<p> There’s always a requirement for faster, more accurate, and easier to implement threat identification systems for concealed electronics, to thwart terrorism and espionage attempts. Common electronic devices are used in the design of improvised explosive devices (IEDs) that target military and civilian populations alike, while concealed recording devices illegally capture proprietary and confidential data, compromising both governmental and industrial information resources. This research proposes a unique nonintrusive, repeatable, reliable and scalable D&I system for identifying threat devices by unintended radiated emissions (URE). Only a passive URE system, as opposed to active or hybrid systems, is appropriate for bomb detection or human interrogation, since potentially hazardous energy radiations are not emitted. Additionally, the proposed system is distinctive in its simplicity, allowing rapid implementation, and easy expandability. Finally, validation testing is provided to demonstrate the system’s reliability and repeatability. </p><p> URE is the electromagnetic emissions that active electronic equipment, such as radios and cellphones radiate. URE is analogous to a human fingerprint, since on a microscopic level, each and every URE signature is unique. However same-type electronic devices put out similar radiations and electronics of the same model have almost identical radio frequency signatures. URE signatures can change with device settings, such as a channel on a radio, or Airplane versus Clock mode on a cell phone. This uniqueness of URE data per device setting enables URE to be used to determine the mode of an operational electronic device. The characteristics of URE enable it to be used for explosive ordinance detection (EOD) and applications such as quality control in manufacturing, electronics troubleshooting,device identification for inventory, and detection of prohibited hidden electronics. </p><p> The proposed D&I process also addresses big data problems involved in capturing URE data and building a database of URE characteristics for identification. Issue interpretation is utilized with the URE data to distinguish between threat and non-threat electronic devices, using multiple criteria decision analysis (MCDA) and decision-making techniques to determine type, model and mode of the hidden devices. The outlined URE data handling methods and specified decision analysis techniques for URE data processing are further unique contributions of this research. </p><p> Optimization, verified by testing, is used to improve the speed and accuracy of the identification decision algorithm. The developed system is validated with URE data from 166 devices, which are representative of IED and espionage threats, but the system is extendable to all URE D&I applications, such as Quality Assurance, Inventory, and smart applications. Due to the immaturity of the URE D&I field and lack of documentation on the topic, the properties and potential of this more effective D&I system, compared to current methods, will be of interest to explosive ordnance disposal, security service, electronic system manufacturing, automated inventory, and mobile application development communities and potentially others as well. </p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10743603 |
| Date | 26 April 2018 |
| Creators | Friedel, Joseph E. |
| Publisher | The George Washington University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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