2022 IEEE International Symposium on Technologies for Homeland Security (HST)最新文献_第3页

Multiuser, multimodal sensemaking cognitive immersive environment with a task-oriented dialog system 多用户，多模态语义认知沉浸式环境与面向任务的对话系统

2022 IEEE International Symposium on Technologies for Homeland Security (HST) Pub Date : 2022-11-14 DOI: 10.1109/HST56032.2022.10025454

Shannon Briggs, Samuel Chabot, Abraham Sanders, Matthew Peveler, T. Strzalkowski, J. Braasch

{"title":"Multiuser, multimodal sensemaking cognitive immersive environment with a task-oriented dialog system","authors":"Shannon Briggs, Samuel Chabot, Abraham Sanders, Matthew Peveler, T. Strzalkowski, J. Braasch","doi":"10.1109/HST56032.2022.10025454","DOIUrl":"https://doi.org/10.1109/HST56032.2022.10025454","url":null,"abstract":"This paper is a conceptual paper that explores how the sensemaking process by intelligence analysts completed within a cognitive immersive environment might be impacted by the inclusion of a progressive dialog system. The tools enabled in the sensemaking room (a specific instance within the cognitive immersive environment) were informed by tools from the intelligence analysis domain. We explore how a progressive dialog system would impact the use of tools such as the collaborative brainstorming exercise [1]. These structured analytic techniques are well established in intelligence analysis training literature, and act as ways to access the intended users' cognitive schema as they use the cognitive immersive room and move through the sensemaking process. A prior user study determined that the sensemaking room encouraged users to be more concise and representative with information while using the digital brainstorming tool. We anticipate that addition of the progressive dialog function will enable a more cohesive link between information foraging and sensemaking behaviors for analysts.","PeriodicalId":162426,"journal":{"name":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130240241","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

Analysis of the Effects of Wavelength Band Selection and Data Fusion Techniques on Multiple-Modality Homeland Security Airborne Scenes via Deep Learning Models 基于深度学习模型的波段选择和数据融合技术对多模态国土安全机载场景的影响分析

2022 IEEE International Symposium on Technologies for Homeland Security (HST) Pub Date : 2022-11-14 DOI: 10.1109/HST56032.2022.10025446

Christopher D. Good, D. B. Megherbi

{"title":"Analysis of the Effects of Wavelength Band Selection and Data Fusion Techniques on Multiple-Modality Homeland Security Airborne Scenes via Deep Learning Models","authors":"Christopher D. Good, D. B. Megherbi","doi":"10.1109/HST56032.2022.10025446","DOIUrl":"https://doi.org/10.1109/HST56032.2022.10025446","url":null,"abstract":"In this work, we study the problem of band selection in multimodal remote sensing scenes. We present a deep learning system based on a three-dimensional variation of the DenseNet model architecture that we further modify to incorporate early and late feature fusion for multimodal learning of land cover classification. Band selection is applied during data preprocessing in order to counteract the Hughes' phenomenon (also known as the “Curse of Dimensionality”), with the intent of improving classification performance. We evaluate this deep learning data fusion system with the IEEE Geoscience and Remote Sensing Society (GRSS) data fusion contest (DFC) 2018 University of Houston dataset, a multimodal urban land usage and land cover (LULC) dataset. The experimental test harness for this work uses the TensorFlow and Keras deep learning frameworks to implement the proposed system, and our models are trained in the cloud via Google Colab notebooks. Our findings show that intelligent selection of hyperspectral bands and careful arrangement of feature fusion can result in an 8%-15% improvement in classification accuracy from the GRSS DFC 2018 contest winners when ignoring ad-hoc postprocessing. Finally, we present tables and plots comparing the efficacy of various modality fusion combinations and band selection methods to provide an in-depth analysis of how different bands and sensor modalities affect classification.","PeriodicalId":162426,"journal":{"name":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","volume":"542 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121983744","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

Securing Over-the-Air Firmware Updates (FOTA) for Industrial Internet of Things (IIOT) Devices 保护工业物联网(IIOT)设备的无线固件更新(FOTA)

2022 IEEE International Symposium on Technologies for Homeland Security (HST) Pub Date : 2022-11-14 DOI: 10.1109/HST56032.2022.10025441

