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A Modified Firefly Optimization Algorithm-Based Fuzzy Packet Scheduler for MANET

Intelligent Automation & Soft computing 2023年第6期36卷 2685-2702页

作者： Mercy Sharon Devadas N.Bhalaji Xiao-Zhi Gao Department of Information Technology SSN College of EngineeringKalavakkamChennai603110Tamil NaduIndia School of Computing University of Eastern FinlandYliopistonranta70210KuopioFinland

In Mobile ad hoc Networks(MANETs),the packet scheduling process is considered the major challenge because of error-prone connectivity among mobile nodes that introduces intolerable delay and insufficient throughput with high packet *** this paper,a Modified Firefly Optimization Algorithm improved Fuzzy Scheduler-based Packet Scheduling(MFPA-FSPS)Mechanism is proposed for sustaining Quality of Service(QoS)in the *** MFPA-FSPS mechanism included a Fuzzy-based priority scheduler by inheriting the merits of the Sugeno Fuzzy inference system that potentially and adaptively estimated packets’priority for guaranteeing optimal network *** further used the modified Firefly Optimization Algorithm to optimize the rules uti-lized by the fuzzy inference engine to achieve the potential packet scheduling *** adoption of a fuzzy inference engine used dynamic optimization that guaranteed excellent scheduling of the necessitated packets at an appropriate time with minimized waiting *** statistical validation of the proposed MFPA-FSPS conducted using a one-way Analysis of Variance(ANOVA)test confirmed its predominance over the benchmarked schemes used for investigation.

关键词： Packet scheduling firefly algorithm ad hoc networks fuzzy scheduler opnet simulator

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Website Traffic Time Series Forecasting Using Regression Machine Learning 12

Website Traffic Time Series Forecasting Using Regression Mac...

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12th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2023

作者： Sikka, Dhruv Vinoth Kumar, C.N.S. Srm Institute of Science and Technology School of Computing College of Engineering and Technology Department of Networking and Communications Kattankulathur603203 India

ISBN: (纸本)9781665462617

The term ''Web analytics'' pertains to the act of monitoring, analysing, and creating reports regarding the use of a website, such as its web pages, images, and videos. By utilising web analytics, businesses can retain their customers, increase their website traffic, and attract more visitors, which ultimately leads to higher revenue. A study has been conducted on statistical forecasting teaching notes of a website, which involved analysing five years of daily time series data for various traffic measures. These measures included the daily counts of page views, unique visitors, first-time visitors, and returning visitors for academic teaching notes on the website. This work presents a single unit of multiple regression machine learning models that can predict new user and returning user web traffic amounts over some time that can be expected over a certain period or on a specific time interval. The voting Regression model combines algorithms like Decision Tree Regression, Multi Linear Regression and Support Vector Machine Regression into a single unit that can predict expected traffic volume over a period with 99.96% accuracy and 0.24% of absolute error. © 2023 IEEE.

关键词： Websites

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A Graph Theory Based Self-Learning Honeypot to Detect Persistent Threats

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Intelligent Automation & Soft computing 2023年第3期35卷 3331-3348页

作者： R.T.Pavendan K.Sankar K.A.Varun Kumar Department of Mathematics College of EngineeringAnna UniversityChennai600025India Department of Networking and Communications School of ComputingSRM Institute of Science and TechnologyKattankulathur602203India

Attacks on the cyber space is getting exponential in recent *** penetrations and breaches are real threats to the individuals and *** security systems are good enough to detect the known threats but when it comes to Advanced Persistent Threats(APTs)they *** APTs are targeted,more sophisticated and very persistent and incorporates lot of evasive techniques to bypass the existing ***,there is a need for an effective defense system that can achieve a complete reliance of *** address the above-mentioned issues,this paper proposes a novel honeypot system that tracks the anonymous behavior of the APT *** key idea of honeypot leverages the concepts of graph theory to detect such targeted *** proposed honey-pot is self-realizing,strategic assisted which withholds the APTs actionable tech-niques and observes the behavior for analysis and *** proposed graph theory based self learning honeypot using the resultsγ(C(n,1)),γc(C(n,1)),γsc(C(n,1))outperforms traditional techniques by detecting APTs behavioral with detection rate of 96%.

关键词： Graph theory Domination Connected Domination Secure Connected Domination honeypot self learning ransomware

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Survey on Security Based Approach to Prevent Attacks in SDN Using IoT Framework 2

Survey on Security Based Approach to Prevent Attacks in SDN ...

