The Food and Drug Administration's Unique Device Identification System

2014 ◽  
Vol 174 (11) ◽  
pp. 1719 ◽  
Author(s):  
Josh Rising ◽  
Ben Moscovitch
Keyword(s):  
Identification System ◽  
Device Identification

ИДЕНТИФИКАЦИЯ УСТРОЙСТВ И СИСТЕМ УЗКОПОЛОСНЫХ БЕСПРОВОДНЫХ СЕТЕЙ СВЯЗИ ИНТЕРНЕТА ВЕЩЕЙ. ЧАСТЬ II

2020 ◽  
Author(s):  
A.S. BORODIN ◽  
R.V. KIRICHEK ◽  
D.D. SAZONOV ◽  
 M.A. ROZHKOV ◽  
 A.V. KOLESNIKOV ◽  
...  
Keyword(s):  
Simulation Model ◽  
Identification System ◽  
Digital Object ◽  
Device Identification ◽  
Transport Industry ◽  
Iot Devices

A description of an identification system for IoT devices based on the Digital Object Architecture (DOA) is given. An analysis of alternative identifiers is given and the advantages of DOA for both identification and anti-counterfeit purposes are shown. The second part of the article presents the implementation of DOA technology on a specific example - the device identification system in the Russian transport industry. It is also developed a simulation model of a network fragment. A series of optimization experiments are performed. Представлено описание системы идентификации на базе архитектуры цифровых объектов (Digital Object Architecture - DOA), которая в настоящее время рассматривается в качестве приоритетной для идентификации устройств и приложений интернета вещей. Приведен анализ альтернативных идентификаторов и показаны преимущества DOA какдля за -дач идентификации, так и для борьбы с контрафактом. Во второй части статьи представлена реализация данной технологии на конкретном примере - системе идентификации устройств в транспортной отрасли России, а также разработана имитационная модель фрагмента сети, на базе которой анализировались различные параметры функционирования системы. Дано базовое описание разработанной имитационной модели и проведена серия оптимизационных экспериментов с целью улучшения производительности текущей системы.

Low-cost non-intrusive device identification system

2016 ◽  
Author(s):  
Gosakan Srinivasan ◽  
Chandirasekarendiran Anandan ◽  
S Aashish Kumar Jain ◽  
Syed Shahbaaz Ahmed ◽  
Vineeth Vijayaraghavan
Keyword(s):  
Low Cost ◽  
Identification System ◽  
Device Identification

An end-to-end deep source recording device identification system for Web media forensics

2020 ◽  
Vol 16 (4) ◽  
pp. 413-425
Author(s):  
Chunyan Zeng ◽  
Dongliang Zhu ◽  
Zhifeng Wang ◽  
Zhenghui Wang ◽  
Nan Zhao ◽  
...  
Keyword(s):  
Source Identification ◽  
Feature Fusion ◽  
Vector System ◽  
Identification System ◽  
Recording Device ◽  
Device Identification ◽  
Content Type ◽  
Media Forensics ◽  
End To End ◽  
Web Media

Purpose Most source recording device identification models for Web media forensics are based on a single feature to complete the identification task and often have the disadvantages of long time and poor accuracy. The purpose of this paper is to propose a new method for end-to-end network source identification of multi-feature fusion devices. Design/methodology/approach This paper proposes an efficient multi-feature fusion source recording device identification method based on end-to-end and attention mechanism, so as to achieve efficient and convenient identification of recording devices of Web media forensics. Findings The authors conducted sufficient experiments to prove the effectiveness of the models that they have proposed. The experiments show that the end-to-end system is improved by 7.1% compared to the baseline i-vector system, compared to the authors’ previous system, the accuracy is improved by 0.4%, and the training time is reduced by 50%. Research limitations/implications With the development of Web media forensics and internet technology, the use of Web media as evidence is increasing. Among them, it is particularly important to study the authenticity and accuracy of Web media audio. Originality/value This paper aims to promote the development of source recording device identification and provide effective technology for Web media forensics and judicial record evidence that need to apply device source identification technology.

scholarly journals Device Identification Interoperability in Heterogeneous IoT Platforms

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1433 ◽  
Author(s):  
Jahoon Koo ◽  
Se-Ra Oh ◽  
Young-Gab Kim
Keyword(s):  
Continuous Improvement ◽  
Identification System ◽  
Device Identification ◽  
Resource Request ◽  
Sensor Device ◽  
Iot Platform ◽  
Considerable Research ◽  
Sensor Devices ◽  
Iot Platforms ◽  
Ibm Watson

With the continuous improvement of Internet of Things (IoT) technologies, various IoT platforms are under development. However, each IoT platform is developed based on its own device identification system. That is, it is challenging to identify each sensor device between heterogeneous IoT platforms owing to the resource request format (e.g., device identifier) varying between platforms. Moreover, despite the considerable research focusing on resource interoperability between heterogeneous IoT platforms, little attention is given to sensor device identification systems in diverse IoT platforms. In order to overcome this problem, the current work proposes an IoT device name system (DNS) architecture based on the comparative analysis of heterogeneous IoT platforms (i.e., oneM2M, GS1 ‘Oliot’, IBM ‘Watson IoT’, OCF ‘IoTivity’, FIWARE). The proposed IoT DNS analyzes and translates the identification system of the device and resource request format. In this process, resource requests between heterogeneous IoT platforms can be reconfigured appropriately for the resources and services requested by the user, and as a result, users can use heterogeneous IoT services. Furthermore, in order to illustrate the aim of the proposed architecture, the proposed IoT DNS is implemented and tested on a microcomputer. The experimental results show that a oneM2M-based device successfully performs a resource request to a Watson IoT and FIWARE sensor devices.

scholarly journals An Ensemble Learning Method for Wireless Multimedia Device Identification

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Zhen Zhang ◽  
Yibing Li ◽  
Chao Wang ◽  
Meiyu Wang ◽  
Ya Tu ◽  
...  
Keyword(s):  
Radio Frequency ◽  
Ensemble Learning ◽  
Data Transmission ◽  
Physical Layer ◽  
Classification Model ◽  
Identification System ◽  
Wireless Multimedia ◽  
Device Identification ◽  
Data Transmission Security ◽  
Iot Devices

In the last decade, wireless multimedia device is widely used in many fields, which leads to efficiency improvement, reliability, security, and economic benefits in our daily life. However, with the rapid development of new technologies, the wireless multimedia data transmission security is confronted with a series of new threats and challenges. In physical layer, Radio Frequency Fingerprinting (RFF) is a unique characteristic of IoT devices themselves, which can difficultly be tampered. The wireless multimedia device identification via Radio Frequency Fingerprinting (RFF) extracted from radio signals is a physical-layer method for data transmission security. Just as people’s unique fingerprinting, different Internet of Things (IoT) devices exhibit different RFF which can be used for identification and authentication. In this paper, a wireless multimedia device identification system based on Ensemble Learning is proposed. The key technologies such as signal detection, RFF extraction, and classification model are discussed. According to the theoretical modeling and experiment validation, the reliability and the differentiability of the RFFs are evaluated and the classification results are shown under the real wireless multimedia device environments.

Device Identification System for Corporate Internal Network Visibility in IoT Era

2019 ◽  
Vol 19 (3) ◽  
pp. 51-59
Author(s):  
Dae-Hyo Lee ◽  
◽  
Yong-Kwon Kim ◽  
Dong-Bum Lee ◽  
Hyeob Kim
Keyword(s):  
Identification System ◽  
Device Identification ◽  
Internal Network
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