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检索条件"任意字段=Conference on Photonic Devices and Algorithms for Computing III"

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IoT DDoS Attack Detection System Using Machine Learning Classification Techniques

IoT DDoS Attack Detection System Using Machine Learning Clas...

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Student conference on Research and Development (SCOReD)

作者： Aiman Saftwan Bin Sa’Idi Ameerah Muhsinah Binti Jamil Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pekan Malaysia

ISBN: (数字)9798350318821

ISBN: (纸本)9798350318838

The Internet of Things (IoT) has experienced substantial expansion, facilitating the connection of a multitude of devices to the Internet and enhancing the level of automation in several aspects of our daily routines. Nevertheless, the expansion has also brought to light several weaknesses, most notably the occurrence of Distributed Denial of Service (DDoS) attacks. IoT devices, which frequently lack comprehensive security measures, are vulnerable to such attacks. The objective of this work is to explore the feasibility of employing machine learning (ML) classification techniques to identify DDoS attacks on IoT networks. This study focuses on three commonly employed machine learning classification techniques: (i) Decision Tree (DT), (ii) Random Forest (RF), and (iii) Naïve Bayes (NB). The models will undergo training using a dataset specifically designed for detecting and classifying DDoS attacks. The TON IoT (UNSWIoT20) dataset sourced from the School of Engineering at the University of New South Wales Canberra is included in the study as the selected dataset. Among the several datasets accessible from the source, the IoT Network dataset with a specific emphasis on DDoS attacks was deliberately selected. To determine the efficacy of the suggested solution, a comprehensive assessment of the dataset is conducted. The testing results are then compared and analyzed to determine the model with the utmost level of precision in detecting DDoS attacks. This paper is a valuable contribution to the subject of IoT security by offering possible efficient and resilient approaches to address DDoS attacks targeting IoT devices and networks. The detection system, which utilizes machine learning, provides a proactive approach to protection, thereby guaranteeing the security and dependability of Internet of Things (IoT) services. Additionally, it facilitates the sustained growth of the IoT ecosystem.

关键词： Radio frequency Biological system modeling Denial-of-service attack Classification algorithms Bayes methods Internet of Things Decision trees

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Offloading of tasks efficiently in mobile edge computing platform

Offloading of tasks efficiently in mobile edge computing pla...

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2020 IEEE International conference on computing, Power and Communication Technologies, GUCON 2020

作者： Guleria, Charu Baruah, Bikash Bhuyan, Dikhit Kumar Mahanta, Kashmiri Moni DUIET Dibrugarh University Department of CSE Dibrugarh Assam India

ISBN: (纸本)9781728150703

A nifty rise in the production and usage of sophisticated mobile devices, improvements in the IoT (Internet of Things) domain have led to a substantial pool of data to work with. With more technological advancements comes the demand for more advanced and resource hungry applications which need overwhelming computing at short notice. Fulfilling this need poses a challenge due to difference between the growth of capable hardware and resource-intensive applications with the latter outpacing the former in growth. By bringing cloud computing resources to the end users (mobile devices in this context), otherwise known as MEC (mobile edge computing) the need of capable hardware is solved by using existing cloud services by efficiently offloading applications, classified using a Deep Learning Model dynamically and previously maintained log on the basis of LRU (Least Recently Used) and other efficient algorithms. With the help of neural network, the model develops a capacity to become more efficient with subsequent usage (herewith more data to feed on) hence encouraging more usage without any compromise in performance. © 2020 IEEE.

关键词： Mobile edge computing

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Scaling Edge computing through S-BVT and Pb/s Switching devices in Large Dense Urban Metro Networks 22

Scaling Edge Computing through S-BVT and Pb/s Switching Devi...

