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Optimized Hybrid Cryptographic Technique Using Symmetric and Asymmetric Encryption for Cloud computing

Optimized Hybrid Cryptographic Technique Using Symmetric and...

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Advances in Electrical, computing, Communication and Sustainable technologies (ICAECT), international conference on

作者： R. Suresh T.R. Nisha Dayana Department of Computer Science Vel's Institute of Science Technology and Advanced Studies Chennai Tamil Nadu India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

Cloud computing (CC) is an expanding computing concept in which computing resources are given as Internetbased services. Security and confidentiality of cloud storage services are critical and pose a difficulty in cloud computing owing to loss of control over data and reliance on the cloud computing provider. While there is a big number of transmitting data in the cloud system, the risk of data access by attackers raises. CC requires encryption to maintain the privacy and security of data stored, processed, and transported on the cloud. Encryption ensures that confidential information saved in the cloud stays private and accessible only to authorized parties. The field of cryptography is continuously evolving to deal with current challenges in cybersecurity, confidentiality, and computing power. Optimizing encryption algorithms entails enhancing security, performance, and efficiency while reducing resource usage. This study suggests a optimized framework for encryption using RSA, an asymmetric key cryptography for key exchange and advanced / Encryption Standard (AES), a symmetric key cryptography for bulk message encryption to improve the efficiency of encryption. The suggested models's performance evaluated with RSA with Data Encrytpion Standard(DES) and RSA with BlowFish algorithms and the efficiency of RSA with AES is found to more in terms of Execution time, Throughput, memory usage and latency.

关键词： Cloud computing Data privacy Memory management Public key Throughput Data models Encryption Blockchains Computer security Standards

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Reinforcement Learning for Intrusion Detection: Recent Advances and Datasets

Reinforcement Learning for Intrusion Detection: Recent Advan...

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advanced innovations in Smart Cities (ICAISC), international conference on

作者： Dalal Fathi Afraa Attiah Abeer Hakeem Asma Cherif IT Department Faculty of Computing and Information Technology Kind Abdulaziz University Jeddah Saudi Arabia Center of Excellence in Smart Environment Research Kind Abdulaziz University Jeddah Saudi Arabia

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

With the development of technologies and increasing security threats, intrusion detection systems have become more critical in detecting and protecting operations from attacks. Deep learning has significantly contributed to advancements in intrusion detection, especially through reinforcement learning systems. This survey reviews the concepts of intrusion detection and Reinforcement Learning (RL) systems in intrusion detection (ID), with a focus on recent advancements using techniques such as Multi-Agent Reinforcement Learning (MARL), Adversarial Reinforcement Learning (AE-RL), and Inverse Reinforcement Learning (IRL). We also emphasize the crucial role of feature engineering in conjunction with RL techniques. By examining these cutting-edge approaches and their integration with advanced feature engineering methods, we aim to provide a comprehensive overview of the current state of the art in reinforcement learning-based intrusion detection systems and their potential to enhance cybersecurity measures. In addition to exploring the applications of reinforcement learning and feature engineering in intrusion detection, we highlight and analyze the most well-known databases used in this field, offering insights into the data resources that drive the development and evaluation of these advanced security systems.

关键词： Surveys Training Deep learning Technological innovation Smart cities Reviews Intrusion detection Reinforcement learning Feature extraction Computer security

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Design of Low power 4-Bit Adder for DSP Applications Using Custom 45nm Technology CMOS Standard Cell Design

Design of Low Power 4-Bit Adder for DSP Applications Using C...

