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IEEE Southeastcon

作者： Xin Wang Quentin Goss Mustafa İlhan Akbaş Alireza Chakeri Juan M. Calderon Luis G. Jaimes Florida Polytechnic University Lakeland FL Electrical ComputerSoftware&Systems Engineering Embry-Riddle Aeronautical University Daytona FL University of South Florida Tampa FL Bethune-Cookman University Daytona Beach FL USA Universidad Santo Tomás Bogota Colombia

ISBN: (数字)9781728168616

ISBN: (纸本)9781728168623

In this paper, we present an incentive mechanism for vehicular crowdsensing (VCS) based on a recurrent reverse auction. The proposed approach encourages participant's vehicles to used their sensors to collect data while also maximizing their utility. This approach tackles important issues in VCS such as cost explosion, and area sensing coverage. Using a realistic street network from OpenStreetMaps with extensive SUMO (Simulation of Urban Mobility) simulations, we show our VCS algorithm significantly o utperforms the baseline approach in terms of sensing coverage and active number of participants by three and eight times respectively.

关键词： Crowdsensing Explosions Sensors

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Fail-Safe, Fail-Secure Experiments for Small UAS and UAM Traffic in Urban Airspace

Fail-Safe, Fail-Secure Experiments for Small UAS and UAM Tra...

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Conference on Digital Avionics systems (DASC)

作者： Sam Siewert Krishna Sampigethaya Jonathan Buchholz Steve Rizor Computer Electrical & Software Engineering Embry-Riddle Aeronautical University Prescott Arizona USA Cyber Intelligence & Security Embry-Riddle Aeronautical University Prescott Arizona USA Unmanned & Autonomous Systems Engineering Embry-Riddle Aeronautical University Daytona Beach Florida USA Electrical Computer & Energy Engineering University of Colorado Boulder Boulder Colorado USA

ISBN: (数字)9781728106496

ISBN: (纸本)9781728114972

Millions of small Unmanned Aerial systems (sUAS), or drones weighing less than 55 pounds, will fly in urban airspaces within a decade. This is in addition to goals for increased Urban Air Mobility (UAM): larger transportation UAS and piloted air vehicles, including air taxi service and innovative aviation designs to revolutionize transportation. A significant problem is the lack of current management systems for this extremely large volume of air traffic, composed of heterogeneous drone shapes, sizes, and onboard equipment capabilities, flying adjacent to larger UAM vehicles in spaces previously unoccupied by General Aviation (GA). Robust and resilient detection, identification, localization, and tracking of sUAS sharing UAM airspace is complicated by urban factors such as non-transmitting, non-cooperative drones. Exacerbating these challenges, current technological limitations and vulnerabilities in Global Positioning System (GPS), Automatic Dependent Surveillance-Broadcast (ADS-B), and Inertial Navigation systems (INS) can pose safety and security threats. To streamline a vision of safe and secure sUAS-UAM shared airspace, we propose Drone Net, a UAS Traffic Management (UTM) network of multi-modal ground and flight instruments. Drone Net is an architecture fusing a network of passive visual and acoustic sensor nodes with active Radio Detection and Ranging (radar) and Light Detection and Ranging (lidar) sensing methods for UTM, designed for integration with existing Air Traffic Control (ATC) and future UAM systems. The purpose of the Drone Net system is to evaluate use of Electro-Optical/Infrared (EO/IR) and acoustic arrays networked within an urban UAS operating region such as uncontrolled Class-G and waiver-granted Class-D airspace. The Drone Net approach combines detection, tracking, and localization estimation from radar, ADS-B, and EO/IR such that the design is robust to sensor errors, sample loss, and spoofing or other types of attacks. The system experimenta

关键词： fail-safe fail-secure UAS UTM UAM GPS ADS-B UAM drone honey bees Global Positioning systems Safes air traffic ground-based radar

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Towards eliciting and analyzing security requirements using ontologies through use case scenarios (work-in-progress) 4

Towards eliciting and analyzing security requirements using ...

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4th International Conference on software Security and Assurance, ICSSA 2018

作者： Ochoa, Omar Steinmann, Jessica Lischuk, Yevgeniy Department of Electrical Computer Software & Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

ISBN: (纸本)9781538692103

As our reliance on large, complex and ubiquitous software system increases, so does the devastating consequences that a cyberattack can have to modern society. Building secure software systems requires a greater need for secure software engineering approaches that can detect and address security vulnerabilities at the earliest stages of the software development life cycle. This paper presents an approach to facilitate the elicitation of cybersecurity requirements based on enhancing the widely adopted technique of use case modeling by incorporating the use of an ontology. The ontology will model the semantic relationship of cybersecurity requirements. Utilizing this ontology, we propose an approach that can be used to reuse and share cybersecurity requirements, providing a potential for the rapid discovery and correction of software vulnerabilities in the development process. © 2018 IEEE.

