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Share photonics technologies research for cyber-physical systems / IoT

Come hear the latest optics and photonics for Cyber-physical systems and the Internet of Things at SPIE Defense + Commercial Sensing 2018

Learn from experts about the latest advancements in sensors, sensor fusion, big data, deep learning, cyber security, and other and related photonics research critical to advancing cyber-physical systems and the Internet of Things.

Our topical tracks help you quickly locate potential items of interest in the 2018 Defense + Commercial Sensing program, such as sessions, papers, vendors, and courses. Explore the information below to see what may interest you. 

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Registration opens late December

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Browse the papers

Below are conferences and papers that include significant technical content related to CPS/IoT applications. SPIE Defense + Commercial Sensing 2018 includes 50 conferences and 1,900 papers and many of them may be of interest to those interested in CPS/IoT applications, however these 4 conferences and 22 papers have been identified as containing specific content that may be of particular interest. 

Review these 4 conferences

 • Cyber Sensing 2018
 • Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
 • Disruptive Technologies in Information Sciences
 • Next-Generation Analyst

Review the 22+ papers below
These papers are listed by conference and paper number

Implementations of moving target defense
Paper 10630-4

Author(s):  Nathaniel Evans, Argonne National Lab. (United States), et al.
Conference 10630: Cyber Sensing 2018
Session 1: Cyber Security Framework

A common challenge in cybersecurity systems is the static nature of their defenses. Moving Target Defense (MTD) systems mitigate the limitations of static defense by creating a dynamic attack surface, which increases uncertainty from the perspective of the attacker(s) as well as the cost and effort required to launch an attack. Although suggestions for MTD techniques flourish, implementation of MTD in practice has been slow, perhaps because of the complexity and lack of demonstrated feasibility of the proposed solutions. We have experimented with the existing MTD concepts and developed our own implementations.


Lightweight hardware monitoring of IoT devices
Paper 10630-21

Author(s):  Jason Wampler, INCA Engineering (United States), et al.
Conference 10630: Cyber Sensing 2018
Session 4: Analog Domain and Cyber Security III


Generation and management of training data for AI based algorithms targeted at coalition operations
Paper 10635-28

Author(s):  Dinesh Verma, IBM Thomas J. Watson Research Ctr. (United States), et al.
Conference 10635: Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX
Session 9: Coalition Operations and Interoperability

AI based algorithms have great potential for inter-operation of coalition ISR systems, but rely on realistic data for training and validation. Getting such data for coalition scenarios is hampered by military regulations, and is a significant hurdle in conducting basic research. We discuss an approach whereby training data can be obtained by means of scenario-driven simulations, which result in traces for network devices, ISR sensors and other infrastructure components. This generated data can be used for both training and comparison of different AI based algorithms. Coupling the synthetic data generator with a data curation system further increases its applicability.


Autonomous vehicles and cybersecurity: a paradigm for problem and solution assessment and a sensing approach to problem detection
Paper 10643-3

Author(s):  Jeremy Straub, North Dakota State Univ. (United States), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session 1: Cyber and Software Security for Autonomous Operations

Autonomous vehicle cybersecurity breaches present severe danger to vehicle occupants and those nearby. Future vehicles will operate without human oversight or, in some cases, human occupants. This paper presents paradigms for characterizing and evaluating security challenges and solutions for autonomous vehicles. It also presents an intrusion / anomaly detection system for fully autonomous vehicles. This system characterizes normal behavior and uses shared characterizations of abnormal behavior from peer vehicles and a centralized node. It decides whether the vehicle is operating in normal, heightened security awareness, or active attack conditions. Multiple case studies are used to evaluate system efficacy.


Maintaining trusted platform in a cyber-contested environment
Paper 10643-6

Author(s):  David Hadcock, Alion Science and Technology Corp. (United States), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session 1: Cyber and Software Security for Autonomous Operations

Maintaining the highest level of trust within each system device is necessary to counter increased cyber-attack surface in distributed environments. The goal is to provide and maintain a trusted embedded computing system while minimizing performance impact. Alion has developed a platform utilizing a heterogeneous system-on-chip that includes multiple processors, programmable logic, and memory allowing for hardware-based resilience technologies that extend or enhance traditional software techniques. Secure boot ensures trusted initial state. Hardware sandboxes and reference monitors limit information leakage and damage from rogue IP. Dynamic introspection detects anomalous conditions on-the-fly. Secure recovery can return compromised systems to a trusted state.


