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  • Open Access

    ARTICLE

    Application of Physical Unclonable Function for Lightweight Authentication in Internet of Things

    Ahmad O. Aseeri1, Sajjad Hussain Chauhdary2,*, Mohammed Saeed Alkatheiri3, Mohammed A. Alqarni4, Yu Zhuang5

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1901-1918, 2023, DOI:10.32604/cmc.2023.028777 - 06 February 2023

    Abstract IoT devices rely on authentication mechanisms to render secure message exchange. During data transmission, scalability, data integrity, and processing time have been considered challenging aspects for a system constituted by IoT devices. The application of physical unclonable functions (PUFs) ensures secure data transmission among the internet of things (IoT) devices in a simplified network with an efficient time-stamped agreement. This paper proposes a secure, lightweight, cost-efficient reinforcement machine learning framework (SLCR-MLF) to achieve decentralization and security, thus enabling scalability, data integrity, and optimized processing time in IoT devices. PUF has been integrated into SLCR-MLF to… More >

  • Open Access

    ARTICLE

    Thermal Properties Reconstruction and Temperature Fields in Asphalt Pavements: Inverse Problem and Optimisation Algorithms

    Zhonghai Jiang1, Qian Wang1, Liangbing Zhou2,*, Chun Xiao3

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1693-1708, 2023, DOI:10.32604/fdmp.2023.025270 - 30 January 2023

    Abstract A two-layer implicit difference scheme is employed in the present study to determine the temperature distribution in an asphalt pavement. The calculation of each layer only needs four iterations to achieve convergence. Furthermore, in order to improve the calculation accuracy a swarm intelligence optimization algorithm is also exploited to inversely analyze the laws by which the thermal physical parameters of the asphalt pavement materials change with temperature. Using the basic cuckoo and the gray wolf algorithms, an adaptive hybrid optimization algorithm is obtained and used to determine the relationship between the thermal diffusivity of two More >

  • Open Access

    ARTICLE

    Deep Learning for Depression Detection Using Twitter Data

    Doaa Sami Khafaga1, Maheshwari Auvdaiappan2, K. Deepa3, Mohamed Abouhawwash4,5, Faten Khalid Karim1,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1301-1313, 2023, DOI:10.32604/iasc.2023.033360 - 05 January 2023

    Abstract Today social media became a communication line among people to share their happiness, sadness, and anger with their end-users. It is necessary to know people’s emotions are very important to identify depressed people from their messages. Early depression detection helps to save people’s lives and other dangerous mental diseases. There are many intelligent algorithms for predicting depression with high accuracy, but they lack the definition of such cases. Several machine learning methods help to identify depressed people. But the accuracy of existing methods was not satisfactory. To overcome this issue, the deep learning method is… More >

  • Open Access

    ARTICLE

    Energy Proficient Reduced Coverage Set with Particle Swarm Optimization for Distributed Sensor Network

    T. V. Chithra1,*, A. Milton2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1611-1623, 2023, DOI:10.32604/csse.2023.026561 - 03 November 2022

    Abstract Retransmission avoidance is an essential need for any type of wireless communication. As retransmissions induce the unnecessary presence of redundant data in every accessible node. As storage capacity is symmetrical to the size of the memory, less storage capacity is experienced due to the restricted size of the respective node. In this proposed work, we have discussed the integration of the Energy Proficient Reduced Coverage Set with Particle Swarm Optimization (PSO). PSO is a metaheuristic global search enhancement technique that promotes the searching of the best nodes in the search space. PSO is integrated with More >

  • Open Access

    ARTICLE

    Sigmoidal Particle Swarm Optimization for Twitter Sentiment Analysis

    Sandeep Kumar1, Muhammad Badruddin Khan2, Mozaherul Hoque Abul Hasanat2, Abdul Khader Jilani Saudagar2,*, Abdullah AlTameem2, Mohammed AlKhathami2

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 897-914, 2023, DOI:10.32604/cmc.2023.031867 - 22 September 2022

    Abstract Social media, like Twitter, is a data repository, and people exchange views on global issues like the COVID-19 pandemic. Social media has been shown to influence the low acceptance of vaccines. This work aims to identify public sentiments concerning the COVID-19 vaccines and better understand the individual’s sensitivities and feelings that lead to achievement. This work proposes a method to analyze the opinion of an individual’s tweet about the COVID-19 vaccines. This paper introduces a sigmoidal particle swarm optimization (SPSO) algorithm. First, the performance of SPSO is measured on a set of 12 benchmark problems,… More >

