MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)最新文献_第9页

NDN Experimental Evaluation in Multi-Domain Tactical Environments 多域战术环境下NDN实验评估

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) Pub Date : 2022-11-28 DOI: 10.1109/MILCOM55135.2022.10017463

Lorenzo Campioni, Bastiaan Wissingh, M. Tortonesi, Niranjan Suri, C. Stefanelli

{"title":"NDN Experimental Evaluation in Multi-Domain Tactical Environments","authors":"Lorenzo Campioni, Bastiaan Wissingh, M. Tortonesi, Niranjan Suri, C. Stefanelli","doi":"10.1109/MILCOM55135.2022.10017463","DOIUrl":"https://doi.org/10.1109/MILCOM55135.2022.10017463","url":null,"abstract":"The characteristics of tactical network environments pose a severe challenge to information sharing. In particular, the Distributed, Intermittent, and Limited (DIL) nature of these networks require specifically designed communication protocols capable of efficiently exploiting the scarce network resources to offer reliable communication. While IP-based protocols have been widely adopted in this context, implementations of the Information Centric Networking (ICN) paradigm represent promising novel approaches to tactical networks thanks to their natural support for in-network caching and their information-oriented architecture. In particular, the Named-Data Networking (NDN) design injects novel ideas to manage channel heterogeneity and multi-homed nodes, while providing easy and enabling cache-and-forwarding mechanisms as well as other mechanisms to tailor its behaviour to a variety of different network environments. With this paper we extend our previous coarse-grained evaluation of NDN within tactical edge networks conducted within the NATO group IST-161 RTG by introducing a more sophisticated network environment and defining two ad-hoc mechanisms to improve the protocol effectiveness and our test harness.","PeriodicalId":239804,"journal":{"name":"MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115914570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Monitoring for Analytics Placement in Tactical Networks 战术网络中分析放置的自适应监控

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) Pub Date : 2022-11-28 DOI: 10.1109/MILCOM55135.2022.10017733

J. Corcoran, Eric Graves, B. Dawson, M. Dwyer, Paul Yu, Kevin S. Chan

引用次数: 0

Sum-Capacity Achieving Schemes of a 2-User Gaussian Multiple-Access Channel with 1-bit ADC 基于1位ADC的2用户高斯多址信道和容量实现方案

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) Pub Date : 2022-11-28 DOI: 10.1109/MILCOM55135.2022.10017986

Sejuti Banik, Md Hasan Rahman, M. Ranjbar, N. Tran, K. Pham

{"title":"Sum-Capacity Achieving Schemes of a 2-User Gaussian Multiple-Access Channel with 1-bit ADC","authors":"Sejuti Banik, Md Hasan Rahman, M. Ranjbar, N. Tran, K. Pham","doi":"10.1109/MILCOM55135.2022.10017986","DOIUrl":"https://doi.org/10.1109/MILCOM55135.2022.10017986","url":null,"abstract":"In this paper, we investigate the fundamentals of a static 2-user Gaussian multiple-access channel (MAC) with 1-bit analog-to-digital-converter (ADC) being equipped at the base station. To shed new light on the characteristics of sum-capacity achieving schemes, we first consider the 1-bit MAC as a single-user channel that is affected by additive white Gaussian noise (AWGN) and a fixed yet unknown interference from the other user. By examining the Kuhn-Tucker condition (KTC) for an input signal to be optimal, we demonstrate that the capacity-achieving signal of this single-user channel must have a bounded amplitude. Based on this characteristic, Dubin's theorem on extreme points of convex sets is exploited to show that the sum-capacity achieving signals of the considered MAC are discrete, with each signal having at most five mass points. In the case of equal power allocation between the two users, we establish an upper bound on the total sum-rate. We then show that the upper bound is achievable by a simple scheme in which the first user employs binary phase shift keying (BPSK) while the second user uses π/2-BPSK. Therefore, this scheme achieves one of the optimal points in the capacity region of the static 2-user 1-bit MAC. Our results show that the proposed simple scheme greatly outperforms PSK-based signaling schemes that are sum-capacity achieving in the fading 2-user 1-bit MAC.","PeriodicalId":239804,"journal":{"name":"MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131062128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Precoding for Security Gap Physical Layer Security in Multiuser MIMO Satellite Systems 多用户MIMO卫星系统安全缺口物理层安全预编码

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) Pub Date : 2022-11-28 DOI: 10.1109/MILCOM55135.2022.10017639

Matthias G. Schraml, A. Knopp

引用次数: 0

Orchestration of Reconfigurable Intelligent Surfaces for Positioning, Navigation, and Timing 用于定位、导航和定时的可重构智能表面编排

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) Pub Date : 2022-11-28 DOI: 10.1109/MILCOM55135.2022.10017665

