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distributed DoS Detection in IoT Networks Using intelligent Machine Learning Algorithms 2

Distributed DoS Detection in IoT Networks Using Intelligent ...

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2nd international conference on Smart Technologies in computing, Electrical and Electronics, ICstCEE 2021

作者： Binny, S. Pendyala, Shamili Srimani Pimo, S. John Aurelia, Sagaya Reddy, P Rahul Satyanarayana, Damaraju Sri Sai Kristu Jyoti College of Management and Technology Department of Computer Science Kerala India Institute of Aeronautical Engineering Department of ECE Hyderabad India St. Xavier's Catholic College of Engineering Nagercoil India Christ University Bangalore India Geethanjali Institute of Science and Technology ECE Nellore India Chalmers University of Technology Goteborg Sweden

ISBN: (纸本)9781665482974

The threat of a distributed Denial of Service (DDoS) attack on web-based services and applications is grave. It only takes a few minutes for one of these attacks to cripple these services, making them unavailable to anyone. The problem has further persisted with the widespread adoption of insecure Internet of Things (IoT) devices across the Internet. In addition, many currently used rule-based detection systems are weak points for attackers. We conducted a comparative analysis of ML algorithms to detect and classify DDoS attacks in this paper. These classifiers compare Nave Bayes with J48 and Random Forest with ZeroR ML as well as other machine learning algorithms. It was found that using the PCA method, the optimal number of features could be found. ML has been implemented with the help of the WEKA tool. © 2021 IEEE.

关键词： Denial-of-service attack

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Blockchain based Security Management of Internet of Medical Things (IoMT) using Homomorphic Encryption using Metaheuristics with a Deep Learning Model

Blockchain based Security Management of Internet of Medical ...

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Trends in Quantum computing and Emerging Business Technologies (TQCEBT), international conference on

作者： S Santiago Prasanna B T Kashif Qureshi K Subash Department of Computer Science St. Joseph College (Autonomous) Trichy India Department of Computer Science and Engineering JSS Science and Technology University Mysuru India Department of Data Science AI India Department of Data Science St. Joseph College (Autonomous) Trichy India

ISBN: (数字)9798350384277

ISBN: (纸本)9798350384284

The introduction of the Internet of Medical Things (IoMT), has drastically transformed the worldwide landscape of healthcare delivery. The proliferation of IoMT devices in healthcare systems brings new issues in guaranteeing the security and privacy of sensitive patient data. We must secure a substantial amount of sensitive data from modification since IoMT is a high-volume, continually developing data domain. Since then, blockchain (BC) technology has been recognised as a distributed ledger that can manage a huge number of intelligent transactions and increase data security at the same time. A comprehensive resource management system may be offered by Blockchain-based security mechanisms with specific customisation and additional levels of authentication and verification. It has functioned brilliantly as a crucial component of the Bitcoin cryptocurrency. This work creates a blockchain-based Internet of Medical Things security management system using homomorphic encryption (HE). Key generation shows how the DOA may enhance cryptographic system security and efficacy. The IoMT-based HE-DOA system provided in this study employs blockchain to secure data exchange and diagnostic models. HE-DOA allows safe data transmission and diagnostic models with BC aid in IoMT. The recommended technique includes data collecting, encryption, and categorization. Blockchains (BCs) securely store data, and IoMT devices are crucial to early data collection. For data encryption, the dingo optimisation algorithm (DOA) may generate the key. Performance experiments and comparison with similar protocols show that the recommended procedure may enhance PSNR, accuracy, and computational time by 19.34%, 95.78%, and 1.887ms, respectively. Comparing HE-DOA to prior studies shows its scalability and durability.

关键词： Deep learning Data privacy Biological system modeling Security management Metaheuristics Internet of Medical Things Blockchains

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Enhanced Smart Waste Management System with Incinerator Compartment 7

Enhanced Smart Waste Management System with Incinerator Comp...