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22nd International conference on Transparent Optical Networks (ICTON)

作者： Otero, G. Fernandez-Palacios, J. P. Moreolo, M. Svaluto Larrabeiti, D. Hernandez, J. A. Fabrega, J. M. Lopez, V Nadal, L. Martinez, R. Univ Carlos III Madrid Madrid Spain Telefon Espana Madrid Spain Ctr Tecnol Telecomunicac Catalunya Castelldefels Spain

ISBN: (数字)9781728184234

ISBN: (纸本)9781728184234

Dense metropolitan areas are responsible for the majority of the traffic growth in telecom operators. The focus of the EU H2020 PASSION project is to develop new photonic technologies for supporting agile metro networks and enabling capacities of Tb/ s per channel to deal with such traffic increment, with a particular focus on two components (1) the Sliceable Bandwidth Variable Transceivers (S-BVT) and (2) Pb/s optical switches. This paper analyses two strategies from the perspective of computation resource consumption: overflow over a paired same-level DC and overflow over a centralized site. We present a methodology to compare both schemes and prove that a proper distribution of computing resources in the centralized overflow together with S-BVT high-speed transmission can outperform the costs of a distributed strategy, requiring fewer processors and much smaller DCs.

关键词： S-BVT metro are network software defined networking edge computing overflow traffic PASSION project

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Analytics-Aware Storage of Surveillance Videos: Implementation and Optimization 6

Analytics-Aware Storage of Surveillance Videos: Implementati...

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6th IEEE International conference on Smart computing (SMARTCOMP)

作者： Tsai, Min-Han Venkatasubramanian, Nalini Hsu, Cheng-Hsin Natl Tsing Hua Univ Hsinchu Taiwan Univ Calif Irvine Irvine CA USA

ISBN: (纸本)9781728169972

Increasingly more surveillance cameras in smart environments stream videos to storage servers for on-demand video analytics queries in the future. Unlike on-demand video services, in which maximizing the user-perceived video quality is the design objective, the considered storage servers aim to retain as much information as possible while offering enough space for incoming video clips. In this paper, we design, optimize, and implement an analytics-aware storage server on a smart campus testbed at NTHU, Taiwan, which consists of eight smart street lamps equipped with various sensors, network devices, analytics servers, and a storage server. We focus on the design and implementation of the storage server, and consider two key research problems: (i) how to efficiently determine the information amount of individual video clips and (ii) how to intelligently downsample individual video clips. More specifically, the first problem is to sample video frames from the stored video clips to analyze for approximations of the information amount without overloading the storage server. The resulting information amount is fed into the second problem to decide the video downsampling approaches for retaining as much information amount as possible without consuming excessive storage space. We propose two efficient algorithms to solve these two problems and compare their performance with the current practices via real experiments on our smart campus testbed. Our experiment results reveal the practicality and efficiency of our proposed design and algorithms, e.g., compared to the current practices, our storage server: (i) improves the per-request information amount by up to similar to 4 times, (ii) increases the total information amount by at most similar to 20%, (iii) boosts the number of saved video clips by up to similar to 35%, (iv) runs in real-time, and (v) scales well with larger storage space.

关键词： Video analysis and downsampling information quantization storage optimization edge computing

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Design of Smart Home System Based on Collaborative Edge computing and Cloud computing 20th

Design of Smart Home System Based on Collaborative Edge Comp...

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20th International conference on algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Ma, Qiangfei Huang, Hua Zhang, Wentao Qiu, Meikang Jingdezhen Ceram Inst Sch Informat Engn Jingdezhen Peoples R China Texas A&M Univ Dept Comp Sci Commerce TX 75428 USA

ISBN: (纸本)9783030602482;9783030602475

With the rapid development of the Internet, more and more smart devices are beginning to enter people's daily lives. The intelligentization of home appliances has gradually become a trend in home networking. How to construct and manage smart homes reasonably system has become the focus of research. Considering the needs and characteristics of smart homes, this paper combines edge computing and cloud computing in intelligent home scenarios to design a smart home system. To improve the system's reliability and real-time performance, we propose a cloud and edge collaborative processing algorithm strategy and use Kubernetes container management platform technology to deploy the system uniformly. Experimental results showed that the system has higher operating efficiency than the system using cloud computing as the center and single edge computing as the center, which can further ensure the smart homes real-time requirements.