Md. Sadman Siraj, Aisha B. Rahman, Maria Diamanti, Eirini-Eleni Tsiropoulou, S. Papavassiliou, J. Plusquellic

{"title":"Orchestration of Reconfigurable Intelligent Surfaces for Positioning, Navigation, and Timing","authors":"Md. Sadman Siraj, Aisha B. Rahman, Maria Diamanti, Eirini-Eleni Tsiropoulou, S. Papavassiliou, J. Plusquellic","doi":"10.1109/MILCOM55135.2022.10017665","DOIUrl":"https://doi.org/10.1109/MILCOM55135.2022.10017665","url":null,"abstract":"Positioning, Navigation, and Timing (PNT) services are exploited by critical infrastructures which are strategic for the functioning of the modern society, such as telecom, energy, finance, and transportation. Though the most popular PNT services' provider is the Global Positioning System (GPS), its performance is often impacted by adverse conditions and different varieties of interference, either intentional or unintentional. In this paper, we exploit the efficient and effective orchestration of Reconfigurable Intelligence Surfaces (RISs) as a means of offering an alternative PNT model, improving accuracy and availability. In particular, we initially introduce a low-complexity reinforcement learning-based approach to enable the various targets under consideration to select the most appropriate set of RISs that, acting complementary to available anchor nodes, will minimize the error in the targets' positioning and timing calculation. Subsequently, the optimal phase shifts of the reflected signals on the selected RISs are determined, in order to further improve the proposed PNT model's accuracy. Finally, an iterative least square (ILS) algorithm determines the targets' positioning and timing in a fully distributed manner. The performance of the proposed PNT model is achieved via modeling and simulation, and indicative numerical results are presented demonstrating its benefits and tradeoffs.","PeriodicalId":239804,"journal":{"name":"MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)","volume":"84 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130686277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Machine Learning-Based Frequency Bands Classification for Efficient Frequency Hopping Spread Spectrum Applications 基于机器学习的高效跳频扩频频段分类

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) Pub Date : 2022-11-28 DOI: 10.1109/MILCOM55135.2022.10017912

Inna Valieva, B. Shashidhar, M. Björkman, J. Åkerberg, Mikael Ekström, I. Voitenko

{"title":"Machine Learning-Based Frequency Bands Classification for Efficient Frequency Hopping Spread Spectrum Applications","authors":"Inna Valieva, B. Shashidhar, M. Björkman, J. Åkerberg, Mikael Ekström, I. Voitenko","doi":"10.1109/MILCOM55135.2022.10017912","DOIUrl":"https://doi.org/10.1109/MILCOM55135.2022.10017912","url":null,"abstract":"This paper is focused on the performance evaluation of nine supervised machine learning algorithms in terms of classification accuracy applied to perform two radio scene analysis tasks: 1. blind binary frequency band occupancy classification: vacant or occupied; 2. interference type classification: sine wave interference, or modulated signal or additive white Gaussian noise (AWGN) for the frequency hopping spread spectrum cognitive radio application. Twenty-nine features derived from the time-, frequency-domain and RSSI, have been used as classification inputs to the evaluated machine learning classifiers. Classifiers training and validation have been performed offline in Matlab Classification Learner and Neural Networks applications using four data sets, generated in the controlled experiment, covering both classification tasks in AWGN and mixed channel propagation conditions (AWGN and Rician fading). Data samples have been generated using a hardware signal generator and recorded on the target application receivers' front end as the time-domain complex signals. The highest classification accuracy of 98.71 % has been demonstrated by Feed Forward Neural Network (FFNN) for the binary occupancy classification in K-fold validation for the mixed data set containing both AWGN and Rician fading channel samples. For the interference type classification, FFNN has demonstrated classification accuracy of 99.82 % for K-fold validation and 99.71 % for hold-out validation. FFNN has been concluded as an acceptable algorithm for further adaptation and embedded deployment on our target radio application for both binary classification between occupied or vacant frequency bands and interference type classification.","PeriodicalId":239804,"journal":{"name":"MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126879720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Security Reassessing in UAV-Assisted Cyber-Physical Systems Based on Federated Learning 基于联邦学习的无人机辅助网络物理系统安全再评估

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) Pub Date : 2022-11-28 DOI: 10.1109/MILCOM55135.2022.10017672

