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  • Open Access

    ARTICLE

    Sensitive Target-Guided Directed Fuzzing for IoT Web Services

    Xiongwei Cui, Yunchao Wang, Qiang Wei*

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4939-4959, 2025, DOI:10.32604/cmc.2025.063592 - 19 May 2025

    Abstract The development of the Internet of Things (IoT) has brought convenience to people’s lives, but it also introduces significant security risks. Due to the limitations of IoT devices themselves and the challenges of re-hosting technology, existing fuzzing for IoT devices is mainly conducted through black-box methods, which lack effective execution feedback and are blind. Meanwhile, the existing static methods mainly rely on taint analysis, which has high overhead and high false alarm rates. We propose a new directed fuzz testing method for detecting bugs in web service programs of IoT devices, which can test IoT… More >

  • Open Access

    ARTICLE

    Self-Tuning Parameters for Decision Tree Algorithm Based on Big Data Analytics

    Manar Mohamed Hafez1,*, Essam Eldin F. Elfakharany1, Amr A. Abohany2, Mostafa Thabet3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 943-958, 2023, DOI:10.32604/cmc.2023.034078 - 06 February 2023

    Abstract Big data is usually unstructured, and many applications require the analysis in real-time. Decision tree (DT) algorithm is widely used to analyze big data. Selecting the optimal depth of DT is time-consuming process as it requires many iterations. In this paper, we have designed a modified version of a (DT). The tree aims to achieve optimal depth by self-tuning running parameters and improving the accuracy. The efficiency of the modified (DT) was verified using two datasets (airport and fire datasets). The airport dataset has 500000 instances and the fire dataset has 600000 instances. A comparison More >

  • Open Access

    REVIEW

    Ensemble Learning Models for Classification and Selection of Web Services: A Review

    Muhammad Hasnain1, Imran Ghani2, Seung Ryul Jeong3,*, Aitizaz Ali1

    Computer Systems Science and Engineering, Vol.40, No.1, pp. 327-339, 2022, DOI:10.32604/csse.2022.018300 - 26 August 2021

    Abstract This paper presents a review of the ensemble learning models proposed for web services classification, selection, and composition. Web service is an evolutionary research area, and ensemble learning has become a hot spot to assess web services’ earlier mentioned aspects. The proposed research aims to review the state of art approaches performed on the interesting web services area. The literature on the research topic is examined using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) as a research method. The study reveals an increasing trend of using ensemble learning in the chosen papers More >

  • Open Access

    ARTICLE

    Development of a Smart Technique for Mobile Web Services Discovery

    Mohamed Eb-Saad1, Yunyoung Nam2,*, Hazem M. El-bakry1, Samir Abdelrazek1

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1483-1501, 2021, DOI:10.32604/cmc.2021.017783 - 21 July 2021

    Abstract Web service (WS) presents a good solution to the interoperability of different types of systems that aims to reduce the overhead of high processing in a resource-limited environment. With the increasing demand for mobile WS (MWS), the WS discovery process has become a significant challenging point in the WS lifecycle that aims to identify the relevant MWSs that best match the service requests. This discovery process is a resource-consuming task that cannot be performed efficiently in a mobile computing environment due to the limitations of mobile devices. Meanwhile, a cloud computing can provide rich computing… More >

  • Open Access

    ARTICLE

    Smart Object Detection and Home Appliances Control System in Smart Cities

    Sulaiman Khan1, Shah Nazir1, Habib Ullah Khan2,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 895-915, 2021, DOI:10.32604/cmc.2021.013878 - 12 January 2021

    Abstract During the last decade the emergence of Internet of Things (IoT) based applications inspired the world by providing state of the art solutions to many common problems. From traffic management systems to urban cities planning and development, IoT based home monitoring systems, and many other smart applications. Regardless of these facilities, most of these IoT based solutions are data driven and results in small accuracy values for smaller datasets. In order to address this problem, this paper presents deep learning based hybrid approach for the development of an IoT-based intelligent home security and appliance control… More >

  • Open Access

    ARTICLE

    Functionality Aware Dynamic Composition of Web Services

    Mohemmed Sha*, Abdalla Alameen

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 201-211, 2021, DOI:10.32604/csse.2021.014513 - 23 December 2020

    Abstract The composition of the web service is a common technique to attain the best results of complex web tasks. The selection of appropriate web services, linking those services in the action flow and attaining the actual functionality of the task are the important factors to be considered. Even though different frameworks and methods have been proposed to dynamically compose web services, each method has its advantage and disadvantage over the other. Most of the methods give much importance to the Quality of Service (QoS) but fail to achieve the actual functionality after composition. This paper… More >

  • Open Access

    ARTICLE

    Performance Anomaly Detection in Web Services: An RNN- Based Approach Using Dynamic Quality of Service Features

    Muhammad Hasnain1, Seung Ryul Jeong2, *, Muhammad Fermi Pasha3, Imran Ghani4

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 729-752, 2020, DOI:10.32604/cmc.2020.010394 - 10 June 2020

    Abstract Performance anomaly detection is the process of identifying occurrences that do not conform to expected behavior or correlate with other incidents or events in time series data. Anomaly detection has been applied to areas such as fraud detection, intrusion detection systems, and network systems. In this paper, we propose an anomaly detection framework that uses dynamic features of quality of service that are collected in a simulated setup. Three variants of recurrent neural networks-SimpleRNN, long short term memory, and gated recurrent unit are evaluated. The results reveal that the proposed method effectively detects anomalies in More >

  • Open Access

    ARTICLE

    Prediction of Web Services Reliability Based on Decision Tree Classification Method

    Zhichun Jia1, 2, Qiuyang Han1, Yanyan Li1, Yuqiang Yang1, Xing Xing1, 2, *

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1221-1235, 2020, DOI:10.32604/cmc.2020.09722 - 30 April 2020

    Abstract With the development of the service-oriented computing (SOC), web service has an important and popular solution for the design of the application system to various enterprises. Nowadays, the numerous web services are provided by the service providers on the network, it becomes difficult for users to select the best reliable one from a large number of services with the same function. So it is necessary to design feasible selection strategies to provide users with the reliable services. Most existing methods attempt to select services according to accurate predictions for the quality of service (QoS) values.… More >

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