引用

Intelligent and Innovative technologies in computing, Electrical and Electronics (IITCEE), international conference

作者： Abhi A Bharadwaj Arvind R Daksh Pankaj Patel Yasha Jyothi M Shirur Electronics and Communucation Engineering BNM Institue of Technology of Organization Bengaluru India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

The increasing demand for energy-efficient digital circuits in resource-constrained environments like mobile devices has driven the need for optimized low-power designs. This research focuses on the design of a 4-bit Ripple Carry Adder (RCA) tailored for Digital Signal Processing (DSP) applications. Using 45nm technology, the goal is to minimize the consumption of power while ensuring high performance. This design addresses static and dynamic power concerns by leveraging custom standard cell design and advanced low-power techniques like Sleepy CMOS Sleepy Stack (SC-SS) and the Forced Stack Technique (FST). The challenge is optimizing the RCA’s design to minimize power consumption while maintaining high operational speed, enabling integration into embedded DSP systems in resource-constrained environments such as mobile devices.

关键词： Performance evaluation power demand Microprocessors Computer architecture Digital signal processing Logic gates Energy efficiency Mobile handsets Adders Standards

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Analysis and Simulation of DC Microgrid for Sustainable Energy Development

Analysis and Simulation of DC Microgrid for Sustainable Ener...

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Intelligent and Innovative technologies in computing, Electrical and Electronics (IITCEE), international conference

作者： Kruthi Jayaram Vidya H A Department of Electrical & Electronics Engineering BNM Institute of Technology Bengaluru India Department of Electrical & Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

A Cutting edge modern day technology for the existing conventional power system is the idea of smart grid. To eradicate climate changes, market variations and security of power supply in near future smart grids help in restructuring the power structure. Smart grids are applied to low carbon energy emissions, electric vehicles, microgrid, renewable energy, flexible power system, distributed energy resources (DER’s), advanced metering infrastructure, fuel markets, customer support etc. In this paper, Analysis of DC Microgrid is implemented with distributed generation. On site generations like PV, wind and battery act as input sources and deliver output to the load. The proposed model is simulated in MATLAB Simulink and the results are verified for the operation of DC Microgrid using distributed energy resources. Results highlight upon the flow of power continuously using any one the input resources. The structure is implemented in MATLAB/Simulink and the results are tabulated.

关键词： Wind Software packages Microgrids Voltage Smart grids Batteries Distributed power generation Topology Security MATLAB

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Unified Kill Chain Model for Executing MITM Attacks in Microgrids with DERs

Unified Kill Chain Model for Executing MITM Attacks in Micro...

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power, Control and computing technologies (ICPC2T), conference on

作者： Suresh Mogilicharla Tony Kondety Manoj Tripathy Mital Kanabar Electrical Engineering Department Indian Institute of Technology Roorkee India GE Renewable Energy GE Grid Solutions Markham Ontario Canada

ISBN: (数字)9798331530402

ISBN: (纸本)9798331530419

The increasing integration of networked Distributed Energy Resources (DERs) into microgrids is expanding the attack surface of modern power systems, particularly in decentralized environments. This paper explores the use of the Unified Kill Chain (UKC) framework to model and execute a Man-in-theMiddle (MITM) attack in a microgrid, focusing on the various stages of the attack, from reconnaissance to the final impact on the Microgrid Energy Management System (MEMS). By leveraging the UKC, the study demonstrates how sophisticated attackers can exploit vulnerabilities in communication protocols like Modbus to manipulate critical parameters, such as the battery state of charge (SoC), leading to erroneous decision-making and undermining the operational reliability of the microgrid. The paper underscores the need for targeted defensive actions at each stage of the attack chain to detect, mitigate, and neutralize the intent of advanced persistent threats (APTs) against DER systems.

关键词： Micromechanical devices Protocols power control Focusing Microgrids Reconnaissance Distributed power generation power system reliability State of charge Reliability

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A Critical Study on Hybrid computing and Its Current Influences and Future Challenges

A Critical Study on Hybrid Computing and Its Current Influen...