Prakhar Consul, Ishan Budhiraja, Rajat Chaudhary, Neeraj Kumar

{"title":"Security Reassessing in UAV-Assisted Cyber-Physical Systems Based on Federated Learning","authors":"Prakhar Consul, Ishan Budhiraja, Rajat Chaudhary, Neeraj Kumar","doi":"10.1109/MILCOM55135.2022.10017672","DOIUrl":"https://doi.org/10.1109/MILCOM55135.2022.10017672","url":null,"abstract":"Mobile-edge computing (MEC) is a popular method for increasing the quality of computing experience for consumers since it allows them to offload computing operations to MEC servers, which have significant processing capabilities. However, safety and information security are major challenges that must be addressed. We employ Federated Learning-based Cyber-Physical Systems (CPS) to address safety and information security in MEC systems, which offers data accuracy and un-sustainability. Security of UAV assisted CPS against cyber-attacks yet an another challenging problem. Because most cyber-attacks occur in unpredictable ways, it is difficult to define them in a structured manner. Instead of developing a unique cyber-attack model, we focus on exploring the dynamic behavior of the system to cyber-attacks throughout this article. Attacks that repeat themselves by interfering with system components or data are insignificant if they can be quickly identified by the system's control mechanism. Intelligent cyber attackers remain undetected by the tracking system by carefully designing cyber-attacks. Our primary goal is to examine the effectiveness of such cyberattacks from the aspect of the CPS and overcome them using Federated Learning (FL).","PeriodicalId":239804,"journal":{"name":"MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121622002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Analysis of Vulnerabilities in Satellite Software Bus Network Architecture 卫星软件总线网络体系结构漏洞分析

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) Pub Date : 2022-11-28 DOI: 10.1109/MILCOM55135.2022.10017967

Adrian Schalk, Luke Brodnik, Dane Brown

{"title":"Analysis of Vulnerabilities in Satellite Software Bus Network Architecture","authors":"Adrian Schalk, Luke Brodnik, Dane Brown","doi":"10.1109/MILCOM55135.2022.10017967","DOIUrl":"https://doi.org/10.1109/MILCOM55135.2022.10017967","url":null,"abstract":"With the rapid expansion of the space industry, there has been a strong push to develop simple, reusable, and easy to deploy satellite system architecture solutions. The space industry may have assumed that the complexity of their systems of systems would make the vulnerability discovery process too difficult for attackers. However, focused research into the design of modern Software-Bus (SB) dependent satellite systems has the ability to reveal numerous vulnerabilities in deployed space system architectures. In particular, our in-depth analysis of NASA's open source core Flight System (cFS) resulted not only in the discovery of various novel vulnerabilities, but also the implementation of several straight-forward, practical exploits. Due to the lack of authentication required to execute commands via the SB as well as the inability to recover from an attack in a robust manner, cFS is vulnerable to a number of attacks through the SB entry point. This paper presents four exploit demonstrations on the unsecured cFS bus architecture, and then provides recommendations on how to secure against these attacks and make a modern satellite system architecture more robust.","PeriodicalId":239804,"journal":{"name":"MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125294101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Joint Beam Management and Relay Selection Using Deep Reinforcement Learning for MmWave UAV Relay Networks 基于深度强化学习的毫米波无人机中继网络联合波束管理和中继选择

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) Pub Date : 2022-11-28 DOI: 10.1109/MILCOM55135.2022.10017754

Dohyun Kim, Miguel R. Castellanos, R. Heath

引用次数: 2

Context-aware Collaborative Neuro-Symbolic Inference in IoBTs 情境感知协同神经符号推理在iobt中的应用

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) Pub Date : 2022-11-28 DOI: 10.1109/MILCOM55135.2022.10017607

T. Abdelzaher, Nathaniel D. Bastian, Susmit Jha, L. Kaplan, Mani Srivastava, V. Veeravalli

{"title":"Context-aware Collaborative Neuro-Symbolic Inference in IoBTs","authors":"T. Abdelzaher, Nathaniel D. Bastian, Susmit Jha, L. Kaplan, Mani Srivastava, V. Veeravalli","doi":"10.1109/MILCOM55135.2022.10017607","DOIUrl":"https://doi.org/10.1109/MILCOM55135.2022.10017607","url":null,"abstract":"IoBTs must feature collaborative, context-aware, multi-modal fusion for real-time, robust decision-making in adversarial environments. The integration of machine learning (ML) models into IoBTs has been successful at solving these problems at a small scale (e.g., AiTR), but state-of-the-art ML models grow exponentially with increasing temporal and spatial scale of modeled phenomena, and can thus become brittle, untrustworthy, and vulnerable when interpreting large-scale tactical edge data. To address this challenge, we need to develop principles and methodologies for uncertainty-quantified neuro-symbolic ML, where learning and inference exploit symbolic knowledge and reasoning, in addition to, multi-modal and multi-vantage sensor data. The approach features integrated neuro-symbolic inference, where symbolic context is used by deep learning, and deep learning models provide atomic concepts for symbolic reasoning. The incorporation of high-level symbolic reasoning improves data efficiency during training and makes inference more robust, interpretable, and resource-efficient. In this paper, we identify the key challenges in developing context-aware collaborative neuro-symbolic inference in IoBTs and review some recent progress in addressing these gaps.","PeriodicalId":239804,"journal":{"name":"MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124319350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2