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Deng, Yingjie, Zhao, Dingxuan, Liu, Tao.  2021.  Self-Triggered Tracking Control of Underactuated Surface Vessels with Stochastic Noise. 2021 International Conference on Security, Pattern Analysis, and Cybernetics(SPAC). :266–273.
This note studies self-triggered tracking control of underactuated surface vessels considering both unknown model dynamics and stochastic noise, where the measured states in the sensors are intermittently transmitted to the controller decided by the triggering condition. While the multi-layer neural network (NN) serves to approximate the unknown model dynamics, a self-triggered adaptive neural model is fabricated to direct the design of control laws. This setup successfully solves the ``jumps of virtual control laws'' problem, which occurs when combining the event-triggered control (ETC) with the backstepping method, seeing [1]–[4]. Moreover, the adaptive model can act as the filter of states, such that the complicated analysis and control design to eliminate the detrimental influence of stochastic noise is no longer needed. Released from the continuous monitoring of the controller, the devised triggering condition is located in the sensors and designed to meet the requirement of stability. All the estimation errors and the tracking errors are proved to be exponentially mean-square (EMS) bounded. Finally, a numerical experiment is conducted to corroborate the proposed strategy.
Shen, Cheng, Liu, Tian, Huang, Jun, Tan, Rui.  2021.  When LoRa Meets EMR: Electromagnetic Covert Channels Can Be Super Resilient. 2021 IEEE Symposium on Security and Privacy (SP). :1304–1317.
Due to the low power of electromagnetic radiation (EMR), EM convert channel has been widely considered as a short-range attack that can be easily mitigated by shielding. This paper overturns this common belief by demonstrating how covert EM signals leaked from typical laptops, desktops and servers are decoded from hundreds of meters away, or penetrate aggressive shield previously considered as sufficient to ensure emission security. We achieve this by designing EMLoRa – a super resilient EM covert channel that exploits memory as a LoRa-like radio. EMLoRa represents the first attempt of designing an EM covert channel using state-of-the-art spread spectrum technology. It tackles a set of unique challenges, such as handling complex spectral characteristics of EMR, tolerating signal distortions caused by CPU contention, and preventing adversarial detectors from demodulating covert signals. Experiment results show that EMLoRa boosts communication range by 20x and improves attenuation resilience by up to 53 dB when compared with prior EM covert channels at the same bit rate. By achieving this, EMLoRa allows an attacker to circumvent security perimeter, breach Faraday cage, and localize air-gapped devices in a wide area using just a small number of inexpensive sensors. To countermeasure EMLoRa, we further explore the feasibility of uncovering EMLoRa's signal using energy- and CNN-based detectors. Experiments show that both detectors suffer limited range, allowing EMLoRa to gain a significant range advantage. Our results call for further research on the countermeasure against spread spectrum-based EM covert channels.
Shamshad, Salman, Obaidat, Mohammad S., Minahil, Saleem, Muhammad Asad, Shamshad, Usman, Mahmood, Khalid.  2021.  Security Analysis on an Efficient and Provably Secure Authenticated Key Agreement Protocol for Fog-Based Vehicular Ad-Hoc Networks. 2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS). :1754–1759.
The maturity of intelligent transportation system, cloud computing and Internet of Things (IoT) technology has encouraged the rapid growth of vehicular ad-hoc networks (VANETs). Currently, vehicles are supposed to carry relatively more storage, on board computing facilities, increased sensing power and communication systems. In order to cope with real world demands such as low latency, low storage cost, mobility, etc., for the deployment of VANETs, numerous attempts have been taken to integrate fog-computing with VANETs. In the recent past, Ma et al. (IEEE Internet of Things, pp 2327-4662, 10. 1109/JIOT.2019.2902840) designed “An Efficient and Provably Secure Authenticated Key Agreement Protocol for Fog-Based Vehicular Ad-Hoc Networks”. Ma et al. claimed that their protocol offers secure communication in fog-based VANETs and is resilient against several security attacks. However, this comment demonstrates that their scheme is defenseless against vehicle-user impersonation attack and reveals secret keys of vehicle-user and fog-node. Moreover, it fails to offer vehicle-user anonymity and has inefficient login phase. This paper also gives some essential suggestions on strengthening resilience of the scheme, which are overlooked by Ma et al.