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Intelligent and Innovative technologies in computing, Electrical and Electronics (IITCEE), international conference

作者： Praveen K V Joe Prathap P. M L Sherin Beevi W Vinil Dani Department of Information Technology St. Peter’s College of Engg. and Tech. Chennai India Department of Computer Science and Engineering R.M.D. Engineering College India Department of EEE St. Peter’s College of Engg. and Tech. Chennai India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

This research focuses on the evolving field of hybrid computing, which combines traditional computing architectures with advanced computational paradigms like quantum computing, neuromorphic computing, or cloud-edge computing. Hybrid computing involves integrating multiple computing models or systems to leverage their complementary strengths. For example, combining classical computing with quantum or neuromorphic approaches to solve complex problems more efficiently. The goal is to enhance computational power, increase efficiency, and tackle problems that are difficult for traditional computing models alone. Emerging technologies, including quantum computing, machine learning, and AI, are driving the need for hybrid systems. These technologies enable the handling of more complex computations that classical systems struggle with, such as optimization, simulation, and cryptography. The integration of cloud and edge computing is also central to hybrid computing, enabling decentralized computation and processing closer to data sources. Combining different computing paradigms requires seamless communication and integration between systems, which is a significant technical challenge. Main challenging areas are scalability, software and hardware compatibility, energy efficiency and security. There is a need for standard protocols and frameworks to enable smoother integration of various computing systems. New algorithms that can take advantage of hybrid architectures need to be developed. Depend on applications significant advancements in hardware, including quantum processors, neuromorphic chips, and integrated hybrid processors required. The rise of hybrid computing will also bring ethical concerns, such as the impact on jobs, privacy, and inequality in access to advanced technologies. The study concludes by emphasizing the transformative potential of hybrid computing while acknowledging the technical, economic, and societal hurdles that need to be overcome. It highlights

关键词： Quantum computing Program processors Scalability Computational modeling Biological system modeling Standards organizations Machine learning Organizations Hardware Optimization

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Towards a Parallel Code for Cellular Behavior in Vitro Prediction 4th

Towards a Parallel Code for Cellular Behavior in Vitro Pr...

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4th international conference on Numerical Computations: Theory and Algorithms, NUMTA 2023

作者： De Luca, Pasquale Galletti, Ardelio Marcellino, Livia Department of Mathematics University Carlos III of Madrid Leganes Spain International PhD Programme / UNESCO Chair "Environment Resources and Sustainable Development" Department of Science and Technology Parthenope University of Naples Centro Direzionale Isola C4 Naples Italy Science and Technologies Department Parthenope University of Naples Naples Italy

ISBN: (纸本)9783031812460

In recent years, there has been an increasing interest in developing in vitro models that predict the behavior of cells in living organisms. Mathematical models based on differential equations, and related numerical algorithms, have been provided to this aim. In this work, we present first experiences in designing parallel strategies for accelerating an algorithm for behavior prediction based on the Cellular Potts Model (CPM). In particular, we exploit the computational power of Graphic Process Units in CUDA environment to address main low-level kernels involved. Tests and experiments complete the paper. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Potts model

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Lowering the PAPR in advanced Waveforms Using PTS Method 7th

Lowering the PAPR in Advanced Waveforms Using PTS Method

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7th international conference on Communication, Device and Networking, ICCDN 2024

作者： Kumar, Arun Gaur, Nishant Joshi, Ira Nanthaamornphong, Aziz Department of Electronics and Communication Engineering New Horizon College of Engineering Bengaluru India Department of Physics JECRC University Jaipur India Department of ECE JECRC University Jaipur India College of Computing Prince of Songkla University Phuket Thailand