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2nd International Conference on Edge computing and Applications, ICECAA 2023

作者： Prabhu, V. Balamurugan, P. School of Computing College of Engineering and Technology Srm Institute of Science and Technology Department of Computer Science and Engineering Kattankulathur Tamilnadu Chengalpattu603 203 India School of Computing College of Engineering and Technology Srm Institute of Science and Technology Department of Networking and Communications Kattankulathur Tamilnadu Chengalpattu603 203 India

ISBN: (纸本)9798350347579

Network evolution trendincludes Internet of Things (IoT) and Software-Defined Networking (SDN). By separating the data plane from the control plane, the software defined networking architectural framework is used and it will makes the network admins works more easily. SDN mainly focuses on network management and controls at the higher levels to monitoring and sharing the connection between the devices with the help of network connectivity in real time using the Internet of Things concepts. Almost in all the fields, IoT devices used so have to improve the security of IoT devices. The SDN has the centralized control logic, if the number of network traffic increases then centralized controller may not be handle all the network traffic requests at the same time, because the SDN controller is a single point of failure, its failure can bring the entire network down. The Software Defined Network (SDN) is easily exposed to various attacks mostly to DDoS attacks. Majority of the existing research is concentrated only on sensing of HR-DDoS attacks occurring over the control layer and not focusing on LR-DDoS attack occurring over the data layer because the accuracy of attacks on the LR-DDoS attacks are very low. This study mainly focusing on how to design the multi controller SDN architecture to improve the scalability, how to increase the detection accuracy of low-rate DDoS attacks on the SDN data layer and how to detect the attacks using machine learning algorithms. © 2023 IEEE.

关键词： Internet of things

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A lightweight identity based generalized signcryption scheme for secure communication in standard model

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International Journal of Information technology (Singapore) 2024年第2期16卷 1221-1229页

作者： Singh, Tej Kumar, Mukesh Gelmecha, Demissie Jabir Thakur, Ganesh Kumar Tyagi, Vikas Sori, Worku Jifara Department of Applied Sciences ABES Engineering College UP Ghaziabad India Institute of Applied Sciences & Humanities GLA University UP Mathura India Department of Electronics and Communication Engineering School of Electrical Engineering and Computing Adama Science and Technology University Adama Ethiopia Department of CSE IMS Engineering College UP Ghaziabad India Department of Computer Science School of Electrical Engineering and Computing Adama Science and Technology University Adama Ethiopia

The implementation of secure communication in the Industrial Internet of Things (IIoT) has made and it is a significant security concern. Identity-based generalized signcryption scheme is one among the cryptographic tools available that offers a secure way out to meet the security needs of IIoT. Our proposal is a lightweight scheme, an efficient identity-based generalized signcryption that works as an encryption signature, or signcryption scheme using only one algorithm in a standard model. This scheme is appropriate for storage-limited environments like wireless sensor networks and smart cards due to its lightweight nature. This means that it can be implemented in a range of IIoT applications where resources are limited, without compromising on security or efficiency. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s);author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

关键词： Bilinear Pairing Generalized signcryption Identity-based cryptography Signcryption

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A Novel Approach for Iris Recognition System Using Genetic Algorithm

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Journal of Artificial Intelligence and technology 2024年第1期4卷 9-17页

作者： Jayesh Mohanrao Sarwade Sandip Bankar Surekha Janrao Kishor Sakure Rohini Patil Shudhodhan Bokefode Nilesh Kulal School of Computing MIT-ADT University PuneIndia School of Technology Management and Engineering SVKM’sNMIMSNaviMumbaiIndia K.J.Somaiya Institute of Technology SionMumbaiIndia Terna Engineering College NaviMumbaiIndia

In a brand new era,with chaotic scenario that exists within the world,people are undermined with diverse psychological *** have been numerous sensible approaches on the way to understand and lessen those *** developments have verified to be one of the beneficial approaches for intercepting these *** recognition through human iris organ is said as one of the well-known biometric strategies because of its reliability and higher accurate return in comparison to different *** beyond literatures,terrible imaging condition,low flexibility of version,and small length iris image dataset are the constraints desiring *** these kinds of developments,the iris popularity structures are suitable gear for the human *** popularity has been an energetic studies location for the duration of previous couple of decades,due to its extensive packages in the areas,from airports to native land protection border *** the past,various functions and methods for iris recognition have been *** of the very fact that there are many approaches published in this field,there are still liberal amount of problems in this methodology like tedious and computational *** suggest an all-encompassing deep learning architecture for iris recognition supported by a genetic algorithm and a wavelet transformation,which may jointly learn the feature representation and perform recognition to realize high *** just a few training photos from each class,we train our model on a well-known iris recognition dataset and demonstrate improvements over prior *** think that this architecture can be frequently employed for various biometric recognition jobs,assisting in the development of a more scalable and precise *** exploratory aftereffects of the proposed technique uncover that the strategy is effective inside the iris acknowledgment.

关键词： biometrics genetics algorithm(GA) iris recognition machine learning wavelet transformation

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High Accurate Gold Prize Rate Prediction Using Random Forest Regression Algorithm 7

High Accurate Gold Prize Rate Prediction Using Random Forest...