Kim, Jaewon, Ko, Woo-Hyun, Kumar, P. R..  2021.  Cyber-Security through Dynamic Watermarking for 2-rotor Aerial Vehicle Flight Control Systems. 2021 International Conference on Unmanned Aircraft Systems (ICUAS). :1277–1283.
We consider the problem of security for unmanned aerial vehicle flight control systems. To provide a concrete setting, we consider the security problem in the context of a helicopter which is compromised by a malicious agent that distorts elevation measurements to the control loop. This is a particular example of the problem of the security of stochastic control systems under erroneous observation measurements caused by malicious sensors within the system. In order to secure the control system, we consider dynamic watermarking, where a private random excitation signal is superimposed onto the control input of the flight control system. An attack detector at the actuator can then check if the reported sensor measurements are appropriately correlated with the private random excitation signal. This is done via two specific statistical tests whose violation signifies an attack. We apply dynamic watermarking technique to a 2-rotor-based 3-DOF helicopter control system test-bed. We demonstrate through both simulation and experimental results the performance of the attack detector on two attack models: a stealth attack, and a random bias injection attack.
Zheng, Shengbao, Shu, Shaolong, Lin, Feng.  2021.  Modeling and Control of Discrete Event Systems under Joint Sensor-Actuator Cyber Attacks. 2021 6th International Conference on Automation, Control and Robotics Engineering (CACRE). :216–220.
In this paper, we investigate joint sensor-actuator cyber attacks in discrete event systems. We assume that attackers can attack some sensors and actuators at the same time by altering observations and control commands. Because of the nondeterminism in observation and control caused by cyber attacks, the behavior of the supervised systems becomes nondeterministic and deviates from the target. We define two bounds on languages, an upper-bound and a lower-bound, to describe the nondeterministic behavior. We then use the upper-bound language to investigate the safety supervisory control problem under cyber attacks. After introducing CA-controllability and CA-observability, we successfully solve the supervisory control problem under cyber attacks.
Ren, Yanzhi, Wen, Ping, Liu, Hongbo, Zheng, Zhourong, Chen, Yingying, Huang, Pengcheng, Li, Hongwei.  2021.  Proximity-Echo: Secure Two Factor Authentication Using Active Sound Sensing. IEEE INFOCOM 2021 - IEEE Conference on Computer Communications. :1–10.
The two-factor authentication (2FA) has drawn increasingly attention as the mobile devices become more prevalent. For example, the user's possession of the enrolled phone could be used by the 2FA system as the second proof to protect his/her online accounts. Existing 2FA solutions mainly require some form of user-device interaction, which may severely affect user experience and creates extra burdens to users. In this work, we propose Proximity-Echo, a secure 2FA system utilizing the proximity of a user's enrolled phone and the login device as the second proof without requiring the user's interactions or pre-constructed device fingerprints. The basic idea of Proximity-Echo is to derive location signatures based on acoustic beep signals emitted alternately by both devices and sensing the echoes with microphones, and compare the extracted signatures for proximity detection. Given the received beep signal, our system designs a period selection scheme to identify two sound segments accurately: the chirp period is the sound segment propagating directly from the speaker to the microphone whereas the echo period is the sound segment reflected back by surrounding objects. To achieve an accurate proximity detection, we develop a new energy loss compensation extraction scheme by utilizing the extracted chirp periods to estimate the intrinsic differences of energy loss between microphones of the enrolled phone and the login device. Our proximity detection component then conducts the similarity comparison between the identified two echo periods after the energy loss compensation to effectively determine whether the enrolled phone and the login device are in proximity for 2FA. Our experimental results show that our Proximity-Echo is accurate in providing 2FA and robust to both man-in-the-middle (MiM) and co-located attacks across different scenarios and device models.
