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11th International Conference on Advanced computer information Technologies, ACIT 2021

作者： Bisikalo, Oleg Kovtun, Viacheslav Boivan, Olesia Kovtun, Oksana Vinnytsia National Technical University Department of Automation and Intelligent Information Technologies Vinnytsia Ukraine Vinnytsia National Technical University Department of Computer Control Systems Vinnytsia Ukraine Vasyl' Stus Donetsk National University Department of Theory and Practice of Translation Vinnytsia Ukraine

A brand new method of automated transcribing of speech signals of the selected language is represented in the article. In this method, in contrast to the existing ones, the result of transcribing is obtained as a solution of the task of optimization of the functional of relative entropy for each of the sequences of non-intersecting frames, which generalize the samples counts of the sampled speech signal. The method provides an option to improve the quality of transcribing due to personalized pre-setting of the bank of whitening filters on estimating the power spectral density in the target frequency domains of the characteristic phonemes of the selected language. Also on the basis of the proposed method in the first approximation the task of classification of language units of higher levels, in particular, morphemes and lexemes, is set. The adequacy of the proposed mathematical apparatus is proved empirically. © 2021 IEEE.

关键词： Authentication

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Toward Mixture-of-Experts Enabled Trustworthy Semantic Communication for 6G Networks

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IEEE Network 2024年

作者： He, Jiayi Luo, Xiaofeng Kang, Jiawen Du, Hongyang Xiong, Zehui Chen, Ci Niyato, Dusit Shen, Xuemin Guangdong University of Technology School of Automation Guangzhou510006 China Nanyang Technological University College of Computing and Data Science Singapore639798 Singapore Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore487372 Singapore University of Waterloo Department of Electrical and Computer Engineering WaterlooONN2L 3G1 Canada

Semantic Communication (SemCom) plays a pivotal role in 6G networks, offering a viable solution for future efficient communication. Through nonlinear mapping of semantic representations, Deep Learning (DL)-based semantic communications further enhance communication efficiency. However, the vulnerability of DL models to security threats, such as adversarial attacks, poses significant challenges for practical applications of SemCom systems. These vulnerabilities allow attackers to tamper with messages and eavesdrop on private information, especially in wireless communication scenarios. Although existing defenses attempt to address specific threats, they often fail to simultaneously handle multiple heterogeneous attacks. To overcome this limitation, we propose a novel Mixture-of-Experts (MoE)-based SemCom system, comprising a gating network and multiple experts, each specializing in different security challenges. The gating network adaptively selects suitable experts to counter heterogeneous attacks based on user-defined security requirements. Multiple experts collaborate to accomplish semantic communication tasks while meeting the security requirements of users. A case study in vehicular networks demonstrates the efficacy of the MoE-based SemCom system. Simulation results show that the proposed MoE-based SemCom system effectively mitigates concurrent heterogeneous attacks, with minimal impact on downstream task accuracy. © 1986-2012 IEEE.

关键词： Vehicular ad hoc networks

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Spear or Shield: Leveraging Generative AI to Tackle Security Threats of Intelligent Network Services

arXiv

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arXiv 2023年

作者： Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Lam, Kwok-Yan Fang, Yuguang Li, Yonghui School of Computer Science and Engineering Nanyang Technological University Singapore School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore National Centre for Research in Digital Trust School of Computer Science and Engineering Nanyang Technological University Singapore Department of Computer Science City University of Hong Kong Hong Kong School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia

Generative AI (GAI) models have been rapidly advancing, with a wide range of applications including intelligent networks and mobile AI-generated content (AIGC) services. Despite their numerous applications and potential, such models create opportunities for novel security challenges. In this paper, we examine the challenges and opportunities of GAI in the realm of the security of intelligent network AIGC services such as suggesting security policies, acting as both a "spear" for potential attacks and a "shield" as an integral part of various defense mechanisms. First, we present a comprehensive overview of the GAI landscape, highlighting its applications and the techniques underpinning these advancements, especially large language and diffusion models. Then, we investigate the dynamic interplay between GAI’s spear and shield roles, highlighting two primary categories of potential GAI-related attacks and their respective defense strategies within wireless networks. A case study illustrates the impact of GAI defense strategies on energy consumption in an image request scenario under data poisoning attack. Our results show that by employing an AI-optimized diffusion defense mechanism, energy can be reduced by 8.7%, and retransmission count can be decreased from 32 images, without defense, to just 6 images, showcasing the effectiveness of GAI in enhancing network security. © 2023, CC BY.

