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Fundamental Limits of Multiple-Access Integrated Sensing and Communication Systems

IEEE Transactions on Information Theory 2025年第6期71卷 4317-4341页

作者： Liu, Yao Li, Min Liu, An Ong, Lawrence Yener, Aylin Zhejiang University College of Information Science and Electronic Engineering Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China University of Newcastle School of Engineering CallaghanNSW2308 Australia The Ohio State University Department of Electrical and Computer Engineering ColumbusOH43210 United States

A state-dependent discrete memoryless multiple access channel is considered to model an integrated sensing and communication system, where two transmitters wish to convey messages to a receiver while simultaneously estimating the state parameter sequences through echo signals. In particular, the sensing state parameters are assumed to be correlated with the channel state. In this setup, improved inner and outer bounds for capacity-distortion region are derived. The inner bound is based on an achievable scheme that combines message cooperation and joint compression of past transmitted codewords and echo signals at each transmitter, resulting in unified cooperative communication and sensing. The outer bound is based on the ideas of dependence balance for communication rate, genie-aided state estimator and rate-limited constraints on sensing distortion. The proposed inner and outer bounds are proved to improve the state-of-the-art bounds. Finally, numerical examples are provided to demonstrate that our new inner and outer bounds strictly improve the existing results. © 1963-2012 IEEE.

关键词： Signal distortion

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Machine learning based fileless malware traffic classification using image visualization

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Cybersecurity 2024年第4期7卷 1-18页

作者： Fikirte Ayalke Demmese Ajaya Neupane Sajad Khorsandroo May Wang Kaushik Roy Yu Fu Department of Computer Science College of EngineeringNorth Carolina A&T State University1601 E Market StGreensboroNC 27411USA Palo Alto Networks Inc.3000 Tannery WaySanta ClaraCA 95054USA

In today's interconnected world,network traffic is replete with adversarial *** technology evolves,these attacks are also becoming increasingly sophisticated,making them even harder to ***,artificial intelli-gence(Al)and,specifically machine learning(ML),have shown great success in fast and accurate detection,classifica-tion,and even analysis of such ***,there is a growing body of literature addressing how subfields of Al/ML(e.g.,natural language processing(NLP))are getting leveraged to accurately detect evasive malicious patterns in network *** this paper,we delve into the current advancements in ML-based network traffic classification using image *** a rigorous experimental methodology,we first explore the process of network traffic to image ***,we investigate how machine learning techniques can effectively leverage image visualization to accurately classify evasive malicious traces within network *** the utilization of production-level tools and utilities in realistic experiments,our proposed solution achieves an impressive accuracy rate of 99.48%in detecting fileless malware,which is widely regarded as one of the most elusive classes of malicious software.

关键词： Network security Traffic classification Fileless malware Image visualization Machine learning Intrusion

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Pravega: Performance impact analysis with Connection Pooling

Pravega: Performance impact analysis with Connection Pooling

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2024 International Conference on Knowledge engineering and Communication Systems, ICKECS 2024

作者： Ramesh, K.V. Raju, G.T. Visvesvaraya Technological University Airspan Networks Belagavi India SJC Institute of Technology Visvesvaraya Technological University Department of Computer Science and Engineering Belagavi India

ISBN: (纸本)9798350359688

In this paper we perform analysis on Pravega distributed streaming storage with and without connection pooling. When connection pooling is enabled, there will be a restriction of number of open connections for data transfer with Pravega cluster. Storage Benchmarking Kit is used to pump data of various sizes to the Pravega cluster running as docker containers with and without enabling connection pooling. The performance numbers are captured in CSV files which are then fed to sbk-charts which will produce simple charts which can be used for detailed analysis of each tests performed. All the tests are performed on two EC2 instances of type *** on AWS Cloud infrastructure. Performance impacts are analysed with the generated charts for each test result which leads us to conclude on the performance gap when applying connection pooling during client applications integrations with Pravega server. © 2024 IEEE.

关键词： Flowcharting

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Optimization of Cube Storage Warehouse Scheduling Using Genetic Algorithms 19

Optimization of Cube Storage Warehouse Scheduling Using Gene...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Ha, Won Yong Jiang, Zhong-Ping Tandon School of Engineering New York University The Control and Networks Lab Department of Electrical and Computer Engineering BrooklynNY11201 United States

ISBN: (纸本)9798350320695

In this paper, a new scheduling model is presented to speed up the logistics processing in an automatic cube storage warehouse. Automated guided vehicles (AGV) are used to move all items in the warehouse according to the computer's instructions. The tasks to be performed by the AGV are optimally distributed using Genetic Algorithms (GA). The goal of our research is to optimize order scheduling in automatic warehouses to reduce human resources and lower the cost of logistics. The proposed GA's fitness function reflects removing the stacked bin, a cube storage warehouse characteristic, and getting the designated bin. Through extensive computer simulations, it is shown that the higher the generation of the GA we design, the lower the logistics processing time. As compared with other meta-heuristic optimization algorithms, our proposed GA algorithm demonstrates a maximum of 21% reduction in delivery time. © 2023 IEEE.

