Personalized lightweight distributed network intrusion detection system in fog computing by Tianpeng YE, Xiang LIN, Jianhua LI, Xuankai ZHANG, Liwen XU

“…With the continuous development of Internet of Things (IoT) technology, there is a constant emergency of new IoT applications with low latency, high dynamics, and large bandwidth requirements.This has led to the widespread aggregation of massive devices and information at the network edge, promoting the emergence and deep development of fog computing architecture.However, with the widespread and in-depth application of fog computing architecture, the distributed network security architecture deployed to ensure its security is facing critical challenges brought by fog computing itself, such as the limitations of fog computing node computing and network communication resources, and the high dynamics of fog computing applications, which limit the edge deployment of complex network intrusion detection algorithms.To effectively solve the above problems, a personalized lightweight distributed network intrusion detection system (PLD-NIDS) was proposed based on the fog computing architecture.A large-scale complex network flow intrusion detection model was trained based on the convolutional neural network architecture, and furthermore the network traffic type distribution of each fog computing node was collected.The personalized model distillation algorithm and the weighted first-order Taylor approximation pruning algorithm were proposed to quickly compress the complex model, breaking through the limitation of traditional model compression algorithms that can only provide single compressed models for edge node deployment due to the high compression calculation overhead when facing a large number of personalized nodes.According to experimental results, the proposed PLD-NIDS architecture can achieve fast personalized compression of edge intrusion detection models.Compared with traditional model pruning algorithms, the proposed architecture achieves a good balance between computational loss and model accuracy.In terms of model accuracy, the proposed weighted first-order Taylor approximation pruning algorithm can achieve about 4% model compression ratio improvement under the same 0.2% model accuracy loss condition compared with the traditional first-order Taylor approximation pruning algorithm.…”
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State-of-the-Art Report on Fiber-Reinforced Lightweight Aggregate Concrete Masonry by Saul Rico, Roshanak Farshidpour, Fariborz M. Tehrani

“…A proposed solution presented in this investigation consists of introducing steel fibers to the lightweight aggregate concrete masonry mix. Previous investigations in the field of lightweight aggregate fiber-reinforced concrete have shown an increase in flexural strength, toughness, and ductility. …”
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Navigating the Challenges and Opportunities of Securing Internet of Autonomous Vehicles With Lightweight Authentication by Hazem Ismail Ali, Harrison Kurunathan, Mohamed Hamdy Eldefrawy, Flavius Gruian, Magnus Jonsson

Subjects: “…Lightweight authentication…”
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Experimental Study on Flexural Behaviour of Lightweight Multi-Ribbed Composite Slabs by Wei Huang, Xiang Ma, Bin Luo, Zeliang Li, Yujiao Sun

“…To develop new slabs with light weight and high rigidity as well as meet the requirements of use and facilitate construction, a large-span multi-ribbed composite slab (R-CS) with filled lightweight blocks is proposed based on systematic research. …”
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Cloud native based lightweight 5GC product and key technologies by Changyi CHEN, Gang LU, Lisha ZHOU, Zeyuan HUANG, Zhuangzhan MA

Subjects: “…lightweight 5G core…”
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LIGHTWEIGHT DESIGN OF STATOR FOR LARGE CAPACITY PERMANENT MAGNET GENERATOR SET by MA DengHui, YU ShenBo, ZHAI FengChen, DOU RuTong

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Alternative estimation of effective Youngs Modulus for Lightweight Aggregate Concrete LWAC by Meriem Fakhreddine Bouali, Abdelkader Hima

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Brain Age Prediction Using a Lightweight Convolutional Neural Network by Fatma Eltashani, Mario Parreno-Centeno, James H. Cole, Joao Paulo Papa, Fumie Costen

“…Our results show that it is feasible to build lightweight CNN models trained on small-scale, heterogeneous datasets and fine-tuned to new external clinical data, making significant steps toward practical clinical application.…”
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SCM-YOLO for Lightweight Small Object Detection in Remote Sensing Images by Hao Qiang, Wei Hao, Meilin Xie, Qiang Tang, Heng Shi, Yixin Zhao, Xiaoteng Han

“…The ability of SCM-YOLO to detect small objects in complex remote sensing environments has been significantly improved while maintaining its lightweight characteristics. The effectiveness and lightweight characteristics of SCM-YOLO are verified through comparison experiments with AI-TOD and SIMD public remote sensing small object detection datasets. …”
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Health Monitoring System for Nursing Homes with Lightweight Security and Privacy Protection by Yu’e Jiang, Jiaxiang Liu

