methods for classifying the status of fetus growth. Manual processing of CTG data is time-consuming and unreliable.… More >

  • Open Access

    REVIEW

    Security and Privacy Challenges in SDN-Enabled IoT Systems: Causes, Proposed Solutions, and Future Directions

    Ahmad Rahdari1,6, Ahmad Jalili2, Mehdi Esnaashari3, Mehdi Gheisari1,4,7,8,*, Alisa A. Vorobeva5, Zhaoxi Fang1, Panjun Sun1,*, Viktoriia M. Korzhuk5, Ilya Popov5, Zongda Wu1, Hamid Tahaei1

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2511-2533, 2024, DOI:10.32604/cmc.2024.052994 - 15 August 2024

    Abstract Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding devices to enhance flexibility and centralize deployment. Concurrently, the Internet of Things (IoT) connects numerous devices to the Internet, enabling autonomous interactions with minimal human intervention. However, implementing and managing an SDN-IoT system is inherently complex, particularly for those with limited resources, as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN integration. The findings of this study underscore the primary security and privacy challenges across application, control, and data planes.… More >

  • Open Access

    ARTICLE

    A Traffic-Aware and Cluster-Based Energy Efficient Routing Protocol for IoT-Assisted WSNs

    Hina Gul1, Sana Ullah1, Ki-Il Kim2,*, Farman Ali3

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1831-1850, 2024, DOI:10.32604/cmc.2024.052841 - 15 August 2024

    Abstract The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications, such as remote health monitoring, industrial monitoring, transportation, and smart agriculture. Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes. This paper presents a traffic-aware, cluster-based, and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks. The proposed protocol divides the network into clusters where optimal cluster heads are selected among super… More >

  • Open Access

    ARTICLE

    Two-Stage IoT Computational Task Offloading Decision-Making in MEC with Request Holding and Dynamic Eviction

    Dayong Wang1,*, Kamalrulnizam Bin Abu Bakar1, Babangida Isyaku2

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2065-2080, 2024, DOI:10.32604/cmc.2024.051944 - 15 August 2024

    Abstract The rapid development of Internet of Things (IoT) technology has led to a significant increase in the computational task load of Terminal Devices (TDs). TDs reduce response latency and energy consumption with the support of task-offloading in Multi-access Edge Computing (MEC). However, existing task-offloading optimization methods typically assume that MEC’s computing resources are unlimited, and there is a lack of research on the optimization of task-offloading when MEC resources are exhausted. In addition, existing solutions only decide whether to accept the offloaded task request based on the single decision result of the current time slot,… More >

  • Open Access

    REVIEW

    AI-Driven Learning Management Systems: Modern Developments, Challenges and Future Trends during the Age of ChatGPT

    Sameer Qazi1,*, Muhammad Bilal Kadri2, Muhammad Naveed1,*, Bilal A. Khawaja3, Sohaib Zia Khan4, Muhammad Mansoor Alam5,6,7, Mazliham Mohd Su’ud6

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3289-3314, 2024, DOI:10.32604/cmc.2024.048893 - 15 August 2024

    Abstract COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus. The foremost and most prime sector among those affected were schools, colleges, and universities. The education system of entire nations had shifted to online education during this time. Many shortcomings of Learning Management Systems (LMSs) were detected to support education in an online mode that spawned the research in Artificial Intelligence (AI) based tools that are being developed by the research community to improve the effectiveness of LMSs. This paper presents a detailed survey of the different enhancements to LMSs, which… More >

  • Open Access

    REVIEW

    Modulatory role of plant-derived metabolites on host-microbiota interactions: personalized therapeutics outlook

    POOJA YADAV, NAR SINGH CHAUHAN*

    BIOCELL, Vol.48, No.8, pp. 1127-1143, 2024, DOI:10.32604/biocell.2024.051318 - 02 August 2024

    Abstract A diverse array of microbes in and on the human body constitute the microbiota. These micro-residents continuously interact with the human host through the language of metabolites to dictate the host’s physiology in health and illnesses. Any biotic and abiotic component ensuring a balanced host-microbiota interaction are potential microbiome therapeutic agents to overcome human diseases. Plant metabolites are continually being used to treat various illnesses. These metabolites target the host’s metabolic machinery and host-gut microbiota interactions to overcome human diseases. Despite the paramount therapeutic significance of the factors affecting host-microbiota interactions, a comprehensive overview of More > Graphic Abstract

    Modulatory role of plant-derived metabolites on host-microbiota interactions: personalized therapeutics outlook

  • Open Access

    ARTICLE

    Combined Application of Biostimulants and EDTA Improved Wheat Productivity under Cadmium Stress

    Abida Aziz1, Shafiqa Bano1, Mubshar Hussain2, Muhammad Farooq Azhar3, Ghulam Yasin3, Naila Hadayat4, Iqra Arooj5, Abeer Hashem6, Ajay Kumar7, Elsayed Fathi Abd_Allah8, Qamar uz Zaman9,10,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1647-1665, 2024, DOI:10.32604/phyton.2024.050974 - 30 July 2024

    Abstract Wheat (Triticum aestivum L.) exhibits a greater capacity for cadmium (Cd) absorption compared to other cereal crops, leading to elevated daily Cd intake, and posing a significant threat to public health. For the mitigation of Cd stress in sustainable and environmentally friendly way, a pot study was designed by using exogenous application of various biostimulants, i.e., Nigella sativa and Ocimum sanctum extracts: 0%, 10%, and 20% in combination with the chelating agent ethylenediaminetetraacetic acid (EDTA) using 0 and 5 mg kg under various levels of Cd stress (i.e., 0, 5, 10, and 15 mg kg soil). Results revealed… More > Graphic Abstract

    Combined Application of Biostimulants and EDTA Improved Wheat Productivity under Cadmium Stress

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