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7th international conference on Advanced computing and Communication Systems, ICACCS 2021

作者： Leninpugalhanthi, P. Bharanidaran, G. Bahiradhan, T. Abirami, E. Anandh, R. Kumar, R.Senthil Sri Krishna College of Technology Department of Eee Coimbatore India

ISBN: (纸本)9781665405201

As of now we are in the 21st century, where we find many technologies ruling the world, and the Internet of Things is one among them which can be defined as an intelligent node that was interconnected in a global infrastructure which helps to implement the connectivity of anything from anywhere at anytime and transferring of data over wireless network. Other than all the developments, human growth becomes liable to overwhelming and stopping difficulties which have been putting its existence in danger. And the issue of gathering trash been the main one. As the human population increases, and the lack of knowledge about the waste management system, increase the risk of pollution to the environment. The enormous measure of waste products is additionally a major danger to the environment. Disposing the Waste like wet, dry or biodegradable and non biodegradable which are getting dumped together are being the big deal in India right now. There was a large amount of plastics and other wastes were produced every year which are not currently carried out in any recycling plants. In order to provide a solution for these wastes and managing the wastes, we proposed a 'Enhanced Smart waste management system with Incinerator compartment', Where the wastes which may be located in either city or village, get monitored through sensors and programmed for informing the waste level status and transferred to the cloud. © 2021 IEEE.

关键词： Microcontrollers

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Cognitive-inspired Post-processing of optical character recognition for Swedish addresses

Cognitive-inspired Post-processing of optical character reco...

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IEEE international conference on Cognitive Informatics

作者： Moa Andersson Summrina Kanwal Faiza Khan School of Electrical Engineering and Computer Science Kth Royal Institute of Technology in Stockholm Sweden School of Electrical Engineering and Computer Science Kth Royal Institute of Technology in Stockholm Centre for Applied Intelligent Systems Research Halmstad University Sweden Faculty of Computing Riphah International University Islamabad Pakistan

Optical character recognition (OCR) has many ap-plications, such as digitizing historical documents, automating processes, and helping visually impaired people read. However, extracting text from images into a digital format is not an easy problem to solve, and the outputs from the OCR frameworks often include errors. The complexity comes from the many variations in (digital) fonts, handwriting, lighting, etc. To tackle this problem, this thesis investigates two different methods for correcting the errors in OCR output. The used dataset consists of Swedish addresses. The methods are therefore applied to postal automation to investigate the usage of these methods for further automating postal work by automatically reading addresses on parcels using OCR. The first method, the lexical implementation, uses a dataset of Swedish addresses so that any valid address should be in this dataset (hence there is a known and limited vocabulary), and misspelled addresses are corrected to the address in the lexicon with the smallest Levenshtein distance. The second approach uses the same dataset, but with artificial errors, or artificial noise, added. The addresses with this artificial noise are then used together with their correct spelling to train a machine learning model based on Neural machine translation (NMT) to automatically correct errors in OCR read addresses. The results from this study could contribute by defining in what direction future work connected to OCR and postal addresses should go. The results were that the lexical implementation outperformed the NMT model. However, more experiments including real data would be required to draw definitive conclusions as to how the methods would work in real-life applications.

关键词： Vocabulary Automation Computational modeling Optical character recognition Lighting Machine learning Complexity theory

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IoT-Enabled intelligent Farming System with Integrated Tracking and Water Gathering Plan

IoT-Enabled Intelligent Farming System with Integrated Track...

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Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF), international conference on

作者： Mekala Bhargav Nariboyina Pavan Sai N Pavan Jeffin Gracewell Electronics and Communication Engineering Saveetha Engineering College Chennai India