K. Crowther, Radhika Upadrashta, G. Ramachandra

{"title":"Securing Over-the-Air Firmware Updates (FOTA) for Industrial Internet of Things (IIOT) Devices","authors":"K. Crowther, Radhika Upadrashta, G. Ramachandra","doi":"10.1109/HST56032.2022.10025441","DOIUrl":"https://doi.org/10.1109/HST56032.2022.10025441","url":null,"abstract":"Industrial Internet of Things (IIOT) is increasingly relying on over-the-air firmware updates (FOTA) to deliver tailored analytics to control systems for critical infrastructure. Connected IIOT with FOTA can deliver significant value by decreasing capital investments, enabling customizable functionalities, or improving operational efficiencies. FOTA also increases exposure to threats targeting critical infrastructure, which could lead to safety or mission damage (i.e., failures could result in loss of life or loss of critical functions). This paper presents a security baseline for FOTA by creating a secure “pipeline” for IIOT firmware. It first provides a generic reference architecture that defines connections between the IIOT device, a gateway for communication outside the control network, cloud storage and configuration logic, and the device-vendor's development environment. It describes attacks against various aspects of the reference architecture and explains the security controls that the device-vendor should implement to ensure that the benefits of FOTA for continuous upgradable security and efficiency outweigh the risks from additional exposure. It also provides some follow-on recommendations that utilities should consider before installing IIOT with FOTA capabilities, including: securing the device with secure boot and chain of trust, securing all communication channels with unique endpoint identification and encryption, taking the human out of the build and update processes, and hardening components involved in FOTA for continuous monitoring. This paper emphasizes that these types of connected devices promote a need for a shared responsibility model of cybersecurity.","PeriodicalId":162426,"journal":{"name":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122316145","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

Resilient First Responder Paging via ATSC 3.0/NEXT GEN TV 弹性第一响应者寻呼通过ATSC 3.0/下一代电视

2022 IEEE International Symposium on Technologies for Homeland Security (HST) Pub Date : 2022-11-14 DOI: 10.1109/HST56032.2022.10024981

F. Engel, Red Grasso, Tony Sammarco

{"title":"Resilient First Responder Paging via ATSC 3.0/NEXT GEN TV","authors":"F. Engel, Red Grasso, Tony Sammarco","doi":"10.1109/HST56032.2022.10024981","DOIUrl":"https://doi.org/10.1109/HST56032.2022.10024981","url":null,"abstract":"Many Emergency Medical Service (EMS) and Fire services across the United States still rely on analog voice paging technology to communicate emergency incident information to responders. The infrastructure for these paging systems is typically owned, operated, and maintained by the local government or agency to ensure coverage includes as close to 100% of the jurisdiction as possible. This paper proposes the use of datacasting technology to provide a redundant method for critical data distribution over a wide area to serve the paging needs of public safety and uses North Carolina as a test case. This concept could lead to cost-sharing, higher reliability, greater collaboration across jurisdictions, and reduced response times. The public deserves the best possible response from the public safety sector and therefore, public safety deserves the best technology available in order to achieve their mission. PBS North Carolina, along with the North Carolina Department of Information Technology First Responder Emerging Technologies Program (FirstTech), presented this concept at the 2019 National Association of Broadcasters (NAB) Broadcast Engineering and Information Technology Conference. Much progress has been made since then. Starting in early 2020, a United States Department of Homeland Security Small Business Innovation Research grant was awarded to develop a prototype system that included an encoder and a custom ATSC 3.0 paging receiver with a miniature antenna. This paper will discuss the overall concept and current progress using ATSC 3.0 to address a critical emergency communications need [1].","PeriodicalId":162426,"journal":{"name":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","volume":"39 327 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127302102","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

AdverSAR: Adversarial Search and Rescue via Multi-Agent Reinforcement Learning AdverSAR:基于多智能体强化学习的对抗性搜索和救援

2022 IEEE International Symposium on Technologies for Homeland Security (HST) Pub Date : 2022-11-14 DOI: 10.1109/HST56032.2022.10025434

A. Rahman, Arnab Bhattacharya, Thiagarajan Ramachandran, Sayak Mukherjee, Himanshu Sharma, Ted Fujimoto, Samrat Chatterjee

