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  • Open Access

    ARTICLE

    GDPR Compliance IoT Authentication Model for Smart Home Environment

    Hisham Raad Jafer Merzeh1,*, Mustafa Kara2, Muhammed Ali Aydın3, Hasan Hüseyin Balık1

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1953-1970, 2022, DOI:10.32604/iasc.2022.021297

    Abstract The Internet of things (IoT) became quickly one of the most popular and most discussed topics in research. Studies paid attention to the Internet stuff, primarily to new products that aim to achieve greater efficiency and simplicity in life. IoT may cover several fields of the smart environment. Because of the data exposure that occurs when data is transferred via various channels, data protection issues have become a major problem as the company continues to expand. When user privacy and property are taken into consideration, the situation may become much worse. As a result, the authentication process for communicating entities… More >

  • Open Access

    ARTICLE

    A Learning-Based Fault Localization Approach Using Subset of Likely and Dynamic Invariants

    Asadullah Shaikh1,*, Syed Rizwan2, Abdullah Alghamdi1, Noman Islam2, M.A. Elmagzoub1, Darakhshan Syed2

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1529-1546, 2022, DOI:10.32604/iasc.2022.021163

    Abstract Fault localization is one of the main tasks of software debugging. Developers spend a lot of time, cost, and effort to locate the faults correctly manually. For reducing this effort, many automatic fault localization techniques have been proposed, which inputs test suites and outputs a sorted list of faulty entities of the program. For further enhancement in this area, we developed a system called SILearning, which is based on invariant analysis. It learns from some existing fixed bugs to locate faulty methods in the program. It combines machine-learned ranking, program invariant differences, and spectrum-based fault localization (SBFL). Using the execution… More >

  • Open Access

    ARTICLE

    Detection and Avoidance of Clone Attack in IoT Based Smart Health Application

    S. Vaishnavi1,*, T. Sethukarasi2

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1919-1937, 2022, DOI:10.32604/iasc.2022.021006

    Abstract The deployment of wireless sensors in the hostile environment makes them susceptible to malicious attacks. One of the most harmful attacks is the clone attack in which a malicious node illegitimately claims the identity of a genuine node in the network and eventually tries to capture the entire network. This attack is also termed as node replication attack. The mobile nature of wireless sensor network (WSN) in smart health environment increases the vulnerability of node replication attack. Since the data involved in smart health system are highly sensitive data, preserving the system from the attack by malicious nodes is a… More >

  • Open Access

    ARTICLE

    Optimal Path Planning for Intelligent UAVs Using Graph Convolution Networks

    Akshya Jothi, P. L. K. Priyadarsini*

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1577-1591, 2022, DOI:10.32604/iasc.2022.020974

    Abstract Unmanned Aerial Vehicles (UAVs) are in use for surveillance services in the geographic areas, that are very hard and sometimes not reachable by humans. Nowadays, UAVs are being used as substitutions to manned operations in various applications. The intensive utilization of autonomous UAVs has given rise to many new challenges. One of the vital problems that arise while deploying UAVs in surveillance applications is the Coverage Path Planning(CPP) problem. Given a geographic area, the problem is to find an optimal path/tour for the UAV such that it covers the entire area of interest with minimal tour length. A graph can… More >

  • Open Access

    ARTICLE

    An Enhanced Routing and Lifetime Performance for Industrial Wireless Sensor Networks

    J. V. Anchitaalagammai1,*, K. Muthumayil2, D. Kamalraj Subramaniam3, Rajesh Verma4, P. Muralikrishnan5, G. Visalaxi6

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1783-1792, 2022, DOI:10.32604/iasc.2022.020967

    Abstract Industrial Wireless Sensor Networks (IWSNs), especially energy resources, are scarce. Since sensor nodes are usually very dense, and the data sampled by the sensor nodes have high redundancy, data aggregation saves energy, reduces the number of transmissions, and eliminates redundancy. Many applications can be used in IIWSNs, and a new technique is introduced to detect multiple sensors embedded in different sensor nodes. Packets created by different applications have different properties. Sensors are resource-constrained devices because it is necessary to find effective reaction analysis methods and transfer sensed data to base stations. Since sensors are resource-constrained devices, efficient topologies require data… More >