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7th IET Smart Cities Symposium, SCS 2023

作者： Sivasangari, A. Deepa, R. Geetha Rani, K. Surendran, R. Tamilvizhi, T. School of Computing Sathyabama Institute of Science and Technology Chennai India Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Bangalore India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering Panimalar Engineering College Chennai600123 India

ISBN: (纸本)9781839539831

In the past, one of the precious resources utilized to fund trading purchases was gold. The nations that have gold resources are regarded as rich countries. The nation's gold reserves show how strong its economy is. Not only have government departments participated in gold reserves, but also a number of private individuals and businesses. The routine of the world's top financial prudence affects gold rates. An increase in investors has been drawn to gold due to the recent fluctuations in price. Transactions involving gold are risky, and price fluctuations in gold are unpredictable due to the unpredictability of the gold market. The suggested uses machine learning to forecast the price of gold. Generally, machine learning is used to predict economic variables. To train a prediction model, we use supervised learning algorithms such as multiple linear regression and random forest regression. © The Institution of engineering & technology 2023.

关键词： Multiple linear regression

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ARIMA Modeling for Reliable Potable Water Identification and Quality Prediction 5

ARIMA Modeling for Reliable Potable Water Identification and...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Selvaraj, P. Shalma, H. Srm Institute of Science and Technology Faculty of Engineering and Technology School of Computing Department of Computing Technologies Chennai Tamil Nadu Kattankulathur603203 India Sphoorthy Engineering College Department of Artificial Intelligence and Machine Learning Telengana Hyderabad India

ISBN: (纸本)9798331504403

This work aims to employ machine learning methods and visualization techniques for evaluating water quality by measuring its potability, a numerical indicator of water quality. The work utilizes water quality parameters to determine the stability condition using pH, Temperature, Dissolved Oxygen, Conductivity, Nitrate, Fecal Coliform, and Total Coliform to evaluate the overall water quality. ARIMA is utilized to identify and categorize water potability based on its features. Using Tableau's interactive dashboarding, we created an interactive dashboard to visually simplify water potability metrics in India. The study utilized both real datasets from various locations around the country using government data sourced directly from the Central Pollution Control Board (CPCB). Based on the results of the experiments, the ARIMA was found to be superior to other classifiers in accurately predicting water potability. © 2024 IEEE.

关键词： Water pollution control

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Live Audio Recognition and Text Conversion System 2

Live Audio Recognition and Text Conversion System

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2nd International Conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Sharma, Pratyaksha Gupta, Sumita Bhavya, Boddu Asmitha Sharma, Khushi Dhir, Saru Gambhir, Sapna Department of Computer Science & Engineering Amity School of Engineering & Technology Amity University UP India Department of Information Technology Amity School of Engineering & Technology Amity University UP India Dept. of Computer Science College of Engineering and Computing George Mason University United States

ISBN: (纸本)9798331530389

With the advancement of technologies, different methods are currently being used for converting spoken language into text. These systems offer a hands-free alternative to traditional input methods, especially for individuals with physical disabilities or those requiring efficient documentation of spoken content. The goal of this study is to review recent advancements in this field and highlight gaps in current research, with a focus on accuracy, language adaptability, ease of use, and the integration of various technologies. We also suggest future directions for enhancing and developing this technology further. © 2025 IEEE.

关键词： Hidden Markov models

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Environmental water quality prediction based on COOT-CSO-LSTM deep learning

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Environmental Science and Pollution Research 2024年第42期31卷 54525-54533页

作者： Rajagopal, Sankarasubbu Ganesh, Sundaram Sankar Karthick, Alagar Sampradeepraj, Thangavel Department of Information Technology National Engineering College Tamilnadu Kovilpatti628503 India Department of Computer Science and Engineering R.M.K. College of Engineering and Technology Puduvoyal Tamilnadu Thiruvallur601206 India Renewable Energy Lab Department of Electrical and Electronics Engineering KPR Institute of Engineering and Technology Tamilnadu Coimbatore641407 India Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Krishnankoil Tamilnadu Virudhunagar626126 India

Water resource management relies heavily on reliable water quality predictions. Predicting water quality metrics in the watershed system, including dissolved oxygen (DO), is the main emphasis of this work. The enhanced long short-term memory (LSTM) model was suggested to improve the model’s performance. Additionally, a hybrid model was employed to calculate the ideal parameter values for the LSTM model, which helped overcome the nonstationarity, unpredictability, and nonlinearity of the data about the water quality parameters. This model recruited the COOT method. The original weekly water quality values at the Vaigai River, Madurai, Tamil Nadu, India, were tested using the suggested hybrid model. An independent LSTM, the hybrid optimisation method takes its cues from the cuckoo bird’s reproductive strategy and a novel meta-heuristic optimisation technique dubbed COOT, which is based on the behaviour of a flock of coot birds. If implemented, the suggested hybrid model might serve as an alternate framework for water quality prediction, laying the groundwork for basin-wide efforts to manage water quality and control pollutants. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Macroinvertebrates

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