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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Jinsha Lawrence Dinesh Kumar Budagam P. Mukilan Kavitha Veerappan E. Chandrasekhar K. Barathi Department of Computer Science and Engineering Faculty of Engineering Karpagam Academy of Higher Education (Deemed to be University) Coimbatore India Department of MS in Software Engineering Security Architect at VISA California United States Department of Electronics and Communication Engineering Dhanalakshmi Srinivasan College of Engineering Coimbatore India Department of Electronics and Communication Engineering Kongu Engineering College Erode India Department of Electronics and Communication Engineering Chaitanya Bharathi Institute of Technology (A) Hyderabad India Department of Electrical and Electronics Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

The development of compact and efficient devices has been made possible by the growth of Very Large Scale Integration (VLSI) technologies, which has transformed modern electronics. However, there are cautions regarding the security of data, especially when it comes to transmission due to the extensive usage of technology. To address these, this study proposes a modified Advanced Encryption Standard (AES) algorithm as a solution for improved security protocol in VLSI systems. The proposed algorithm are intended to support the encryption procedure, increasing stronger production against cryptographic attacks while preserving the system's effectiveness and speed factors that are critical aspects for VLSI applications. Through extensive simulations and testing, the modified AES algorithm demonstrated significant security enhancements the operational efficiency of the VLSI system. The attained outcomes of the proposed work shows that the Modified AES strategy provides a workable technique to protect data in VLSI-based devices while maintaining data communication integrity and confidentiality. The proposed modified AES algorithm demonstrates a significant improvement in performance with a propagation delay of 7 ns, power consumption of 29 mW, and a computational overhead of 62 bits, leading to enhanced efficiency in cryptographic operations. This study highlights that the modified AES algorithm improve security in modern electronic systems and maintain performance.

关键词： Protocols Power demand System performance Very large scale integration Throughput Hardware Encryption Security Data communication Standards

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Asynchronous Fractional Multi-Agent Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing

arXiv

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arXiv 2024年

作者： Jin, Lyudong Tang, Ming Pan, Jiayu Zhang, Meng Wang, Hao Zhejiang University University of Illinois at Urbana–Champaign Institute Zhejiang University Haining314400 China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518000 China School of Software Technology Zhejiang University Ningbo315048 China Department of Data Science and AI Faculty of Information Technology Monash University MelbourneVIC3800 Australia

In the realm of emerging real-time networked applications such as industrial cyber-physical systems (CPS), the Age of Information (AoI) has emerged as a pivotal metric for evaluating the timeliness. To meet the high computational demands, such as those in smart manufacturing within CPS, mobile edge computing (MEC) presents a promising solution for optimizing computing and reducing AoI. In this work, we study the timeliness of computational-intensive updates and explore jointly optimizing the task updating (when to generate a task) and offloading (where to process a task) policies to minimize AoI. Specifically, we consider edge load dynamics and formulate a task scheduling problem to minimize the expected time-average AoI. Solving this problem is challenging due to the fractional objective introduced by AoI and asynchronous decision-making of the semi-Markov game (SMG). To this end, we propose a fractional reinforcement learning (RL) framework. We first introduce a fractional single-agent RL framework and further propose a fractional multi-agent RL framework, including convergence analysis for both scenarios. To tackle the challenge of asynchronous decision-making in SMG, we further design an asynchronous model-free fractional multi-agent RL algorithm, where each mobile device can determine the task updating and offloading decisions without knowing the real-time system dynamics and decisions of other devices. Experimental results show that when compared with the best baseline algorithm, our proposed algorithms reduce the average AoI by up to 52.6%. Copyright © 2024, The Authors. All rights reserved.

关键词： Markov processes

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EHG Signal Analysis for Prediction of Term and Preterm using Variational Mode Decomposition and Artificial Neural Networks

EHG Signal Analysis for Prediction of Term and Preterm using...

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Frontiers of Information Technology (FIT)

作者： Muhammad Umar Khan Sumair Aziz Khushbakht Iqtidar Raul Fernandez Rojas Department of Electronics Engineering University of Engineering and Technology Taxila Taxila Pakistan Department of Computer Software Engineering National University of Sciences and Technology Islamabad Pakistan Faculty of Science & Technology University of Canberra Canberra Australia