关键词： Network security

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Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networks

arXiv

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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Shen, Xuemin Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the stochastic nature of diffusion models, the quality and accuracy of the generated content can vary significantly. In wireless edge networks, the transmission of incorrectly generated content may unnecessarily consume network resources. Thus, a dynamic AIGC service provider (ASP) selection scheme is required to enable users to connect to the most suited ASP, improving the users’ satisfaction and quality of generated content. In this article, we first review the AIGC techniques and their applications in wireless networks. We then present the AIGC-as-a-service (AaaS) concept and discuss the challenges in deploying AaaS at the edge networks. Yet, it is essential to have performance metrics to evaluate the accuracy of AIGC services. Thus, we introduce several image-based perceived quality evaluation metrics. Then, we propose a general and effective model to illustrate the relationship between computational resources and user-perceived quality evaluation metrics. To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for the optimal ASP selection. Simulation results show that the proposed algorithm can provide a higher quality of generated content to users and achieve fewer crashed tasks by comparing with four benchmarks, i.e., overloading-avoidance, random, round-robin policies, and the upper-bound schemes. © 2023, CC BY.

关键词： Reinforcement learning

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Capacitor Minimization in Analog Synapses for Efficient and Compact Binarized SNNs

IEEE Transactions on Circuits and Systems for Artificial Int...

引用

IEEE Transactions on Circuits and systems for Artificial Intelligence 2025年第2期2卷 114-125页

作者： Mikail Yayla Ming-Liang Wei Simon Thomann Albi Mema Chia-Lin Yang Jian-Jia Chen Hussam Amrouch Design Automation for Embedded Systems Group TU Dortmund University Dortmund Germany Lamarr Institute for Machine Learning and Artificial Intelligence Dortmund Germany Department of the Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Technical University of Munich (TUM) Munich Germany TUM School of Computation Information and Technology Chair of AI Processor Design Munich Institute of Robotics and Machine Intelligence Munich Germany Department of Computer Science and Information Engineering Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Department of Computer Science TU Dortmund University Dortmund Germany Lamarr Institute Dortmund Germany

Accelerating the immense workloads of Neural Networks (NNs) is a critical challenge, and analog computing-based approaches present a promising solution. Among these, the Integrate-and-Fire (IF) Spiking Neural Network (SNN) stands out for its potential in efficient neural computation. However, achieving high inference accuracy through precise multiply-accumulate (MAC) operations necessitates a large membrane capacitor—224 to 547 times larger than the synapse array at the 14nm technology node—resulting in prohibitive area costs. Additionally, the large capacitor size introduces higher energy consumption and longer access times. Thus, a key research challenge is maintaining accuracy while mitigating the costs associated with the large membrane capacitor. In this work, we propose a HW/SW Codesign method, called CapMin, for capacitor size minimization in analog computing IF-SNNs. CapMin minimizes the capacitor size by reducing the number of spike times needed for accurate operation of the HW, based on the absolute frequency of MAC level occurrences in the SW. To increase the operation of IF-SNNs to current variation, we propose the method CapMin-V, which trades capacitor size for protection based on the reduced capacitor size found in CapMin. In our experiments, CapMin achieves more than a 14 $\times$ reduction in capacitor size along with a 34% reduction in energy consumption over the state of the art, while CapMin-V achieves increased variation tolerance in the IF-SNN operation, requiring only a small increase in capacitor size.

关键词： Capacitors Circuits Accuracy Capacitance Micromechanical devices Costs Neurons Integrated circuit modeling Spiking neural networks Hardware

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information control system for the production of mineral fertilizers in the granulator with a fluidized bed 3

information control system for the production of mineral fer...

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3rd IEEE International Conference on Advanced Trends in information Theory, ATIT 2021

作者： Korniyenko, Bogdan Ladieva, Lesya Galata, Liliya Nesteruk, Andrii Matviichuk-Yudina, Olena Department of information Systems and Technologies National Technical University of Ukraine "igor Sikorsky Kyiv Polytechnic institute" Kyiv Ukraine Department of Hardware and Software Automation National Technical University of Ukraine "igor Sikorsky Kyiv Polytechnic institute" Kyiv Ukraine Department of Computerized information Security Systems National Aviation University Kyiv Ukraine Department of Computer Multimedia Technologies National Aviation University Kyiv Ukraine

ISBN: (纸本)9781665438452

A temperature control information system has been developed to ensure the production of high-quality granules with low moisture content. The study of the granulation and dehydration process, the main factors influencing the production of quality fertilizers, namely: temperature of heating air, temperature of granules, moisture content of granules, viscosity of the binder and its concentration. Based on the mathematical model, the transfer function of the granulator was obtained with the help of the Matlab software package, information control systems based on Pi and PiD controllers were developed, which should output and maintain the temperature of the granules at a given level. Their comparison is made to determine the system that better copes with the task. it is recommended to use a information control system with a PiD regulator in the production, because it allows to reduce the consumption of gas used during the dehydration process, due to the faster achievement of the set temperature of the granules. © 2021 iEEE.