关键词： Ontology

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ESFNet: Efficient network for building extraction from high-resolution aerial images

arXiv

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arXiv 2019年

作者： Lin, Jingbo Jing, Weipeng Song, Houbing Chen, Guangsheng College of Information and Computer Engineering Northeast Forestry University Harbin HLJ China Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

Building footprint extraction from high-resolution aerial images is always an essential part of urban dynamic monitoring, planning and management. It has also been a challenging task in remote sensing research. In recent years, deep neural networks have made great achievement in improving accuracy of building extraction from remote sensing imagery. However, most of existing approaches usually require large amount of parameters and floating point operations for high accuracy, it leads to high memory consumption and low inference speed which are harmful to research. In this paper, we proposed a novel efficient network named ESFNet which employs separable factorized residual block and utilizes the dilated convolutions, aiming to preserve slight accuracy loss with low computational cost and memory consumption. Our ESFNet obtains a better trade-off between accuracy and efficiency, it can run at over 100 FPS on single Tesla V100, requires 6x fewer FLOPs and has 18x fewer parameters than state-of-the-art real-time architecture ERFNet while preserving similar accuracy without any additional context module, post-processing and pre-trained scheme. We evaluated our networks on WHU Building Dataset and compared it with other state-of-the-art architectures. The result and comprehensive analysis show that our networks are benefit for efficient remote sensing researches, and the idea can be further extended to other areas. The code is public available at: https://***/mrluin/ESFNet-Pytorch. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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SAN: Scale-aware network for semantic segmentation of high-resolution aerial images

arXiv

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arXiv 2019年

作者： Lin, Jingbo Jingy, Weipeng Songz, Houbing College of Information and Computer Engineering Northeast Forestry University Harbin HLJ China Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

High-resolution aerial images have a wide range of applications, such as military exploration, and urban planning. Semantic segmentation is a fundamental method extensively used in the analysis of high-resolution aerial images. However, the ground objects in high-resolution aerial images have the characteristics of inconsistent scale, and this feature usually leads to unexpected predictions. To tackle this issue, we propose a novel scale-aware module (SAM). In SAM, we employ resampling method aimed to make pixels adjust their positions to fit the ground objects with different scales, and it implicitly introduce spatial attention by employing re-sampling map as weighted map. As a result, the network with the proposed module named scale-aware network (SANet) has a stronger ability to distinguish the ground objects with inconsistent scale. Other than this, our proposed modules can easily embed in most of the existing network to improve their performance. We evaluate our modules on International Society for Photogrammetry and Remote Sensing Vaihingen Dataset, and the experimental results and comprehensive analysis demonstrate the effectiveness of our proposed module. Copyright © 2019, The Authors. All rights reserved.

关键词： Remote sensing

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Security of the Internet of Things: Vulnerabilities, Attacks and Countermeasures

arXiv

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arXiv 2019年

作者： Butun, Ismail Österberg, Patrik Song, Houbing Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Mid Sweden University Sundsvall Sweden Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University FL United States

Wireless Sensor Networks (WSNs) constitute one of the most promising third-millennium technologies and have wide range of applications in our surrounding environment. The reason behind the vast adoption of WSNs in various applications is that they have tremendously appealing features, e.g., low production cost, low installation cost, unattended network operation, autonomous and longtime operation. WSNs have started to merge with the Internet of Things (IoT) through the introduction of Internet access capability in sensor nodes and sensing ability in Internet-connected devices. Thereby, the IoT is providing access to huge amount of data, collected by the WSNs, over the Internet. However, owing to the absence of a physical line-of-defense, i.e. there is no dedicated infrastructure such as gateways to watch and observe the flowing information in the network, security of WSNs along with IoT is of a big concern to the scientific community. More specifically, for the application areas in which CIA (confidentiality, integrity, availability) has prime importance, WSNs and emerging IoT technology might constitute an open avenue for the attackers. Besides, recent integration and collaboration of WSNs with IoT will open new challenges and problems in terms of security. Hence, this would be a nightmare for the individuals using these systems as well as the security administrators who are managing those networks. Therefore, a detailed review of security attacks towards WSNs and IoT, along with the techniques for prevention, detection, and mitigation of those attacks are provided in this paper. In this text, attacks are categorized and treated into mainly two parts, most or all types of attacks towards WSNs and IoT are investigated under that umbrella: "Passive Attacks" and "Active Attacks". Understanding these attacks and their associated defense mechanisms will help paving a secure path towards the proliferation and public acceptance of IoT technology. Copyright © 2019, The Aut

关键词： Internet of things

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Fine-grained Resource Management for Edge Computing Satellite Networks

Fine-grained Resource Management for Edge Computing Satellit...