The goal of this research is to develop a smart irrigation system based on the Internet of Things that is affordable for a typical middle-class farmer. In the 21st century, automation has been more integrated into daily life. As a result of automation, machines may be programmed to operate without human intervention. The reduced energy use, increased productivity, and decreased amount of time spent on mundane tasks are all bonuses. In addition to being crucial to people's ability to eat and stay alive, agriculture is critical to a nation's economic development and overall prosperity. With the help of innovations like the Internet of Things (IoT), wireless sensor networks (WSNs), remote sensing, drone surveillance, and more, “fastidious agriculture” has emerged as a hot topic in the IT industry. In this study, we demonstrate the efficacy of our gadget, which is designed to give data and save water by only watering fields when they really need it. Cloud website named item talk is used to transmit the data to the farmers. The farmers may keep tabs on their fields with the use of thing speaks channel connection. A built-in Wi-Fi module in the microcontroller transmits the collected data to the thing talk cloud storage service. Then, we'll evaluate how much water is saved in various soil types, such as sand, clay, and sandy clay. The water savings from this technology are clearly visible when compared to the water savings from the conventional technique.

关键词： Wireless sensor networks Cloud computing Technological innovation Automation Surveillance Soil moisture Internet of Things

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Explainable Decentralized Federated Learning for Energy-Efficient Base station Sleep Control

Explainable Decentralized Federated Learning for Energy-Effi...

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international conference on Telecommunications (ICT)

作者： Narges Movahedkor Reza Shahbazian Seyed Ali Ghorashi Department of Computer Engineering Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran Department of Informatics Modeling Electronics and System Engineering (DIMES) University of Calabria Rende Italy School of Architecture Computing and Engineering University of East London London UK

ISBN: (数字)9798331514471

ISBN: (纸本)9798331514488

Given the capacity and performance boosts offered by the 5 G cellular networks, energy consumption at the base stations (BSs) has increased tremendously. This paper proposes a decentralized federated learning (DFL)-based intelligent BS switching, integrated with explainable artificial intelligence (XAI) methods, to mitigate the concerns for energy consumption in dense 5G networks. This entails collaboration among distributed but interconnected networks to learn the best policies for BS switching without any central controller, so that knowledge sharing can be ensured while privacy and communication efficiency are maintained. Very importantly, we further researched the XAI techniques to provide better transparency on the decisionmaking of the switching control agent and create some trust in the learned policies. Such explainability allows us to derive the most important factors affecting BS switching decisions and how these contribute in enabling energy savings while maintaining quality of service (QoS). Extensive simulations conducted to validate our proposed framework in presenting valuable XAI analysis have elaborately provided the basis for understanding the learned strategies and key factors driving energy-efficient BS management.

关键词： Base stations Energy consumption Explainable AI Federated learning 5G mobile communication Switches Quality of service Control systems Energy efficiency Telecommunications

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Determinants of technology Innovation Performance

Determinants of Technology Innovation Performance

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Software Engineering, Artificial Intelligence, Networking and Parallel/distributed computing (SNPD-Winter), ACIS international Winter conference on

作者： Min Young Park Hye Soo Choi Jeong Chul Yoon Soongsil University Seoul South Korea

This study aims to analyze the characteristics of technology innovation for domestic small and medium size enterprises by measuring a technology innovation effect level and analyzing technology innovation effect characteristics. The characteristics of study in this respect are to analyze both technology innovation effect based on three factors, product, process, and organization, by using Korea Innovation Survey Data, and characteristics of causal among innovation effects. In addition, the study has suggested a technology innovative diffusion pathway by analyzing innovation dynamics characteristics which has not been researched from pre-existed study.

关键词： Technological innovation Organizations Data collection Size measurement Manufacturing Investment Software engineering

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Development of Interactive Dashboards and intelligent Data Analytics for Visual Decision-Making in The Underground Mining Environment: The sterkfontein Cave Case study 18

Development of Interactive Dashboards and Intelligent Data A...