关键词： Quality control

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Digital Twin Aided Predictive Scheduling and Bandwidth Allocation for Multi-Vehicle Cooperative Perception systems

Digital Twin Aided Predictive Scheduling and Bandwidth Alloc...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Binbin Lu Xumin Huang Yuan Wu Liping Qian Dusit Niyato Tony Q. S. Quek Cheng-Zhong Xu State Key Lab of Internet of Things for Smart City Macau China School of Automation Guangdong University of Technology Guangzhou China Zhuhai- UM Science and Technology Research Institute Zhuhai China College of Information Engineering Zhejiang University of Technology Hangzhou China School of Computer Science and Engineering Nangyang Technological University Singapore Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

As an emerging technology, Digital Twin (DT) can provide a virtual presentation of the physical Intelligent Trans-portation systems (ITS) to enhance the applications of ITS such as cooperation perception. In cooperative perception, accurate location is crucial for selecting proper cooperative vehicles (CoVs) to improve the perception performance. However, due to the high mobility of vehicles, the deviation between DT and physical world may lead to non-negligible location errors, which raises the challenges for achieving efficient CoV selection in cooperative perception. In this paper, we propose a DT-empowered multi-vehicle cooperative perception system, in which the CoV selection and bandwidth allocation are jointly optimized to improve the performance of cooperative perception. Specifically, an asyn-chronous federated learning scheme is deployed in DT for location prediction to mitigate the effect of the deviation. Based on the prediction results, the problem of joint predictive scheduling and bandwidth allocation is then formulated as the average delay minimization problem while reaching the required performances. The adaptive CoV selection and bandwidth allocation algorithm based on deep reinforcement learning is proposed to find the optimal scheduling strategy. Simulation results demonstrate that the proposed algorithm achieves the lowest average delay while effectively guaranteeing the performance requirement.

关键词： Vehicular and wireless technologies Federated learning Simulation Optimal scheduling Channel allocation Prediction algorithms Minimization

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Markov Model for Availability Assessment of PLC in Industrial IoT Considering Subsystems Failures

Markov Model for Availability Assessment of PLC in Industria...

引用

IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Maryna Kolisnyk Axel Jantsch Iryna Piskachova Department of computer systems networks and cybersecurity National aerospace university “KhAI” Kharkiv Ukraine Institute of information technologies of Vienna University of Technology “TU Wien” Vienna Austria Department of automation and computer-integrated technologies State Biotechnological University Kharkiv Ukraine

ISBN: (纸本)9798350333053

Large modular programmable logic controllers (PLCs) are the important components of Industrial Internet of Things (IIoT) systems. PLC is a complex system, which consists of different subsystems, each of them can fail, and can lead to the failure of PLC, and to partial failure of IIoT system. In this paper was developed and provided research of a model for assessing the availability and dependability of PLC and its subsystem. The Markov model to describe the states and potential state transitions for the PLC in an IIoT environment was developed and investigated. The results of simulation of Markov model of PLC availability were analyzed, and obtained the probabilities of PLC's subsystems states.

关键词： Analytical models Programmable logic devices Markov processes Probability Mathematical models Data models Reliability

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

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computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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A Subspace-Based Non-Dominated Subset Selection Method

A Subspace-Based Non-Dominated Subset Selection Method

引用

Congress on Evolutionary Computation

作者： Qingshan Tan Changhe Li Sanyou Zeng Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

Environmental selection is an important process in multi-objective evolutionary algorithms (MOEAs). As the evolution progresses, the number of non-dominated solutions increases. This paper is focused on selecting a subset from excess non-dominated solutions for evolutionary or the final output. However, traditional selection methods in classical MOEAs encounter difficulties when dealing with candidate solutions that possess irregular topologies. Although the distance-based subset selection methods are not sensitive to the topologies of the candidate points, they have significant room for reducing computational complexity. In order to address the above issues, a subspace selection method is proposed in this paper. It partitions the objective space into multiple subspaces that have comparable volumes and shapes. The maximal minimum distance of each solution is considered to ensure that the sparsest solution is always chosen first. To save computational costs, only the solutions in the neighboring subspaces are taken into account. The experimental results demonstrate that the proposed subspace selection method outperforms classical selection methods in solving problems with various shapes of the Pareto front.

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