  • Open Access

    ARTICLE

    Swarm Intelligence Based Routing with Black Hole Attack Detection in MANET

    S. A. Arunmozhi*, S. Rajeswari, Y. Venkataramani

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2337-2347, 2023, DOI:10.32604/csse.2023.024340 - 01 August 2022

    Abstract Mobile Ad hoc Network (MANET) possesses unique characteristics which makes it vulnerable to security threats. In MANET, it is highly challenging to protect the nodes from cyberattacks. Power conservation improves both life time of nodes as well as the network. Computational capabilities and memory constraints are critical issues in the implementation of cryptographic techniques. Energy and security are two important factors that need to be considered for improving the performance of MANET. So, the incorporation of an energy efficient secure routing protocol becomes inevitable to ensure appropriate action upon the network. The nodes present in More >

  • Open Access

    ARTICLE

    Discovering the Common Traits of Cybercrimes in Pakistan Using Associative Classification with Ant Colony Optimization

    Abdul Rauf1, Muhammad Asif Khan1,*, Hamid Hussain Awan2, Waseem Shahzad3, Najeeb Ul Husaan4

    Journal of Cyber Security, Vol.4, No.4, pp. 201-222, 2022, DOI:10.32604/jcs.2022.038791 - 10 August 2023

    Abstract In the modern world, law enforcement authorities are facing challenges due to the advanced technology used by criminals to commit crimes. Criminals follow specific patterns to carry out their crimes, which can be identified using machine learning and swarm intelligence approaches. This article proposes the use of the Ant Colony Optimization algorithm to create an associative classification of crime data, which can reveal potential relationships between different features and crime types. The experiments conducted in this research show that this approach can discover various associations among the features of crime data and the specific patterns More >

  • Open Access

    ARTICLE

    P-ACOHONEYBEE: A Novel Load Balancer for Cloud Computing Using Mathematical Approach

    Sunday Adeola Ajagbe1, Mayowa O. Oyediran2, Anand Nayyar3,*, Jinmisayo A. Awokola4, Jehad F. Al-Amri5

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1943-1959, 2022, DOI:10.32604/cmc.2022.028331 - 18 May 2022

    Abstract Cloud computing is a collection of disparate resources or services, a web of massive infrastructures, which is aimed at achieving maximum utilization with higher availability at a minimized cost. One of the most attractive applications for cloud computing is the concept of distributed information processing. Security, privacy, energy saving, reliability and load balancing are the major challenges facing cloud computing and most information technology innovations. Load balancing is the process of redistributing workload among all nodes in a network; to improve resource utilization and job response time, while avoiding overloading some nodes when other nodes… More >

  • Open Access

    ARTICLE

    Whale Optimization Algorithm Strategies for Higher Interaction Strength T-Way Testing

    Ali Abdullah Hassan1,*, Salwani Abdullah1, Kamal Z. Zamli2, Rozilawati Razali1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2057-2077, 2022, DOI:10.32604/cmc.2022.026310 - 18 May 2022

    Abstract Much of our daily tasks have been computerized by machines and sensors communicating with each other in real-time. There is a reasonable risk that something could go wrong because there are a lot of sensors producing a lot of data. Combinatorial testing (CT) can be used in this case to reduce risks and ensure conformance to specifications. Numerous existing meta-heuristic-based solutions aim to assist the test suite generation for combinatorial testing, also known as t-way testing (where t indicates the interaction strength), viewed as an optimization problem. Much previous research, while helpful, only investigated a small… More >

  • Open Access

    ARTICLE

    An Efficient Path Planning Strategy in Mobile Sink Wireless Sensor Networks

    Najla Bagais*, Etimad Fadel, Amal Al-Mansour

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1237-1267, 2022, DOI:10.32604/cmc.2022.026070 - 18 May 2022

    Abstract Wireless sensor networks (WSNs) are considered the backbone of the Internet of Things (IoT), which enables sensor nodes (SNs) to achieve applications similarly to human intelligence. However, integrating a WSN with the IoT is challenging and causes issues that require careful exploration. Prolonging the lifetime of a network through appropriately utilising energy consumption is among the essential challenges due to the limited resources of SNs. Thus, recent research has examined mobile sinks (MSs), which have been introduced to improve the overall efficiency of WSNs. MSs bear the burden of data collection instead of consuming energy… More >

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