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IEEE Global Communications Conference

作者： Feng Wang Dingde Jiang Sheng Qi Chen Qiao Houbing Song School of Astronautics and Aeronautic University of Electronic Science and Technology of China Chengdu China Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona Beach FL USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

The low earth orbit (LEO) satellite network has been a valuable architecture due to its characteristics of wide coverage and low transmission delay. Utilizing LEO satellites as edge computing nodes to provide real-time services for access terminals will be the indispensable paradigm of integrated space-air-ground network. However, it is not easy to design resource management strategies in edge computing satellite (ECS), considering different accessing planes and resource requirements of terminals. Moreover, a comprehensive analysis of the network topology, relative motion, and available resources is required to establish ECS collaborative networks. To address these problems, the dynamic resource allocation architecture and advanced K-means algorithm (AKA) in ECSs are proposed. Then, the extended graph model and breadth-first-search-based spanning tree (BFST) algorithm are utilized to guide the inter-satellite link (ISL) construction. As a result, the ECS collaborative network is established with fine-grained resource management. Simulation results show that the proposed fine-grained resource management scheme is feasible and effective.

关键词： Resource management Low earth orbit satellites Satellite broadcasting Edge computing Satellites Delays Bandwidth

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Using scenarios to validate requirements through the use of eye-tracking in prototyping 12th

Using scenarios to validate requirements through the use of ...

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12th International Conference on Augmented Cognition, AC 2018 Held as Part of HCI International 2018

作者： Larsen-Calcano, Tia Ochoa, Omar Simonson, Richard Department of Human Factors Psychology Norflok United States Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

ISBN: (纸本)9783319914664

Research has shown that eliciting and capturing the correct behavior of systems reduces the number of defects that a system contains. A requirements engineer will model the functions of the system to gain a comprehensive understanding of the system in question. Engineers must verify the model for correctness by either having another engineer review it or build a prototype and validate with a stakeholder. However, research has shown that this form of verification can be ineffective because looking at an existing model can be suggestive and stump the development of new ideas. This paper provides an automated technique that can be used as an unbiased review of use case scenarios. Using the prototype and a scenario, a stakeholder can be guided through the use case scenario demonstrating where they expect to find the next step. Instead of measuring how many mistakes the individual makes or how long it takes them to complete the scenario, the purpose of going through the scenario with the prototype can be to capture where the individual is actually looking. Analysis of that information can be used to identify missing requirements such as interaction steps that should have alternative sequences, or determining problems with the flow of actions. The proposed approach can be used to both facilitate the further elicitation of requirements using eye-tracking techniques and validate prototypes in tandem with use case scenarios. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Eye tracking

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A Robust Network Traffic Modeling Approach to software Defined Networking

A Robust Network Traffic Modeling Approach to Software Defin...

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IEEE Global Communications Conference

作者： Liuwei Huo Dingde Jiang Houbing Song College of Computer Science and Engineering Northeastern University Shenyang China School of Astronautics and Aeronautic University of Electronic Science and Technology of China Chengdu China Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona Beach FL USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

software Defined Networking (SDN) architecture satisfies the flexibility and scalability requirements of Internet of Things (IoT) network. A large amounts of IoT data is transmitted and exchanged through IoT network. However, many of services of IoT are sensitive to latency and bandwidth, so the network traffic model and measurement in IoT are different legacy networks. In this paper, we propose a robust network traffic modeling approach and use it to estimate network traffic in IoT. To obtain the measurement results with low overhead and high accuracy, we model the network traffic as liner function with noise. Then, we collect the statistics of coarse-grained traffic of flows and fine-grained traffic of links, and use the robust network traffic model to forecast the network traffic with the coarsegrained measurement of flows. In order to optimize the estimation results, we propose an optimization function to decrease the estimation errors. Since the optimization function is NP-hard problem, then we use a heuristic algorithm to obtain the optimal solution of the fine-grained measurement. Finally, we conduct some simulations to verify the proposed measurement scheme. Simulation results show that our approach is feasible and effective.

关键词： Telecommunication traffic Estimation Cloud computing Load modeling Computational modeling Optimization

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Towards Eliciting and Analyzing Security Requirements Using Ontologies through Use Case Scenarios (Work-in-Progress)

Towards Eliciting and Analyzing Security Requirements Using ...

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International Conference on software Security and Assurance (ICSSA)

作者： Omar Ochoa Jessica Steinmann Yevgeniy Lischuk Department of Electrical Computer Software & Systems Engineering Embry-Riddle Aeronautical University Daytona Beach FL USA

ISBN: (数字)9781538692103

ISBN: (纸本)9781538692110

关键词： Ontologies software systems Cyberattack Authentication

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