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18th international Bhurban conference on Applied Sciences and Technologies (IBCAst)

作者： Atif, Iqra Cawood, Frederick Thomas Mahboob, Muhammad Ahsan Univ Witwatersrand Wits Min Inst WMI Johannesburg South Africa Univ Witwatersrand Wits Min Inst WMI Sibanye Stillwater Digital Min Lab DigiMine Johannesburg South Africa

ISBN: (纸本)9781665405164

In the 21st century, the advancements of computing, Internet of Things and wireless communications are enabling mining companies to collect a vast amount of datasets during risk management. Multipurpose sensors installed at many locations in underground mining environment provide data about the safety, security and mine conditions in near real-time. However, it is more important to convert this data into strategic intelligence, which means the communication of the right information to the right people at the right time to enable them to make optimal and informed decisions on risk control and process optimization. The sterkfontein caves is a world heritage site, and over the past few years, some deformation was recorded inside the caves. Possible reasons include urbanization in the surrounding area, illegal dolomite mining in the past, weathering, man-made archaeological activities and continuous pouring of polluted and acidic water into the caves system. Acid water has high potential to dissolve the sensitive dolomite, create new and enlarge existing rock cavities, which can destabilize rock formations. The Wits Mining Institute (WMI) has installed a geotechnical and geo-environmental wireless sensor network inside the caves for monitoring and to gain a better understanding of deformation in a cave system. In this research, data analytics and visualization concepts have been applied to the data collected from the sensors in order to identify the trends or patterns inside the caves. Several dashboards have been developed to analyze and visualize the ground movement, wind velocity, temperature, humidity and toxic gases (carbon monoxide) using Tableau code. The data from ground movement monitoring sensors placed at different locations can be analyzed and visualized in relation to each other and in different time steps (minutes to hours, daily, weekly, monthly and/or yearly basis). The analytics can also be applied to the aggregated data based on seasonal, time and/or l

关键词： geotechnical and environmental sensors underground mining near real-time monitoring data analytics data visualization intelligent dashboards cave stability air quality

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The Compiler of DFC: A Source Code Converter that Transform the Dataflow Code to the Multi-threaded C Code 1

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21st international conference on Parallel and distributed computing, Applications, and Technologies, PDCAT 2020

作者： Du, Zheng Zhang, Jing Li, Jinrong Du, Haixin Shu, Jiwu Luo, Qiuming Department of Computer Science and Technology Tsinghua University Beijing China NHPCC/Guangdong Key Laboratory of Popular HPC College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (数字)9783030692445

ISBN: (纸本)9783030692438

The working principle of DFC compiler is introduced in this article. DFC is a grammatical extension of standard C language, with special DF function which describe the dependence of computing DAG. DFC compiler, dfcc, is used to convert the DFC source codes to standard C codes with the assistance of multi-threaded library. The lexical rules and grammatical rules are used to setup the Ast of DFC codes, and then it is converted to the Ast of standard C without DF function nodes. The derived Ast is printed into a text file, a normal C file, and finally is processed by GCC to obtain the executable file. The experiment gives some demonstration of that converting details, and the memory footprint is studied to show an ideal scalability. © 2021, Springer Nature Switzerland AG.

关键词： Program compilers

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Smart Energy station Terminal 5G Adaptation strategy Based on Genetic-Algorithm Task Offloading Method 21

Smart Energy Station Terminal 5G Adaptation Strategy Based o...

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21st IEEE international conference on Communication technology, ICCT 2021

作者： Qin, Li Zengqing, Qi Weiwei, Lin Zhiqiang, Xu Institute of Economic Technology State Grid Hunan Electric Power Limited Corporation Changsha China Hunan Economic and Research Power Design Co. Ltd. Changsha China

ISBN: (纸本)9781665432061

In order to meet the multi-service delay and power consumption requirements of smart energy stations without local hardware upgrades, this paper proposed a terminal 5G adaptation strategy based on genetic-algorithm task offloading method for smart energy station. Firstly, the related delay and reliability requirements are analyzed for the terminal tasks the smart energy station. Then, genetic algorithms are used to consider the delay and power consumption to optimize and obtain the optimal task offloading decision. Finally, the proposed genetic-algorithm task offloading method is depicted to implement the terminal 5G adaptation in the Smart energy station. Simulation experiment results illustrate that the proposed task offloading strategy can adapt to the terminal 5G performance of the smart energy station effectively, while the decision result meets the QoS requirements of the terminal services of the smart energy station. © 2021 IEEE.

关键词： Mobile edge computing

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