“…So this paper proposed a health monitoring system with lightweight security and privacy protection for nursing homes. …”
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Mechanical Strengthening of Lightweight Aluminium Alloys through Friction Stir Process by P. Yogesh, Santaji Krishna Shinde, Shyamlal. C, R. Suresh kumar, Moti Lal Rinawa, G. Puthilibai, M. Sudhakar, Kassu Negash, Rajesh S

“…The aerospace industries are focused on lightweighting with alloys having good tensile strength, fracture toughness, fatigue resistance, and corrosion resistance. …”
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Structural behavior of Lightweight and High strength Layered Hollow Core Slabs by Asmaa Ghamry, Ahmed Esia, Louay Aboul-Nour

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Analysis and Structural Optimization of Gearbox for New Type Lightweight Bridge Crane by Zhu Shuaihua, Wang Zhengbing, Zhang Zhihong, Yan Shidang, Liu Zhongming

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Heavy and Lightweight Deep Learning Models for Semantic Segmentation: A Survey by Cristina Carunta, Alina Carunta, Calin-Adrian Popa

“…We provide a detailed review comprising the most significant methods for both heavy and lightweight two-dimensional (2D) semantic segmentation, starting with the introduction of convolutional neural networks until the use of Transformer architecture, the latter being a widely adopted model with state-of-the-art results in several artificial intelligence fields. …”
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LIGHTWEIGHT OPTIMIZATION OF VEHICLE FRAME STRUCTURE BASED ON THE KRIGING APPROXIMATE MODEL by REN Ming, SUN Tao, SHI YongJin, ZHENG SongLin, LI YuGang

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MODEL STIFFNESS VERIFICATION OF MINI-TRUCK BODY BASED ON LIGHTWEIGHT IMPROVEMENT by ZHAO HaiJun, WANG GuoHua, TIAN LiPing, LI Qi, LIU HongXia, WANG Nan

“…Body improvement of lightweight mini-truck made vehicle mass reduction of 10. 9kg. …”
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Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars by Mirosław Targosz, Wojciech Skarka, Piotr Przystałka

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Lightweight mobile Ad Hoc network authentication scheme based on blockchain by Xu ZHANG, Xin MA

“…In order to solve the problem that the existing authentication method can’t track the vulnerable of malicious nodes and depends on the centralized authentication center,based on the de-centralization,tamper-proof and traceable characteristics of blockchain technology,a distributed lightweight mobile Ad Hoc network authentication scheme was proposed.It included the establishment of peer-to-peer network,the design of certification ledger and the choice of consensus mechanism.Then the role of smart contracts was analyzed and discussed.In this scenario,when the maximum transmission delay τ_max between a pair of peers is given,the relationship between node authentication timeδand network size <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <msubsup> <mi>N</mi> <mi>t</mi> <mrow> <mtext>all</mtext></mrow> </msubsup></math></inline-formula>is satisfied with<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow><mo>(</mo> <mrow> <mfrac> <mrow> <msubsup> <mi>N</mi> <mi>t</mi> <mrow> <mtext>all</mtext></mrow> </msubsup> </mrow> <mn>3</mn> </mfrac> <mo>+</mo><mn>7</mn></mrow> <mo>)</mo></mrow><msub> <mi>τ</mi> <mrow> <mtext>max</mtext></mrow> </msub> <mo>≤</mo><mi>δ</mi><mo>≤</mo><mn>3</mn><mo stretchy="false">(</mo><msubsup> <mi>N</mi> <mi>t</mi> <mrow> <mtext>all</mtext></mrow> </msubsup> <mo>+</mo><mn>1</mn><mo stretchy="false">)</mo><msub> <mi>τ</mi> <mrow> <mtext>max</mtext></mrow> </msub></math></inline-formula> .…”
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Design of efficient anonymous identity authentication protocol for lightweight IoT devices by Zhenyu WANG, Yang GUO, Shaoqing LI, Shen HOU, Ding DENG

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Reconstructing a lightweight security protocol in the radio‐frequency identification systems by Alireza Abdellahi Khorasgani, Mahdi Sajadieh, Mohammad Rouhollah Yazdani

“…The comparison will reveal that the proposed protocol is both lightweight and highly secure.…”
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