ISBN: (纸本)9798350345940

Preterm deliveries are an important cause of mortality and morbidity in newborns. Accurate and early prediction of a premature delivery can prove helpful in providing proper medication and treatment. Recording of electrical activity known as Electrohysterogram (EHG) from the abdominal surface of pregnant women corresponds to the uterus contractions. A new direction is open using EHG signals for the diagnosis of preterm births. In this research, we present a new method for the accurate classification of preterm and term EHG signals. The proposed method first filters a three-channel EHG signal using bandpass filters. Next, we combined the filtered three-channel EHG into one signal using an accumulation operation. The accumulated EHG signal was post-processed through variational mode decomposition (VMD). VMD algorithm splits the input signal into finite modes using center frequencies known as intrinsic mode functions (IMFs). An energy-based intelligent signal reconstruction approach is designed to combine IMFs having an energy level above the computed threshold. Next, the reconstructed EHG signals were split into continuous windows, and time, frequency, and Hjorth features were extracted. These features were fused to construct a distinct feature representation and were reduced using the ReliefF algorithm. We trained an artificial neural network (ANN) to obtain 98.8 % average accuracy using 10-fold cross-validation.

关键词： Band-pass filters Time-frequency analysis Artificial neural networks Filtering algorithms Feature extraction Signal reconstruction Classification algorithms

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The Essence of Perceived Compatibility and Behavioral Intention in Mobile Money Use

The Essence of Perceived Compatibility and Behavioral Intent...

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Advanced Information Scientific Development (ICAISD), International Conference on

作者： Leni Susanti Siti Hajar Mohamad Mila Andria Savitri Karen Etania Saputra Doni Purnama Alamsyah Ahmad Setiadi Entrepreneurship Department BINUS Business School Bina Nusantara University Jakarta Indonesia Department of Business Management and Law Management and Science University Selangor Malaysia Interior Design Department School of Design Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Software Engineering Department Faculty of Information Technology Universitas Bina Sarana Informatika Jakarta Indonesia

ISBN: (数字)9798350392036

ISBN: (纸本)9798350392043

Today, financial technology is a part of consumer needs. Mobile payments are used to support daily transactions, so a study of factors that can support behavioral intention and mobile money use is conducted. This study examines the support of digital literacy, perceived security, and perceived compatibility of mobile payments in increasing behavioral intention and mobile money use. The research was conducted on mobile payment users in Bandung City (Indonesia), and 416 research participants were asked using a questionnaire. The research was conducted using a quantitative survey and was processed using the SmartPLS tool. Two tests, namely, the PLS Algorithm and Bootstrapping, were used to test the research model. Next, the research hypothesis testing was used to explain the results. The research results found positive support from digital literacy, perceived security, and perceived compatibility on mobile payment behavioral intention. However, only perceived compatibility can directly increase the use of mobile money. In line with the hypothesis test, behavioral intention can support increased mobile money use by digital payment users. The research findings explain the ability of behavioral intention to mediate support for digital literacy, perceived security, and perceived compatibility in mobile money use.

关键词： Surveys Online banking Fintech Urban areas Security Digital intelligence Testing

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Latency and Secrecy Performance Analysis in Backscatter-Enabled Vehicular Cloudlet Networks

Latency and Secrecy Performance Analysis in Backscatter-Enab...

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IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia)

作者： Van-Long Nguyen Thi My Tien Bui Van-Binh Phan Dac-Binh Ha School of Computer Science Duy Tan University Da Nang Vietnam Quy Nhon AI Center FPT Software Science Avenue Quy Nhon City Binh Dinh Province Vietnam Faculty of Basic Sciences Kien Giang Vocational College Vietnam School of Engineering and Technology Duy Tan University Da Nang Vietnam

ISBN: (数字)9798331530839

ISBN: (纸本)9798331530846

In this work, we investigate the joint secrecy and latency performance of a multi-user backscatter communication (BC)-enabled vehicular network in the presence of a passive eavesdropper. Specifically, a number of vehicles intend to offload their tasks to a vehicle equipped with a mobile edge computing (MEC) server by utilizing dedicated BC communication and time division multiple access (TDMA) schemes. Meanwhile, a passive mobile eavesdropper attempts to intercept information from each user without any attacks. In order to investigate the performance of this system, we derive the closed-form expressions of the successful computation probability (SCP) and secrecy successful computation probability (SSCP) in two corresponding scenarios: with and without eavesdropper. In addition, the impacts of key parameters on the system's behavior to gain insight into its performance are also examined. Finally, the numerical results using Monte-Carlo simulations are provided to validate our analysis.