关键词： Genetic algorithms

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Adaptive Defense Mechanisms Against Zero-Day Attacks in Wireless Sensor networks

Adaptive Defense Mechanisms Against Zero-Day Attacks in Wire...

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2024 International Conference on Distributed Systems, computer networks and Cybersecurity, ICDSCNC 2024

作者： Chaturvedi, Abhay Kukreti, Sanjeev Durga Bhavani, A. Nizampatnam, Venkata Naga Ravi Kiran Kaur, Davinder Natrayan, L. Gla University Department of Electronics & Communication Engineering Chaumuhan India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India Bms Institute of Technology and Management Department of Computer Science and Engineering Bengaluru India Expert Network Security Engineer Acxiom Llc Department of Computer Networks AustinTX United States Symbiosis Law School Department of Law Pune India Saveetha School of Engineering Simats Department of Mechanical Engineering Kuthambakkam India

ISBN: (纸本)9798350375442

Important fields including healthcare, environmental monitoring, and military operations are seeing a rise in the use of wireless sensor networks (WSNs). But they are susceptible to complex cyber dangers, especially zero-day assaults, due to their dispersed nature and lack of resources. In order to protect WSNs against zero-day attacks, this research introduces an Adaptive Defense Mechanism (ADM). A dynamic response system that can adjust to changing attack patterns in real-time is integrated with machine learning-based anomaly detection in the proposed ADM. A hybrid model integrating Support Vector Machines (SVM) and Long Short-Term Memory (LSTM) networks is used by the anomaly detection module. It achieves a detection accuracy of 94.7% on simulated zero-day assault scenarios. In comparison to static defensive systems, the ADM's adaptive response mechanism, which is based on reinforcement learning, dynamically modifies the network's security regulations, resulting in a 23.5% reduction in false positives. Results from testing the proposed ADM in a simulated WSN setting show that it can greatly improve the network's ability to withstand zero-day assaults. With assaults present, the total network throughput increased by 15% and the average detection time dropped to 0.35 seconds. Based on these findings, the ADM provides a strong and effective defensive technique, guaranteeing the safety and dependability of WSNs in mission-critical applications. © 2024 IEEE.

关键词： Zero-day attack

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A Robust Speech Encryption Method Using Segmentation and Chaotic Keys for Enhanced Audio Security 3rd

A Robust Speech Encryption Method Using Segmentation and Ch...

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3rd International Conference on Advances in Computing Research, ACR 2025

作者： Abu-Faraj, Mua’ad Al-Hyari, Abeer Alqadi, Ziad Department of Computer Information Systems The University of Jordan Aqaba77110 Jordan Department of Electrical Engineering Al-Balqa Applied University As Salt19117 Jordan Department of Computers and Networks Engineering Al-Balqa Applied University Amman15008 Jordan

ISBN: (纸本)9783031876462

This paper presents an innovative method for safeguarding audio files. The proposed technique leverages an advanced primary key with a complex structure, offering a vast keyspace resistant to hacking. The private key includes details for segmenting the speech audio file and generating unique chaotic keys for encryption. These keys are extremely sensitive to minor changes in the primary key, flagging any slight alteration during decryption as a hacking attempt. The method is tested and implemented on various speech signals, with the results analyzed to highlight the main features and improvements. The findings demonstrate how the technique improves encryption and decryption by optimizing metrics such as MSE, PSNR, CC, and NSCR. Speed analysis verifies the method’s performance by maximizing the throughput of the speech cryptography process. The results are compared with existing approaches to show the superiority and enhancements provided. This method is straightforward to implement, as it does not require modifying the algorithm when altering the speech audio file or the private key, making it a versatile solution for various speech encryption needs. This research is highly relevant to network security, as it ensures the integrity and confidentiality of transmitted speech signals, preventing unauthorized access and improving overall communication security. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Speech enhancement

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Distributed Throughput and Energy Efficient Resource Optimization When D2D and Massive MIMO Coexist

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Journal of Communications and Information networks 2022年第3期7卷 278-295页

作者： Abi Abate Dejen Yihenew Wondie Anna Forster Sustainable Communication Networks Department Universitat BremenBremen 28195Germany School of Electrical and Computer Engineering Addis Ababa UniversityAddis Ababa 999047Ethiopia

Fifth generation(5G)cellular networks intend to overcome the challenging demands posed by dynamic service quality requirements,which are not achieved by single network *** future cellular networks require efficient resource allocation and power control schemes that meet throughput and energy efficiency requirements when multiple technologies coexist and share network *** this paper,we optimize the throughput and energy efficiency(EE)performance for the coexistence of two technologies that have been identified for the future cellular networks,namely,massive multiple-input multiple-output(MIMO)and network-assisted device-to-device(D2D)*** such a hybrid network,the co/cross-tier interferences between cellular and D2D communications caused by spectrum sharing is a significant *** this end,we formulate the average sum rate and EE optimization problem as mixed-integer non-linear programming(MINLP).We develop distributed resource allocation algorithms based on matching theory to alleviate interferences and optimize network *** is shown in this paper that the proposed algorithms converge to a stable matching and terminate after finite *** simulation results show that the proposed algorithms achieved more than 88%of the average transmission rate and 86%of the energy efficiency performance of the optimal matching with lower complexity.