Piatkowska, Ewa, Gavriluta, Catalin, Smith, Paul, Andrén, Filip Pröstl.  2020.  Online Reasoning about the Root Causes of Software Rollout Failures in the Smart Grid. 2020 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). :1–7.
An essential ingredient of the smart grid is software-based services. Increasingly, software is used to support control strategies and services that are critical to the grid's operation. Therefore, its correct operation is essential. For various reasons, software and its configuration needs to be updated. This update process represents a significant overhead for smart grid operators and failures can result in financial losses and grid instabilities. In this paper, we present a framework for determining the root causes of software rollout failures in the smart grid. It uses distributed sensors that indicate potential issues, such as anomalous grid states and cyber-attacks, and a causal inference engine based on a formalism called evidential networks. The aim of the framework is to support an adaptive approach to software rollouts, ensuring that a campaign completes in a timely and secure manner. The framework is evaluated for a software rollout use-case in a low voltage distribution grid. Experimental results indicate it can successfully discriminate between different root causes of failure, supporting an adaptive rollout strategy.
Cultice, Tyler, Ionel, Dan, Thapliyal, Himanshu.  2020.  Smart Home Sensor Anomaly Detection Using Convolutional Autoencoder Neural Network. 2020 IEEE International Symposium on Smart Electronic Systems (iSES) (Formerly iNiS). :67–70.
We propose an autoencoder based approach to anomaly detection in smart grid systems. Data collecting sensors within smart home systems are susceptible to many data corruption issues, such as malicious attacks or physical malfunctions. By applying machine learning to a smart home or grid, sensor anomalies can be detected automatically for secure data collection and sensor-based system functionality. In addition, we tested the effectiveness of this approach on real smart home sensor data collected for multiple years. An early detection of such data corruption issues is essential to the security and functionality of the various sensors and devices within a smart home.
Fang, Hao, Zhang, Tao, Cai, Yueming, Zhang, Linyuan, Wu, Hao.  2020.  Detection Schemes of Illegal Spectrum Access Behaviors in Multiple Authorized Users Scenario. 2020 International Conference on Wireless Communications and Signal Processing (WCSP). :933–938.
In this paper, our aim is to detect illegal spectrum access behaviors. Firstly, we detect whether the channel is busy, and then if it is busy, recognizing whether there are illegal users. To get closer to the actual situation, we consider a more general scenario where multiple users are authorized to work on the same channel under certain interference control strategies, and build it as a ternary hypothesis test model using the generalized multi-hypothesis Neyman-Pearson criterion. Considering the various potential combination of multiple authorized users, the spectrum detection process utilizes a two-step detector. We adopt the Generalized Likelihood Ratio Test (GLRT) and the Rao test to detect illegal spectrum access behaviors. What is more, the Wald test is proposed which has a compromise between computational complexity and performance. The relevant formulas of the three detection schemes are derived. Finally, comprehensive and in-depth simulations are provided to verify the effectiveness of the proposed detection scheme that it has the best detection performance under different authorized sample numbers and different performance constraints. Besides, we illustrate the probability of detection of illegal behaviors under different parameters of illegal behaviors and different sets of AUs' states under the Wald test.
Ferdous Khan, M. Fahim, Sakamura, Ken.  2020.  A Context-Policy-Based Approach to Access Control for Healthcare Data Protection. 2020 International Computer Symposium (ICS). :420–425.
Fueled by the emergence of IoT-enabled medical sensors and big data analytics, nations all over the world are widely adopting digitalization of healthcare systems. This is certainly a positive trend for improving the entire spectrum of quality of care, but this convenience is also posing a huge challenge on the security of healthcare data. For ensuring privacy and protection of healthcare data, access control is regarded as one of the first-line-of-defense mechanisms. As none of the traditional enterprise access control models can completely cater to the need of the healthcare domain which includes a myriad of contexts, in this paper, we present a context-policy-based access control scheme. Our scheme relies on the eTRON cybersecurity architecture for tamper-resistance and cryptographic functions, and leverages a context-specific blend of classical discretionary and role-based access models for incorporation into legacy systems. Moreover, our scheme adheres to key recommendations of prominent statutory and technical guidelines including HIPAA and HL7. The protocols involved in the proposed access control system have been delineated, and a proof-of-concept implementation has been carried out - along with a comparison with other systems, which clearly suggests that our approach is more responsive to different contexts for protecting healthcare data.