{"title":"AdverSAR: Adversarial Search and Rescue via Multi-Agent Reinforcement Learning","authors":"A. Rahman, Arnab Bhattacharya, Thiagarajan Ramachandran, Sayak Mukherjee, Himanshu Sharma, Ted Fujimoto, Samrat Chatterjee","doi":"10.1109/HST56032.2022.10025434","DOIUrl":"https://doi.org/10.1109/HST56032.2022.10025434","url":null,"abstract":"Search and Rescue (SAR) missions in remote environments often employ autonomous multi-robot systems that learn, plan, and execute a combination of local single-robot control actions, group primitives, and global mission-oriented coordination and collaboration. Often, SAR coordination strategies are manually designed by human experts who can remotely control the multi-robot system and enable semi-autonomous operations. However, in remote environments where connectivity is limited and human intervention is often not possible, decentralized collaboration strategies are needed for fully-autonomous operations. Nevertheless, decentralized coordination may be ineffective in adversarial environments due to sensor noise, actuation faults, or manipulation of inter-agent communication data. In this paper, we propose an algorithmic approach based on adversarial multi-agent reinforcement learning (MARL) that allows robots to efficiently coordinate their strategies in the presence of adversarial inter-agent communications. In our setup, the objective of the multi-robot team is to discover targets strategically in an obstacle-strewn geographical area by minimizing the average time needed to find the targets. It is assumed that the robots have no prior knowledge of the target locations, and they can interact with only a subset of neighboring robots at any time. Based on the centralized training with decentralized execution (CTDE) paradigm in MARL, we utilize a hierarchical meta-learning framework to learn dynamic team-coordination modalities and discover emergent team behavior under complex cooperative-competitive scenarios. The effectiveness of our approach is demonstrated on a collection of prototype grid-world environments with different specifications of benign and adversarial agents, target locations, and agent rewards.","PeriodicalId":162426,"journal":{"name":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132853066","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

Universal Simulation Platform, a VR Simulator for IED Neutralization Training 通用仿真平台，一种用于IED中和训练的VR模拟器

2022 IEEE International Symposium on Technologies for Homeland Security (HST) Pub Date : 2022-11-14 DOI: 10.1109/HST56032.2022.10025428

Arman Hamzehlou Kahrizi, Mihal Miu, Christopher Chun Ki Chan, A. Ferworn

{"title":"Universal Simulation Platform, a VR Simulator for IED Neutralization Training","authors":"Arman Hamzehlou Kahrizi, Mihal Miu, Christopher Chun Ki Chan, A. Ferworn","doi":"10.1109/HST56032.2022.10025428","DOIUrl":"https://doi.org/10.1109/HST56032.2022.10025428","url":null,"abstract":"Improvised explosive devices are mainly used to cause harm and terror. Explosive ordnance disposal technicians detect and safely neutralize improvised explosive devices. Due to their nature, improvised explosive devices pose an inherent risk to explosive ordnance disposal technicians. To minimize the risk associated with improvised explosive devices, explosive ordnance disposal technicians receive extensive training in working with explosive ordnances in various forms. Training often involves mock scenarios designed to simulate real-world conditions and can involve specialized equipment such as “disruptors” that fire live ammunition against a simulated improvised explosive device. While this training format is valuable, it still involves the expenses associated with the environment setup and equipment used during the training. Because of that, only a limited number of training sessions can be conducted. In this paper, we propose Universal Simulation Platform, a software based on virtual reality technology that can be used for improvised explosive device neutralization training. This simulation software allows for customized scenarios implemented by participants or any organization intending to deploy the software. Participants in each simulation can interact with the virtual environment while trying to neutralize or mitigate the impact of the improvised explosive device under various conditions and settings.","PeriodicalId":162426,"journal":{"name":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117122903","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

Analytics for Cybersecurity Policy of Cyber-Physical Systems 网络物理系统的网络安全策略分析

2022 IEEE International Symposium on Technologies for Homeland Security (HST) Pub Date : 2022-11-14 DOI: 10.1109/HST56032.2022.10025438

N. Choucri, G. Agarwal

引用次数: 0

UNIMODAL: UAV-Aided Infrared Imaging Based Object Detection and Localization for Search and Disaster Recovery 单模:用于搜索和灾难恢复的基于无人机辅助红外成像的目标检测和定位

2022 IEEE International Symposium on Technologies for Homeland Security (HST) Pub Date : 2022-11-14 DOI: 10.1109/HST56032.2022.10025436