关键词： Smart home Edge computing Cloud computing Container Algorithm strategy

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A Cost-Effective photonics-based Device for Early Prediction, Monitoring and Management of Diabetic Foot Ulcers 20

A Cost-Effective Photonics-based Device for Early Prediction...

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13th International conference on Pervasive Technologies Related to Assistive Environments

作者： Doulamis, Anastasios Doulamis, Nikolaos Angeli, Aikaterini Natl Tech Univ Athens Athens Greece Univ Athens Sch Med Athens Greece

ISBN: (纸本)9781450377737

Early prediction and management of Diabetic Foot Ulcers (DFUs) is an important health factor of Europe. Recent clinical trials have concluded that NIR sensing captures oxy(deoxy)haemoglobin (HbO2, Hb) and peripheral/ tissue oxygen saturations (StO2, SpO2), thermal Infrared-IR detects hyperthermia, among Regions of Interest (ROIs) and Mid-IR contains rich information about the proteomics, lipidomics and metabolomics (e.g., glucose). Current medical approaches are i) invasive (e.g., skin lesion biopsy), ii) requires consumables, and iii) being operated by certified physicians. Our research aims at developing a non-invasive, reliable and cost-effective photonics-driven device for DFU monitoring and management which can be applied for wide use. Hyper-spectral image data are exploited for this purpose. Cost-effectiveness is achieved by introducing i) targeted photonics technologies for DFU, ii) implementing advanced signal processing/learning algorithms to increase the discrimination accuracy while maintaining hardware cost-benefit, (iii) developing a user-friendly framework operated by non-certified physicians, and even by patients, and (iv) minimizing operational cost with our non-invasive device.

关键词： photonic devices Diabetic foot Ulcers Hyper-spectral imaging

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Towards a Secure Communication of Data in IoT Networks: A Technical Research Report 20th

Towards a Secure Communication of Data in IoT Networks: A Te...

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20th International conference on algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Asare, Bismark Tei Quist-Aphetsi, Kester Nana, Laurent Ghana Technol Univ Comp Sci Dept Accra Ghana CRITAC Cyber Secur Div Cape Coast Ghana CRITAC Directorate Informat Assurance & Intelligence Res Cape Coast Ghana Univ Brest Lab STICC CNRS UMR 6285 F-29200 Brest France

ISBN: (纸本)9783030602482;9783030602475

The past decade has seen a sharp rise in the number and research efforts towards improving optimization, efficiency, security and privacy challenges of internet-of-things (IoT) networks. Internet-of-Things (IoT) and its related frameworks have brought about convenience and improved lifestyle through the use of automation services that have afforded individuals, businesses and Governments the unique opportunities to expand their control and efficiently handle growth. Although recent IoT network architecture have attempted to incorporate cloud components to assist in storing sensed data from edge devices in order to create a much larger storage space for these sensed data and also make them readily accessible and available on demand;issues of security, trust and privacy challenges in IoT network architectures that incorporate the cloud have not been satisfactorily addressed. There is the need for a cloud based IoT network architecture that provides a good balance and fair trade-off between security, efficiency and trust to facilitate the transfer of data between edge nodes and the cloud to lessen the storage workload on the edge nodes to make them efficient. We aim to address the challenges of ensuring an efficient and secured approach in offloading the validated messages from edge nodes and the cloud by proposing an architecture that uses blockchain-based cryptographic techniques to allow IoT devices to be discovered each other to reach an agreement in the validation of messages on devices and the cloud.

关键词： Internet-of-Things Stellar Consensus Protocol Blockchain Cloud-computing Signature schemes

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Policy Gradient based Quantum Approximate Optimization Algorithm 1

Policy Gradient based Quantum Approximate Optimization Algor...