关键词： device-to-device(D2D) massive MIMO communication interference management resource optimization

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Development of an Interface for Digital Neuromorphic Hardware Based on an FPGA

Development of an Interface for Digital Neuromorphic Hardwar...

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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, International Conference on Maintenance engineering, IncoME-V 2023, International conference on the Efficiency and Performance engineering Network, TEPEN 2023

作者： Harmann, René Sohlbach, Lukas Perez-Peña, Fernando Schmidt, Karsten Department of Computer Science and Engineering Frankfurt University of Applied Sciences Nibelungenplatz 1 Frankfurt60318 Germany Department of Automation Electronics and Computer Architecture and Networks School of Engineering University of Cadiz Avda. de la Universidad 10 Puerto Real11519 Spain

ISBN: (纸本)9783031494208

Exploring and understanding the functioning of the human brain is one of the greatest challenges for current research. Neuromorphic engineering tries to address this challenge by abstracting biological mechanisms and translating them into technology. Via the abstraction process and experiments with the resulting technical system, an attempt is made to obtain information about the biological counterpart. One subsection of Neuromorphic engineering (NE) is Spiking Neural networks (SNN), which describe the structures of the human brain more and more closely than Artificial Neural networks (ANN). Together with their dedicated hardware, SNNs provide a good platform for developing new algorithms for information processing. In the context of these neuromorphic hardware platforms, this paper aims to develop an interface for a digital hardware platform (SPINN-3 Development Board) to enable the use of industrial or conventional sensors and thus create new approaches for experimental research. The basis for this endeavor is a Field Programmable Gate Array (FPGA), which is placed as a gateway between the sensors and the neuromorphic hardware. Overall, the developed system provides a robust solution for a wide variety of investigations related to neuromorphic hardware and SNNs. Furthermore, the solution also offers suitable possibilities to monitor all processes within the system in order to obtain suitable measurements, which can be examined in search of meaningful results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Neural networks

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5G Smart Mobility Management Based Fuzzy Logic Controller Unit

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computers, Materials & Continua 2022年第6期71卷 4941-4953页

作者： Chafaa Hamrouni Slim Chaoui Taif University-Khurma Univ.College-Department of Computer Sciences Khurma2935Kingdom of Saudi Arabia College of Computer and Information Sciences Dep.of Computer Engineering and NetworksJouf UniversitySkakaK.S.A

In the paper,we propose a fuzzy logic controller system to be implemented for smart mobility management in the 5G wireless communication *** management is considered as a main issue for all-IP mobile networks future *** a network-based mobility management protocol,Internet engineering Task Force developed the Proxy Mobile IPv6(PMIPv6)in order to support the mobility of IP devices,and many other results were presented to reduce latency handover and the amount of PMIPv6 signaling,but it is not enough for the application needs in *** present paper describes an approach based on the IEEE 802.21 Media Independent Handover(MIH)standard and PMIPv6,so we present a new vertical handover algorithm for anticipating handover process *** object is to propose a smart mobility management that contribute in 5G wireless communication system network operating *** proposed dynamic thresholds were successfully made to guaranty process triggering,and a new primitive MIH is proposed for signaling a needed handover to be *** results demonstrate a significant reduction of the handover delay,packet loss,handover blocking probability and signaling *** results and tests are accomplished.

关键词： 5G proxy mobile IPv6 media independent handover wireless system QoS LTE HDM

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Hardware considerations of a DSP based wireless coded receiver under limited resources

Hardware considerations of a DSP based wireless coded receiv...

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2022 International Conference on Intelligent Technology, System and Service for Internet of Everything, ITSS-IoE 2022

作者： Abdelkareem, A.E. College of Information Engineering Al-Nahrain University Department of Computer Networks Engineering Baghdad Iraq

ISBN: (数字)9781665459983

ISBN: (纸本)9781665459983

Reliable wireless communication is enabled by adopting advanced Forward Error Correction (FEC) codes, such as Turbo codes. However, the Turbo decoder for real-time communication necessitates accommodating limited resources offered by the DSP processor. This motivates the benchmarking of the Super Harvard Architecture (SHARC) Digital Signal Processor (DSP), which is considered a high flexibility platform. However, implementing turbo code, which is based on the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm on DSP, requires extensive processing time and high memory usage due to its data dependencies. Motivated by this, the hardware considerations to implement a coded receiver under limited memory and processing time are proposed. A memory management strategy that terminates full memory concerns due to the data dependencies of the BCJR is presented. We show that by jointly optimizing the dynamic memory allocation and accessing the external memory, a significant improvement of the available computing resources and lessen the memory requirements. Results showed that the proposed coded receiver requires a memory size of 21 symbol lengths. © 2022 IEEE.

关键词： Digital signal processors

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