关键词： Time division multiple access Multi-access edge computing Monte Carlo methods Simulation Reflection coefficient Performance analysis Security Servers Backscatter Signal to noise ratio

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Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement Learning

arXiv

引用

arXiv 2024年

作者： Wang, Tianfu Shen, Li Fan, Qilin Xu, Tong Liu, Tongliang Xiong, Hui Anhui Province Key Laboratory of Big Data Analysis and Application School of Computer Science University of Science and Technology of China Hefei230027 China The School of Big Data and Software Engineering Chongqing University ChinaScience Chongqing401331 China JD Explore Academy The UBTECH Sydney Artificial Intelligence Centre The School of Information Technologies Faculty of Engineering and Information Technologies The University of Sydney DarlingtonNSW2008 Australia Thrust of Artificial Intelligence Nansha Guangdong Guangzhou511400 China The Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

As an essential resource management problem in network virtualization, virtual network embedding (VNE) aims to allocate the finite resources of physical network to sequentially arriving virtual network requests (VNRs) with different resource demands. Since this is an NP-hard combinatorial optimization problem, many efforts have been made to provide viable solutions. However, most existing approaches have either ignored the admission control of VNRs, which has a potential impact on long-term performances, or not fully exploited the temporal and topological features of the physical network and VNRs. In this paper, we propose a deep Hierarchical Reinforcement Learning approach to learn a joint Admission Control and Resource Allocation policy for VNE, named HRL-ACRA. Specifically, the whole VNE process is decomposed into an upper-level policy for deciding whether to admit the arriving VNR or not and a lower-level policy for allocating resources of the physical network to meet the requirement of VNR through the HRL approach. Considering the proximal policy optimization as the basic training algorithm, we also adopt the average reward method to address the infinite horizon problem of the upper-level agent and design a customized multi-objective intrinsic reward to alleviate the sparse reward issue of the lower-level agent. Moreover, we develop a deep feature-aware graph neural network to capture the features of VNR and physical network and exploit a sequence-to-sequence model to generate embedding actions iteratively. Finally, extensive experiments are conducted in various settings, and show that HRL-ACRA outperforms state-of-the-art baselines in terms of both the acceptance ratio and long-term average revenue. Our code is available at https://***/GeminiLight/hrl-acra. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Metaheuristic Based IDS Using Multi-objective Wrapper Feature Selection and Neural Network Classification 2nd

Metaheuristic Based IDS Using Multi-objective Wrapper Featur...

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2nd International Conference on Advances in Cyber Security, ACeS 2020

作者： Ghanem, Waheed Ali H. M. El-Ebiary, Yousef A. Baker Abdulnab, Mohamed Tubishat, Mohammad Alduais, Nayef A. M. Nasser, Abdullah B. Abdullah, Nibras Al-wesabi, Ola A. Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Terengganu Malaysia Faculty of Engineering and Faculty of Education-Aden and Saber Aden University Aden Yemen Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Kuala Terengganu Malaysia School of Computing and Technology Asia Pacific University of Technology and Innovation Kuala Lumpur Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit Raja Malaysia Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Pekan Malaysia National Advanced IPv6 Center Universiti Sains Malaysia Gelugor Malaysia Faculty of Computer Science and Engineering Hodeidah University Al Hudaydah Yemen

ISBN: (纸本)9789813368347

Due to the significant ongoing expansion of computer networks in our lives nowadays, the demand for network security and protection from cyber-attacks has never been more imperative to either clients or businesses alike, which signifies the key role of cyber intrusion detection systems in network security. This article proposes a cyber-intrusion detecting system classification with MLP trained by a hybrid metaheuristic algorithm and feature selection based on multi-objective wrapper method. The classifier, named as HADMLP is trained using a hybridization of the artificial bee colony along with the dragonfly algorithm. A multi-objective artificial bee colony model which is wrapper-based is used for selection of feature. Hence, collective name of the proposed technique referred as MO-HADMLP. For performance evaluation, the proposed method was assessed using ISCX 2012 and KDD CUP 99 datasets. The results of our experiments indicate a significant enhancement to the efficacy of network intrusion detection when compared to other approaches. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Multiobjective optimization

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Design and demonstration of an operating system for executing applications on quantum network nodes

arXiv

引用

arXiv 2024年

作者： Donne, Carlo Delle Iuliano, Mariagrazia van der Vecht, Bart Ferreira, Guilherme M. Jirovská, Hana van der Steenhoven, Thom J.W. Dahlberg, Axel Skrzypczyk, Matt Fioretto, Dario Teller, Markus Filippov, Pavel Montblanch, Alejandro R.-P. Fischer, Julius van Ommen, H. Benjamin Demetriou, Nicolas Leichtle, Dominik Music, Luka Ollivier, Harold te Raa, Ingmar Kozlowski, Wojciech Taminiau, Tim H. Pawelczak, Przemyslaw Northup, Tracy E. Hanson, Ronald Wehner, Stephanie QuTech Kavli Institute of Nanoscience Delft University of Technology Delft2628 CJ Netherlands Quantum Computer Science Department of Software Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 XE Netherlands Embedded Systems Department of Software Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 XE Netherlands Institut für Experimentalphysik Universität Innsbruck Technikerstraße 25 Innsbruck6020 Austria QAT DIENS Ecole Normale Supérieure PSL University CNRS INRIA. 45 rue d’Ulm Paris75005 France LIP6 CNRS Sorbonne Université 4 Place Jussieu Paris75005 France