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conference on Mathematical and Scientific Machine Learning

作者： Yao, Jiahao Bukov, Marin Lin, Lin Univ Calif Berkeley Dept Math Berkeley CA 94720 USA Univ Calif Berkeley Dept Phys Berkeley CA 94720 USA Lawrence Berkeley Natl Lab Computat Res Div Berkeley CA 94720 USA

The quantum approximate optimization algorithm (QAOA), as a hybrid quantum/classical algorithm, has received much interest recently. QAOA can also be viewed as a variational ansatz for quantum control. However, its direct application to emergent quantum technology encounters additional physical constraints: (i) the states of the quantum system are not observable;(ii) obtaining the derivatives of the objective function can be computationally expensive or even inaccessible in experiments, and (iii) the values of the objective function may be sensitive to various sources of uncertainty, as is the case for noisy intermediate-scale quantum (NISQ) devices. Taking such constraints into account, we show that policy-gradient-based reinforcement learning (RL) algorithms are well suited for optimizing the variational parameters of QAOA in a noise-robust fashion, opening up the way for developing RL techniques for continuous quantum control. This is advantageous to help mitigate and monitor the potentially unknown sources of errors in modern quantum simulators. We analyze the performance of the algorithm for quantum state transfer problems in single- and multi-qubit systems, subject to various sources of noise such as error terms in the Hamiltonian, or quantum uncertainty in the measurement process. We show that, in noisy setups, it is capable of outperforming state-of-the-art existing optimization algorithms.

关键词： Quantum approximate optimization algorithm Policy gradient Reinforcement learning Robust optimization Quantum computing Quantum control

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Optimizing the A* search algorithm for mobile robotic devices 3

Optimizing the A* search algorithm for mobile robotic device...

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3rd International conference on Cognitive Robotics

作者： Maneev, V. V. Syryamkin, M. V. Natl Res Tomsk State Univ Tomsk Russia

The purposes of this article are to analyze the pathfinding algorithms used to search and calculate the trajectory of movement of mobile autonomous robotic devices and to search for optimization methods in order to reduce the load on computing and memory units of the mobile devices. This paper analyzes the basic pathfinding algorithms including breadth-first search, depth-first search, Dijkstra's algorithm, greedy best-first search, and the A*algorithm, considers principles of their work, and proposes optimization methods. This work results in a new approach for using the A* algorithm for solving problems associated with pathfinding in real dynamic environments. The proposed approach speeds up the process of path calculation and the choice of the movement direction and reduces the requirements for computing power of autonomous mobile devices.

关键词： computing power

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Integrated Single Photon Source of InAs Quantum Dot with Silicon based photonic Circuits

Integrated Single Photon Source of InAs Quantum Dot with Sil...

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conference on Lasers and Electro-Optics Europe / European Quantum Electronics conference (CLEO/Europe-EQEC)

作者： Ko, Young-Ho Han, Won Seok Kim, Kap-Joong Choi, Byung-Seok Kim, Kyu Young Kim, Je-Hyung Youn, Chun Ju Kim, Jong-Hoi Ju, Jung Jin Elect & Telecommun Res Inst ETRI Photon Wireless Convergence Res Dept 218 Gajeong Ro Daejeon 34129 South Korea Ulsan Natl Inst Sci & Technol UNIST Dept Phys UNIST Gil 50 Ulsan 44919 South Korea

ISBN: (纸本)9781728104690

A single photon source is an essential element for the photonic quantum information applications including the quantum communication, the quantum simulation, and the quantum computation [1,2]. Semiconductor quantum dots (QDs) have been widely considered as a promising platform for the single photon source due to their various advantages of manipulation and integration with various photonic elements. To realize the on-chip quantum devices, there have been numerous effort to integrate iii-V QDs with silicon-based photonic circuits [3,4]. However the self-assembled QDs have inherent drawbacks of irregular size distribution and random position. To overcome these drawbacks, various methods have been studied to obtain the site-controlled QDs such as the pyramid, the inverted pyramid, the nanohole, and the spatially selective H incorporation techniques [5]. In this study, we obtained site-controlled InAs QDs by the selective-area growth (SAG) method and integrated single photon source with the silicon-based photonic circuits through the micro-transfer technique.

关键词： photonics Silicon Indium phosphide iii-V semiconductor materials Quantum dots Quantum computing System-on-chip

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