ISBN: (纸本)9789819753369

Filter Bank Multicarrier (FBMC) is an attractive modulation scheme for advanced wireless communication systems due to its capability to address issues like spectral efficiency and interference resilience. However, FBMC, like other multi-carrier modulation techniques, suffers from a high Peak-to-Average power Ratio (PAPR), limiting its practical deployment. This research focuses on mitigating PAPR in FBMC through the application of the Partial Transmit Sequence (PTS) method. The Partial Transmit Sequence technique, widely used in filter bank multi-carrier (FBMC) systems, has shown effectiveness in reducing PAPR by optimizing the phase factors of sub-blocks. Extending this methodology to FBMC requires a nuanced understanding of the unique characteristics of FBMC signals. The distinctive filter bank structure in FBMC introduces challenges and opportunities for PAPR reduction, making it a compelling area for investigation. The proposed research aims to explore and optimize the PTS method for FBMC, considering the filter bank characteristics and the peculiarities of FBMC signals. The study involves developing novel algorithms for selecting and applying phase factors to sub-blocks, tailored to the FBMC framework. Additionally, the research investigates the trade-off between PAPR reduction and the computational complexity associated with PTS in the FBMC context. This work leverages simulations and analytical modeling to assess the performance gains achieved by the PTS method in reducing PAPR for FBMC systems. Through systematic experimentation, the research aims to identify optimal configurations, offering insights into the parameters that most significantly impact PAPR reduction in FBMC using PTS. The outcomes of this study are expected to contribute to the design and optimization of FBMC-based communication systems, fostering advancements in wireless communication technologies. By addressing the PAPR challenges inherent in FBMC, the research aims to enhance the reliabili

关键词： Multicarrier modulation

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Advancements in Weather Monitoring System: A Comprehensive Review

Advancements in Weather Monitoring System: A Comprehensive R...

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international conference on Electronics, Materials Engineering and Nano-Technology (IEMENTech)

作者： Manjyot Singh Soni Mitra Jisan Bera Kaustav Rajib Ghosh Institute of Engineering and Management Kolkata India

ISBN: (数字)9798331520762

ISBN: (纸本)9798331520779

This review provides an in-depth analysis of recent advancements and key trends in weather monitoring systems. It emphasizes the progress made in technologies and highlights their significant contributions to the field. These systems are essential tools for collecting and interpreting atmospheric data to predict and monitor weather conditions, supporting applications such as disaster management, agriculture, aviation, and climate research. The review investigates modern sensor innovations, IoT-enabled systems, and remote sensing technologies that have transformed real-time data collection and analysis. It discusses advancements in performance factors, including accuracy, scalability, energy efficiency, and costeffectiveness. Furthermore, the paper explores advanced topics like machine learning-driven weather prediction, satellite-based observation systems, and the integration of cloud computing for improved data processing capabilities. Challenges such as hardware constraints, data reliability, and integration complexities are also examined, along with potential strategies to overcome them. By synthesizing existing research, this study offers valuable insights for professionals in the field, helping them enhance and innovate weather monitoring systems. The findings provide overview of present state-of-the-art technologies and propose directions for future research and development, emphasizing the importance of this field in addressing global challenges.

关键词： Cloud computing Technological innovation Accuracy Reviews Weather forecasting Real-time systems Hazards Forecasting Monitoring Remote sensing

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Artificial Intelligence in Health Care computing and Assessments in Oman: an Effectual Study

Artificial Intelligence in Health Care Computing and Assessm...

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Machine Learning and Autonomous Systems (ICMLAS), international conference on

作者： Wilfred Blessing N. R Hemalatha Gunasekaran Hariharan B. Jaber Saleh Salim Al Jabri Kavitha S. J Sutherlin Subitha G. College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Sultanate of Oman Department of Computational Intelligence SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Department of Computer Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Department of Computer Science and Engineering Stella Mary's College of Engineering Aruthenganvilai Tamil Nadu India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

Health care plays a vital responsibility in a human life span. World countries targets to provide better care for their citizens. Digital transformations and innovations in Artificial Intelligence (AI) technologies helps in deep for the novel solutions to speed-up the decision making process in health management and patient consulting. AI branches including Machine Learning (ML), Deep Learning (DL), Neural Networks (NN), Natural Language Processing (NLP) and so forth can support innovations in heal care domain. This paper presents the comprehensive and noble review on recent existing tools and techniques and also recommends advanced techniques for health care industry that are to be used in Sultanate of Oman. Furthermore, overcoming AI challenges are resulted and presented through the study. This work mainly aimed to produce the multiple dimensions and challenges that helps to develop AI powered real-life applications in health care support system.

关键词： Deep learning Technological innovation Ethics Reviews Decision making Surgery Medical services Natural language processing Medical diagnostic imaging Diseases

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