AlShiab, Ismael, Leivadeas, Aris, Ibnkahla, Mohamed.  2021.  Virtual Sensing Networks and Dynamic RPL-Based Routing for IoT Sensing Services. ICC 2021 - IEEE International Conference on Communications. :1–6.
IoT applications are quickly evolving in scope and objectives while their focus is being shifted toward supporting dynamic users’ requirements. IoT users initiate applications and expect quick and reliable deployment without worrying about the underlying complexities of the required sensing and routing resources. On the other hand, IoT sensing nodes, sinks, and gateways are heterogeneous, have limited resources, and require significant cost and installation time. Sensing network-level virtualization through virtual Sensing Networks (VSNs) could play an important role in enabling the formation of virtual groups that link the needed IoT sensing and routing resources. These VSNs can be initiated on-demand with the goal to satisfy different IoT applications’ requirements. In this context, we present a joint algorithm for IoT Sensing Resource Allocation with Dynamic Resource-Based Routing (SRADRR). The SRADRR algorithm builds on the current distinguished empowerment of sensing networks using recent standards like RPL and 6LowPAN. The proposed algorithm suggests employing the RPL standard concepts to create DODAG routing trees that dynamically adapt according to the available sensing resources and the requirements of the running and arriving applications. Our results and implementation of the SRADRR reveal promising enhancements in the overall applications deployment rate.
Hörmann, Leander B., Pichler-Scheder, Markus, Kastl, Christian, Bernhard, Hans-Peter, Priller, Peter, Springer, Andreas.  2020.  Location-Based Trustworthiness of Wireless Sensor Nodes Using Optical Localization. 2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM). :1–4.
A continually growing number of sensors is required for monitoring industrial processes and for continuous data acquisition from industrial plants and devices. The cabling of sensors represent a considerable effort and potential source of error, which can be avoided by using wireless sensor nodes. These wireless sensor nodes form a wireless sensor network (WSN) to efficiently transmit data to the destination. For the acceptance of WSNs in industry, it is important to build up networks with high trustworthiness. The trustworthiness of the WSN depends not only on a secure wireless communication but also on the ability to detect modifications at the wireless sensor nodes itself. This paper presents the enhancement of the WSN's trustworthiness using an optical localization system. It can be used for the preparation phase of the WSN and also during operation to track the positions of the wireless sensor nodes and detect spatial modification. The location information of the sensor nodes can also be used to rate their trustworthiness.
Huaynacho, Yoni D., Huaynacho, Abel S., Chavez, Yaneth.  2020.  Design and Implementation of a Security System Created by RF Using Controllers with Sensors in EPIE. 2020 X International Conference on Virtual Campus (JICV). :1–4.
This work focuses on the design and implementation of a microcontroller for apply all the knowledge acquired during Engineering Electronics career. In order to improve the knowledge about RF technologies, security system have been created, which increases the number of applications used in these days. This design utilizes light sensors as the end device for detecting any changes of resistance. The results show that the designed system can send and receive data until 100 meters of distance between module sides (receiver-transmitter). This security system designed using PIC 16F84 microcontroller as entire brain of the system with sensors, has been successfully designed and implement considering some factors such as economy, availability of components and durability in the design process.
You, Guoping, Zhu, Yingli.  2020.  Structure and Key Technologies of Wireless Sensor Network. 2020 Cross Strait Radio Science Wireless Technology Conference (CSRSWTC). :1–2.