  • Open Access

    ARTICLE

    Classification Similarity Network Model for Image Fusion Using Resnet50 and GoogLeNet

    P. Siva Satya Sreedhar1,*, N. Nandhagopal2

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1331-1344, 2022, DOI:10.32604/iasc.2022.020918

    Abstract The current trend in Image Fusion (IF) algorithms concentrate on the fusion process alone. However, pay less attention to critical issues such as the similarity between the two input images, features that participate in the Image Fusion. This paper addresses these two issues by deliberately attempting a new Image Fusion framework with Convolutional Neural Network (CNN). CNN has features like pre-training and similarity score, but functionalities are limited. A CNN model with classification prediction and similarity estimation are introduced as Classification Similarity Networks (CSN) to address these issues. ResNet50 and GoogLeNet are modified as the classification branches of CSN v1,… More >

  • Open Access

    ARTICLE

    Analysis of Software Success Through Structural Equation Modeling

    Muhammad Hamid1,*, Furkh Zeshan2, Adnan Ahmad2, Saadia Malik3, Muhammad Saleem4, Nadia Tabassum5, Muhammad Qasim1

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1689-1701, 2022, DOI:10.32604/iasc.2022.020898

    Abstract Determining factors influencing the success of software projects has been the emphasis of extensive research for more than 40 years. However, the majority of research in this domain has focused on developed countries, with little attention paid to underdeveloped and developing countries. The primary objective of this article was to assess the effect of critical elements on the success of software projects in underdeveloped countries (like Pakistan), because enterprise environmental factors and staff working habits, as well as their experience and expertise level, all have an effect on a project's success. For this purpose, data were collected from 339 senior… More >

  • Open Access

    ARTICLE

    Industrial Datasets with ICS Testbed and Attack Detection Using Machine Learning Techniques

    Sinil Mubarak1, Mohamed Hadi Habaebi1,*, Md Rafiqul Islam1, Asaad Balla1, Mohammad Tahir2, Elfatih A. A. Elsheikh3, F. M. Suliman3

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1345-1360, 2022, DOI:10.32604/iasc.2022.020801

    Abstract Industrial control systems (ICS) are the backbone for the implementation of cybersecurity solutions. They are susceptible to various attacks, due to openness in connectivity, unauthorized attempts, malicious attacks, use of more commercial off the shelf (COTS) software and hardware, and implementation of Internet protocols (IP) that exposes them to the outside world. Cybersecurity solutions for Information technology (IT) secured with firewalls, intrusion detection/protection systems do nothing much for Operational technology (OT) ICS. An innovative concept of using real operational technology network traffic-based testbed, for cyber-physical system simulation and analysis, is presented. The testbed is equipped with real-time attacks using in-house… More >

  • Open Access

    ARTICLE

    IoT and Machine Learning Based Stem Borer Pest Prediction

    Rana Muhammad Nadeem1, Arfan Jaffar2, Rana Muhammad Saleem3,*

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1377-1392, 2022, DOI:10.32604/iasc.2022.020680

    Abstract Global climatic changes have severe impacts on agricultural productivity. Enhanced pest attacks on crops are one of the major impacts on sustainable developments in agriculture to come up with the needs of the ever-increasing human population. Early warning of a pest attack is important for Integrated Pest Management (IPM) activities to be effective. Early warning of pest attacks is also important for judicious use of pesticides for efficient use of resources for minimal impacts on the environment. Sugarcane is the major cash crop and is also severely affected by different types of pests. This study proposed stem borer attack prediction… More >

  • Open Access

    ARTICLE

    IIoT Framework Based ML Model to Improve Automobile Industry Product

    S. Gopalakrishnan1,*, M. Senthil Kumaran2

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1435-1449, 2022, DOI:10.32604/iasc.2022.020660

    Abstract In the automotive industry, multiple predictive maintenance units run behind the scenes in every production process to support significant product development, particularly among Accessories Manufacturers (AMs). As a result, they wish to maintain a positive relationship with vehicle manufacturers by providing 100 percent quality assurances for accessories. This is only achievable if they implement an effective anticipatory strategy that prioritizes quality control before and after product development. To do this, many sensors devices are interconnected in the production area to collect operational data (humanity, viscosity, and force) continuously received from machines and sent to backend computers for control operations and… More >

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