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  • Open Access


    SFSDA: Secure and Flexible Subset Data Aggregation with Fault Tolerance for Smart Grid

    Dong Chen1, Tanping Zhou1,2,3,*, Xu An Wang1,2, Zichao Song1, Yujie Ding1, Xiaoyuan Yang1,2

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2477-2497, 2023, DOI:10.32604/iasc.2023.039238

    Abstract Smart grid (SG) brings convenience to users while facing great challenges in protecting personal private data. Data aggregation plays a key role in protecting personal privacy by aggregating all personal data into a single value, preventing the leakage of personal data while ensuring its availability. Recently, a flexible subset data aggregation (FSDA) scheme based on the Paillier homomorphic encryption was first proposed by Zhang et al. Their scheme can dynamically adjust the size of each subset and obtain the aggregated data in the corresponding subset. In this paper, firstly, an efficient attack with both theorems proving and experimentative verification is… More >

  • Open Access


    Blockchain-Enabled Secure and Privacy-Preserving Data Aggregation for Fog-Based ITS

    Siguang Chen1,2,*, Li Yang1,2, Yanhang Shi1,2, Qian Wang1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3781-3796, 2023, DOI:10.32604/cmc.2023.036437

    Abstract As an essential component of intelligent transportation systems (ITS), electric vehicles (EVs) can store massive amounts of electric power in their batteries and send power back to a charging station (CS) at peak hours to balance the power supply and generate profits. However, when the system collects the corresponding power data, several severe security and privacy issues are encountered. The identity and private injection data may be maliciously intercepted by network attackers and be tampered with to damage the services of ITS and smart grids. Existing approaches requiring high computational overhead render them unsuitable for the resource-constrained Internet of Things… More >

  • Open Access


    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

    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 improve the security of the… More >

  • Open Access


    Efficient Energy and Delay Reduction Model for Wireless Sensor Networks

    Arslan Iftikhar1, M. A. Elmagzoub2, Ansar Munir1,*, Hamad Abosaq Al Salem2, Mahmood ul Hassan3, Jarallah Alqahtani2, Asadullah Shaikh2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1153-1168, 2023, DOI:10.32604/csse.2023.030802

    Abstract In every network, delay and energy are crucial for communication and network life. In wireless sensor networks, many tiny nodes create networks with high energy consumption and compute routes for better communication. Wireless Sensor Networks (WSN) is a very complex scenario to compute minimal delay with data aggregation and energy efficiency. In this research, we compute minimal delay and energy efficiency for improving the quality of service of any WSN. The proposed work is based on energy and distance parameters as taken dependent variables with data aggregation. Data aggregation performs on different models, namely Hybrid-Low Energy Adaptive Clustering Hierarchy (H-LEACH),… More >

  • Open Access


    Hierarchical Data Aggregation with Data Offloading Scheme for Fog Enabled IoT Environment

    P. Nalayini1,*, R. Arun Prakash2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2033-2047, 2023, DOI:10.32604/csse.2023.028269

    Abstract Fog computing is a promising technology that has been emerged to handle the growth of smart devices as well as the popularity of latency-sensitive and location-awareness Internet of Things (IoT) services. After the emergence of IoT-based services, the industry of internet-based devices has grown. The number of these devices has raised from millions to billions, and it is expected to increase further in the near future. Thus, additional challenges will be added to the traditional centralized cloud-based architecture as it will not be able to handle that growth and to support all connected devices in real-time without affecting the user… More >

  • Open Access


    Discrete GWO Optimized Data Aggregation for Reducing Transmission Rate in IoT

    S. Siamala Devi1, K. Venkatachalam2, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1869-1880, 2023, DOI:10.32604/csse.2023.025505

    Abstract The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced technologies. Early diagnosis of many diseases will improve the patient life. The cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things (IoT), Wireless Sensor Networks (WSN), Embedded systems, Deep learning approaches and Optimization and aggregation methods. The data generated through these technologies will demand the bandwidth, data rate, latency of the network. In this proposed work, efficient discrete grey wolf optimization (DGWO) based data aggregation scheme using Elliptic curve Elgamal with Message… More >

  • Open Access


    Data Aggregation-based Transmission Method in Ultra-Dense Wireless Networks

    Dae-Young Kim, Seokhoon Kim*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 727-737, 2023, DOI:10.32604/iasc.2023.027563

    Abstract As the Internet of Things (IoT) advances, machine-type devices are densely deployed and massive networks such as ultra-dense networks (UDNs) are formed. Various devices attend to the network to transmit data using machine-type communication (MTC), whereby numerous, various are generated. MTC devices generally have resource constraints and use wireless communication. In this kind of network, data aggregation is a key function to provide transmission efficiency. It can reduce the number of transmitted data in the network, and this leads to energy saving and reducing transmission delays. In order to effectively operate data aggregation in UDNs, it is important to select… More >

  • Open Access


    Lamport Certificateless Signcryption Deep Neural Networks for Data Aggregation Security in WSN

    P. Saravanakumar1, T. V. P. Sundararajan2, Rajesh Kumar Dhanaraj3, Kashif Nisar4,*, Fida Hussain Memon5,6, Ag. Asri Bin Ag. Ibrahim4

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1835-1847, 2022, DOI:10.32604/iasc.2022.018953

    Abstract Confidentiality and data integrity are essential paradigms in data aggregation owing to the various cyberattacks in wireless sensor networks (WSNs). This study proposes a novel technique named Lamport certificateless signcryption-based shift-invariant connectionist artificial deep neural networks (LCS-SICADNN) by using artificial deep neural networks to develop the data aggregation security model. This model utilises the input layer with several sensor nodes, four hidden layers to overcome different attacks (data injection, compromised node, Sybil and black hole attacks) and the output layer to analyse the given input. The Lamport one-time certificateless signcryption technique involving three different processes (key generation, signcryption and unsigncryption)… More >

  • Open Access


    Improved Energy Based Multi-Sensor Object Detection in Wireless Sensor Networks

    Thirumoorthy Palanisamy1,*, Daniyal Alghazzawi2, Surbhi Bhatia3, Areej Abbas Malibari2, Pankaj Dadheech4, Sudhakar Sengan5

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 227-244, 2022, DOI:10.32604/iasc.2022.023692

    Abstract Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can sense physical characteristics such as temperature, sound, pressure, energy, and so on. WSNs have secure link to physical environment and robustness. Data Aggregation (DA) plays a key role in WSN, and it helps to minimize the Energy Consumption (EC). In order to have trustworthy DA with a rate of high aggregation for WSNs, the existing research works have focused on Data Routing for In-Network Aggregation (DRINA). Yet, there is no accomplishment of an effective balance between overhead and routing. But EC required during DA remained unsolved. The… More >

  • Open Access


    DAMFO-Based Optimal Path Selection and Data Aggregation in WSN

    S. Sudha Mercy1,*, J. M. Mathana2, J. S. Leena Jasmine3

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 589-604, 2022, DOI:10.32604/iasc.2022.021068

    Abstract Wireless Sensor Network (WSN) encompasses several tiny devices termed as Sensor Nodes (SN) that have restriction in resources with lower energy, memory, together with computation. Data Aggregation (DA) is required to optimize WSN for secured data transmission at Cluster Head (CH) together with Base Station (BS). With regard to the Energy Efficiency (EE) along with the privacy conservation requirements of WSN in big-data processing and aggregation, this paper proposed Diversity centered Adaptive Moth-Flame Optimization (DAMFO) for Optimal Path Selection (OPS) and DA in WSN. In the proposed work, initially, the Trust Evaluation (TE) process is performed. The Pompeiu Distance-centered Fuzzy… More >

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