Shubhabrata Mukherjee, Oliver Coudert, C. Beard

引用次数: 1

Complex Economic Consequence Analysis to Protect the Maritime Infrastructure 保护海洋基础设施的复杂经济后果分析

2022 IEEE International Symposium on Technologies for Homeland Security (HST) Pub Date : 2022-11-14 DOI: 10.1109/HST56032.2022.10024979

D. Egan, C. Nelson, F. Roberts, Adam Rose, A. Tucci, Ryan A G Whytlaw

{"title":"Complex Economic Consequence Analysis to Protect the Maritime Infrastructure","authors":"D. Egan, C. Nelson, F. Roberts, Adam Rose, A. Tucci, Ryan A G Whytlaw","doi":"10.1109/HST56032.2022.10024979","DOIUrl":"https://doi.org/10.1109/HST56032.2022.10024979","url":null,"abstract":"The marine transportation system (MTS) is a critical part of the nation's supply chain. Malicious actors, natural disasters, pandemics, geo-political events and larger marine casualties such as the 2021 Suez Canal grounding incident can disrupt the MTS and domestic and global supply chains. To date, most research and contingency planning has focused on single-event disruptions such as oil spills or security issues. While supply chains may be resilient enough to cope with a wide variety of single disruptions, aggregated challenges may result in cascading failures. There has been little analysis of the impacts of multiple disruptions that build on each other in complex ways. This suggests that modeling the impact of multiple vector disruptions on multiple MTS targets can help policy makers, business leaders, and others anticipate, plan for, mitigate, and rapidly recover from future complex disruptions. This paper describes an approach to research questions like: What are plausible examples of complex, multi-vector disruptions to the MTS? What could make their outcomes more complicated and challenging than those of single disruptions? What are their consequences for different components of the MTS? What are some pre-disruption mitigations and post-disruption resilience tactics that might be useful in such cases? How can we estimate the time to implement them, the costs of implementation, and the reduction of impact of such measures? The project described is developing a framework to address such questions. The framework will be used to analyze the impact of different combinations of individual disruptions, including natural disasters and climate change; security events, including cyber, accidents and marine casualties; and social/political disruptions. The analysis will focus on the total economic consequences of these threat combinations and transition into a user-friendly decision-support tool to improve risk management.","PeriodicalId":162426,"journal":{"name":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131222851","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

Machine Learning Models for Network Traffic Classification in Programmable Logic 可编程逻辑中网络流量分类的机器学习模型

2022 IEEE International Symposium on Technologies for Homeland Security (HST) Pub Date : 2022-11-14 DOI: 10.1109/HST56032.2022.10025442

Brendan Jacobson, Denver Conger, Bryton Petersen, Matthew Anderson, Matthew Sgambati

{"title":"Machine Learning Models for Network Traffic Classification in Programmable Logic","authors":"Brendan Jacobson, Denver Conger, Bryton Petersen, Matthew Anderson, Matthew Sgambati","doi":"10.1109/HST56032.2022.10025442","DOIUrl":"https://doi.org/10.1109/HST56032.2022.10025442","url":null,"abstract":"Network traffic classification via machine learning on network packet payloads has emerged as an active area of research for network security due to the high accuracy machine learning models have achieved in classifying payloads. For effective deployment as part of network security, these machine learning models must not only classify malicious packet payloads accurately, they must also identify anomalous payloads and perform inference at speeds generally faster than 10,000 packets per second to be effective. This work explores the inference speeds and accuracy of several neural network models implemented in programmable logic on various field programmable gate arrays (FPGA), including the Xilinx VC1902 and Xilinx Zynq Ultrascale+. This work also presents the design and performance of both an autoencoder and variational autoencoder programmed on the FPGA for identifying anomalous packet payloads. The performance benefits of the FPGA implementation for this type of packet payload inspection driven by machine learning are compared against graphics processing unit (GPU) inference implementations run on two state-of-the-art datacenter GPU devices, the NVIDIA V100 and A100. The model accuracy difference between the FPGA and GPU implementations was 4% or less while the Xilinx VC1902 outperformed both the NVIDIA V100 and A100 for inference speeds on all the models explored except the variational autoencoder.","PeriodicalId":162426,"journal":{"name":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114506321","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