Certificates, code signing and digital signatures
Paper 10643-7

Author(s):  Michael Anderson, The PTR Group (United States), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session 1: Cyber and Software Security for Autonomous Operations

In order to secure our IoT devices and their cloud-based data collection systems, we need to provide some immutable means for identification and authentication of systems and their software. In this session, we will discuss the nature of security certificates, code signing and digital signatures. The talk will compare and contrast these approaches and outline which techniques are used in what ecosystems, how to generate your own digital certificates and how to secure the transactions in IoT ecosystems.


Enhanced pedestrian safety awareness at crosswalks via networked lidar, thermal imaging, and sensors
Paper 10643-13

Author(s):  Zachary A. Weingarten, Florida Polytechnic Univ. (United States), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session 2: Object Sensing for Detection, Classification, and Autonomous Operations

The system makes use of thermal imaging, LiDAR, conventional imagers, and sensors to distinguish between cars, people, animals, and other objects that may interact with a crosswalk at or near an intersection. A mesh network of these systems as nodes enables the coordination of information, alerts and/or interfaces to coordinate control of the lights as well as alert vehicles and people crossing at a crosswalk or an intersection. The data could also be used to enhance coordination of IoT or mobile devices such as those integrated with autonomous vehicles and the Intelligent Transportation System infrastructure to predict how to handle a pedestrian interaction with crosswalks or intersection. The goal of the system is to enhance pedestrian safety at crosswalks or intersections via LiDAR, thermal imaging, conventional imagers, shared interfaces, networks and other resources.


Distributed control technology for management of roads with driverless cars
Paper 10643-35

Author(s):  Peter Sapaty, The National Academy of Sciences of Ukraine (Ukraine), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session 7: Autonomous Operations, Artificial Intelligence, and Navigation III

The presentation will describe advanced information and control technology suitable among many applications for distributed integral management of road networks massively using autonomous cars. The approach is based on high-level Spatial Grasp Language (SGL) expressing solutions in large distributed spaces in the form of active self-evolving, self-modifying, and self-propagating patterns. Practical examples will be shown how different road problems and conflicts can be solved by invoking emergency scenarios covering any regions with any number of communicating vehicles. They are using intelligent SGL code spreading in networks in a controlled super-virus mode and creating distributed operational infrastructures oriented on concrete solutions.


It's a target-rich environment in the IoT
Paper 10643-43

Author(s):  Michael Anderson, The PTR Group (United States), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session PS1: Posters-Tuesday

The Internet of Things is a wonderful marketing term that means very little to many. What is a thing? How do we connect them to an Internet? In this presentation, we will discuss the nature of the major flavors of things including those from consumer and industrial/medial markets, and highlight the differences in end devices, border gateways and cloud--based data collection systems. We will also discuss messaging protocols and enabling technologies that make these devices both very desirable and incredibly vulnerable. in addition, we will talk about the presence of processors hidden in the silicon dies of other processors, establishing persistence of data in these hidden processors and the networking technologies that enable infiltration and exfiltration of data from these IoT devices.


Technical trade-offs of IoT platforms
Paper 10643-44

Author(s):  Michael Anderson, The PTR Group (United States), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session PS1: Posters-Tuesday

The IoT is crowded with dozens of so-called platforms. But, what is a platform? How do platforms make development and deployment of IoT applications easy or hard? In this session, we will discuss the major IoT platform offerings and provide some perspective on which platforms are likely to success and which will likely fail. We will specifically address, Apple's HomeKit, Thread, IoTivity, AllSeen and a collection of industrial platforms such as IBM's Bluemix, ThingWorx, Xively and several others. We will touch on how they differentiate themselves and why you might pick on over the other for an IoT sensor deployment.


Networking 20-billion devices
Paper 10643-45

Author(s):  Michael Anderson, The PTR Group (United States), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session PS1: Posters-Tuesday

The IPv4 address space is exhausted. The regional Internet registries are now only handing out IPv6 addresses. But, how does IPv6 enable access to the 20+ billion devices that are estimated to be in the IoT by the year 2020? And, since IPv4 isn't going away any time soon, how do we make IPv6 work side by side with IPv4? In this session, we will describe IPv6 addressing and its operation. Additionally, we will show techniques for writing one application that can support both IPv4 and IPv6 protocols simultaneously.