The goal of future quantum networks is to enable new internet applications that are impossible to achieve using solely classical communication[1, 2, 3]. Up to now, demonstrations of quantum network applications[4, 5, 6] and functionalities[7, 8, 9, 10, 11, 12] on quantum processors have been performed in ad-hoc software that was specific to the experimental setup, programmed to perform one single task (the application experiment) directly into low-level control devices using expertise in experimental physics. Here, we report on the design and implementation of the first architecture capable of executing quantum network applications on quantum processors in platform-independent high-level software. We demonstrate the architecture’s capability to execute applications in high-level software, by implementing it as a quantum network operating system – QNodeOS – and executing test programs including a delegated computation from a client to a server[13] on two quantum network nodes based on nitrogen-vacancy (NV) centers in diamond[14, 15]. We show how our architecture allows us to maximize the use of quantum network hardware, by multitasking different applications on a quantum network for the first time. Our architecture can be used to execute programs on any quantum processor platform corresponding to our system model, which we illustrate by demonstrating an additional driver for QNodeOS for a trapped-ion quantum network node based on a single 40Ca+atom[16]. Our architecture lays the groundwork for computer science research in the domain of quantum network programming, and paves the way for the development of software that can bring quantum network technology to society. Copyright © 2024, The Authors. All rights reserved.

关键词： Trapped ions

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software Development in Startup Companies: The Greenfield Startup Model

arXiv

引用

arXiv 2023年

作者： Giardino, Carmine Paternoster, Nicolò Unterkalmsteiner, Michael Gorschek, Tony Abrahamsson, Pekka The Faculty of Computer Science Free University of Bolzano/Bozen Dominikanerplatz 3 Bozen Bolzano39100 Italy The Software Engineering Research Lab Sweden Blekinge Institute of Technology Campus Gräsvik Karlskrona371 79 Sweden The Department of Computer and Information Science Norwegian University of Science and Technology Ntnu Sem Sælandsvei 7-9 Trondheim7491 Norway

software startups are newly created companies with no operating history and oriented towards producing cutting-edge products. However, despite the increasing importance of startups in the economy, few scientific studies attempt to address software engineering issues, especially for early-stage startups. If anything, startups need engineering practices of the same level or better than those of larger companies, as their time and resources are more scarce, and one failed project can put them out of business. In this study we aim to improve understanding of the software development strategies employed by startups. We performed this state-of-practice investigation using a grounded theory approach. We packaged the results in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible. This strategy allows startups to verify product and market fit, and to adjust the product trajectory according to early collected user feedback. The need to shorten time-to-market, by speeding up the development through low-precision engineering activities, is counterbalanced by the need to restructure the product before targeting further growth. The resulting implications of the GSM outline challenges and gaps, pointing out opportunities for future research to develop and validate engineering practices in the startup context. © 2023, CC BY-NC-SA.

关键词： Precision engineering

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Method for filtering encrypted traffic using a neural network between an Industrial Internet of things system and Digital Twin 21

Method for filtering encrypted traffic using a neural networ...

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Proceedings of the 5th International Conference on Future Networks and Distributed Systems

作者： Ivan Luksha Truong Duy Dinh Evgenii Karelin Ruslan Glushakov Ruslan Kirichek Dept. of software engineering and computer science Bonch-Bruevich Saint Petersburg State University of Telecommunications Russian Federation Posts and Telecommunications Institute of Technology Faculty of Information Vietnam Dept. of software engineering and computer science The Bonch-Bruevich Saint Petersburg State University of Telecommunications Russian Federation Saint-Petersburg State Pediatric Medical University Russian Federation The Bonch-Bruevich Saint Petersburg State University of Telecommunications Dept. of software engineering and computer science Russian Federation

ISBN: (纸本)9781450387347

Several traffic optimization approaches are available nowadays, including compression, packet deduplication, specialized hardware and software solutions, application optimization, and neural network utilization. However, the inclination to approach data to consumers and transfer data to the periphery necessitates the employment of novel (perhaps combining the use of known) ways to handle the problem, while keeping in mind that most traffic is encrypted, and the proposed solution should be “transparent” to end-users. The article presents a technique for isolating encrypted IoT traffic, and a study of its effectiveness using a neural network in encrypted SSL sessions has been carried out.

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