Cloud versus Fog: Which model is more secure for the IoT?
Paper 10643-46

Author(s):  Michael Anderson, The PTR Group (United States), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session PS1: Posters-Tuesday

When people traditionally think of the IoT, they thing sensors talking to big data collection system in the cloud. However, this model is significantly flawed from a security perspective. Namely, if your sensor can see the cloud, the cloud can also see your sensor. This opens up an attack surface that makes offensive cyber-operations specialists drool with anticipation. How can we provide for connectivity, while still providing protection from outside attackers? In this session, we will introduce the "fog" model and compare and contrast it to the more traditional cloud model for IoT connectivity. The attendee will get an opportunity to see the characteristics of each model with their pros and cons and why you might pick one connectivity model over another.


Printed self-powered miniature air sampling sensors
Paper 10643-47

Author(s):  Joseph Birmingham, Birmingham Technologies, Inc. (United States), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session PS1: Posters-Tuesday

The recent geo-political climate has increased the necessity for autonomous, chip-sized, lightweight, air sampling systems which can quickly detect and characterize chemical, biological, radiological, nuclear, and high explosive (CBRNE) hazardous materials and relay the results. To address these issues, we have developed a self-powered 3-D chip architecture that processes air to produce a concentrated size-sorted particle (and vapor) samples that are integrated with on-chip nanoelectronic detectors for the discovery of weapons of mass destruction (WMD). The self-powered microstructured array air sampler was designed using computational fluid dynamics (CFD) modeling to maximize aerosol collection and the CFD results predicted that the particles from 1-10 microns were collected at greater than 99.9999% efficiency. These predictions were matched by experimental results gathered in a Government aerosol chamber that verified that the microstructured arrays exceeded the collection capabili


An IOT honeynet for military deception and indications and warnings
Paper 10643-48

Author(s):  Peter Hanson, Concurrent Technologies Corp. (United States), et al.
Conference 10643: Autonomous Systems: Sensors, Vehicles, Security and the Internet of Everything
Session PS1: Posters-Tuesday

Honeyman, named for the American Revolutionary War spy and source of disinformation, is an IoT distributed deception platform (DDP), aka “honeynet”, based approach to military deception and indications and warning (I&W) generation. Honeyman uses dynamic targeted cyberbait and combines a proxy military logistics and readiness reporting IoT comprised of a mixture of virtual and physical devices with non-cyber information operations for military deception and to stimulate nation-state adversary behavior within the DDP. A machine learning (ML)-based traffic analysis model leverages observations within the honeynet to forecast an adversary’s physical military activity thereby providing critical I&W.


Occluded object reconstruction for first responders with augmented reality (AR) glasses using deep learning generative adversarial networks (GAN)
Paper 10649-34

Author(s):  Kyongsik Yun, Jet Propulsion Lab. (United States), et al.
Conference 10649: Pattern Recognition and Tracking XXIX
Session 7: Deep Learning Based Pattern Recognition

Over the past two decades, the number of firefighters injured per 1,000 fires has remained relatively constant, reinforcing the need for advanced ground support for firefighters. We built an occluded object reconstruction method on augmented reality (AR) glasses for the first responders. We used a deep learning based on generative adversarial networks (GAN) to train associations between the various images of flammable and hazardous objects and their occluded images. Our system then reconstructed an image of a new flammable object. Finally, the reconstructed image was superimposed on the input image to provide "transparency". The system imitates human learning about the laws of physics through experience by learning the shape of flammable objects and the flame characteristics.


OpenTap: Software defined data acquisition
Paper 10652-6

Author(s):  Michael McGarry, The Univ. of Texas at El Paso (United States), et al.
Conference 10652: Disruptive Technologies in Information Sciences
Session 1: IoT, Big Data Analytics and Storage


Design-optimization and performances of multispectral (VIS-SWIR) photodetector and its array
Paper 10656-21

Author(s):  Jaydeep Dutta, Banpil Photonics, Inc. (United States), et al.
Conference 10656: Image Sensing Technologies: Materials, Devices, Systems, and Applications V
Session 5: Advanced Photodetectors and Focal Plane Array (FPA)

A novel broadband (VIS-SWIR) photodetector is developed for focal plane array (FPA) for military, security, and industrial imaging applications. The photodetector is based on InGaAs and fabricated on InP substrate, exhibiting high sensitivity, high quantum efficiency, and yet cost-effective. In order to realize a small weight, power, and cost effectiveness (SWAP-C) camera, the photodetector must have low dark current at high operating temperatures, which saves power for cooling. This paper will explain photodetector structure, design-simulation for optimizing the parameters, and performance of the photodetector and its array. We investigate the device structure and the theory of the photodetector. Electrical and optical characteristics of the photodetectors will be also presented in this paper.


Ultra-miniature computational sensors and imagers: Incorporating algorithms to yield final digital images
Paper 10656-22

Author(s):  David G. Stork, Rambus Inc. (United States), et al.
Conference 10656: Image Sensing Technologies: Materials, Devices, Systems, and Applications V
Session 6: Computational Imaging I

Computational imaging relies on the joint design of optics and digital processing for producing the final digital image our output. Because the intermediate optical image need preserve the relevant visual information yet not necessarily "look good," a wider range of optical designs can be employed, including designs that eschew traditional optical elements such as lenses and curved mirrors. There are three primary approaches to such lensless imaging, based on 1) diffraction by special optical gratings, 2) in-line digital holography and computational phase recovery, and 3) compressive sensing using sets of pseudo-random masks. Each technique has relative strengths and weaknesses in computational burden, image accuracy, and are appropriate for different target applications.


Snapshot optical coherence tomography
Paper 10658-4

Author(s):  Xin Yuan, Nokia Bell Labs (United States), et al.
Conference 10658: Compressive Sensing VII: From Diverse Modalities to Big Data Analytics
Session 1: CS for Spectral and Medical Imaging

We propose the snapshot optical coherence tomography (OCT). The proposed system can capture the spectral domain OCT signal in a single snapshot, which is at least 10x faster than the current state-of-the-art approach with 10x lower cost. We implemented the system using the code division multiple access technique, which is composed a mask, a prism and a charge-coupled device (CCD), and all of them are low-cost. The coherence signal (the output of the spectral-domain OCT) is first projected on a mask with a random binary pattern, and then by using a prism, the spectrum of the light is spatially spread and modulated by shifting variants of the same mask. The coded spectra are then superimposed and captured by the CCD. In this manner, neither frequency scan nor spatial scan is required in the imaging system and thus the signal is captured in a single snapshot.


Image quality and accuracy of different thermal sensor at varying operation parameters
Paper 10664-14

Author(s):  Ajay Sharda, Kansas State Univ. (United States), et al.
Conference 10664: Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III
Session 3: Thermal and Hyperspectral Imaging from UAVs

Thermal image quality is very critical for accurately quantify spatial and temporal growth and stress patterns of field crops. Image quality can be impacted by many factors including environment, flying altitude, and camera focal length. Often times the thermal sensor selection is based upon price or already owned sensor. Metrics are available to select the flight altitude based on the thermal sensor for desired ground resolution, however, no study has been conducted to provide the relative difference in image quality and efficiency of generating a thermal orthomosaic. Therefore, this study was conducted with the goal to compare the accuracy of canopy temperature quantification and assess the quality of thermal orthomosaic when using a thermal sensor of different focal length and image acquisition at varying flying altitudes.


A low-cost method for collecting hyperspectral measurements from a small unmanned aircraft system
Paper 10664-15

Author(s):  Ali Hamidisepehr, Univ. of Kentucky (United States), et al.
Conference 10664: Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III
Session 3: Thermal and Hyperspectral Imaging from UAVs

This study aimed to develop a spectral measurement platform for deployment on a sUAS for quantifying and delineating moisture zones within an agricultural landscape. A series of portable spectrometers covering ultraviolet (UV), visible (VIS), and near-infrared (NIR) wavelengths were instrumented using an embedded computer programmed to interface with the sUAS autopilot for autonomous data acquisition. A calibration routine was developed that scaled raw reflectance data by sensor integration time and ambient light energy. Results indicated the potential for mitigating the effect of ambient light when passively measuring reflectance on a portable spectral measurement system.


Performance analysis of real-time DNN inference on Raspberry Pi
Paper 10670-14

Author(s):  Jorge Fernández-Berni, Instituto de Microelectrónica de Sevilla (Spain), et al.
Conference 10670: Real-Time Image and Video Processing 2018
Session 3: Real-Time Algorithms II

Deep Neural Networks (DNNs) have emerged as the reference processing architecture for multiple computer vision tasks. They achieve higher accuracy than traditional algorithms based on shallow learning. However, it comes at the cost of a substantial increase of computational resources. In this paper, we present a comparative study of the most popular frameworks for DNN deployment in terms of power consumption, throughput and precision. The benchmarking system is Raspberry Pi 3 Model B. We highlight the advantages and limitations associated with the practical use of the analyzed frameworks and provide some guidelines for suitable selection according to prescribed application requirements.


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