With the improvement of scientific and technological level in China, wireless sensor network technology has been widely promoted and applied, which has now been popularized to various fields of society from military defense. Wireless sensor network combines sensor technology, communication technology and computer technology together, and has the ability of information collection, transmission and processing. In this paper, the structure of wireless sensor network and node localization technology are briefly introduced, and the key technologies of wireless sensor network development are summarized from the four aspects of energy efficiency, node localization, data fusion and network security. As a detection system of perceiving the physical world, WSN is also facing challenges while developing rapidly.
JOUINI, Oumeyma, SETHOM, Kaouthar.  2020.  Physical Layer Security Proposal for Wireless Body Area Networks. 2020 IEEE 5th Middle East and Africa Conference on Biomedical Engineering (MECBME). :1–5.
Over the last few decades, and thanks to the advancement of embedded systems and wireless technologies, the wireless sensors network (WSN) are increasingly used in many fields. Many researches are being done on the use of WSN in Wireless body Area Network (WBAN) systems to facilitate and improve the quality of care and remote patient monitoring.The broadcast nature of wireless communications makes it difficult to hide transmitted signals from unauthorized users. To this end, Physical layer security is emerging as a promising paradigm to protect wireless communications against eavesdropping attacks. The primary contribution of this paper is achieving a minimum secrecy outage probability by using the jamming technique which can be used by the legitimate communication partner to increase the noise level of the eavesdropper and ensure higher secure communication rate. We also evaluate the effect of additional jammers on the security of the WBAN system.
Lalouani, Wassila, Younis, Mohamed.  2020.  Machine Learning Enabled Secure Collection of Phasor Data in Smart Power Grid Networks. 2020 16th International Conference on Mobility, Sensing and Networking (MSN). :546–553.
In a smart power grid, phasor measurement devices provide critical status updates in order to enable stabilization of the grid against fluctuations in power demands and component failures. Particularly the trend is to employ a large number of phasor measurement units (PMUs) that are inter-networked through wireless links. We tackle the vulnerability of such a wireless PMU network to message replay and false data injection (FDI) attacks. We propose a novel approach for avoiding explicit data transmission through PMU measurements prediction. Our methodology is based on applying advanced machine learning techniques to forecast what values will be reported and associate a level of confidence in such prediction. Instead of sending the actual measurements, the PMU sends the difference between actual and predicted values along with the confidence level. By applying the same technique at the grid control or data aggregation unit, our approach implicitly makes such a unit aware of the actual measurements and enables authentication of the source of the transmission. Our approach is data-driven and varies over time; thus it increases the PMU network resilience against message replay and FDI attempts since the adversary's messages will violate the data prediction protocol. The effectiveness of approach is validated using datasets for the IEEE 14 and IEEE 39 bus systems and through security analysis.
Sun, Yizhen, Lin, Dandan, Song, Hong, Yan, Minjia, Cao, Linjing.  2020.  A Method to Construct Vulnerability Knowledge Graph Based on Heterogeneous Data. 2020 16th International Conference on Mobility, Sensing and Networking (MSN). :740–745.
In recent years, there are more and more attacks and exploitation aiming at network security vulnerabilities. It is effective for us to prevent criminals from exploiting vulnerabilities for attacks and help security analysts maintain equipment security that knows vulnerabilities and threats on time. With the knowledge graph, we can organize, manage, and utilize the massive information effectively in cyberspace. In this paper we construct the vulnerability ontology after analyzing multi-source heterogeneous databases. And the vulnerability knowledge graph is established. Experimental results show that the accuracy of entity recognition for extracting vendor names reaches 89.76%. The more rules used in entity recognition, the higher the accuracy and the lower the error rate.
Desnitsky, Vasily A., Kotenko, Igor V., Parashchuk, Igor B..  2020.  Neural Network Based Classification of Attacks on Wireless Sensor Networks. 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). :284–287.
The paper proposes a method for solving problems of classifying multi-step attacks on wireless sensor networks in the conditions of uncertainty (incompleteness and inconsistency) of the observed signs of attacks. The method aims to eliminate the uncertainty of classification of attacks on networks of this class one the base of the use of neural network approaches to the processing of incomplete and contradictory knowledge on possible attack characteristics. It allows increasing objectivity (accuracy and reliability) of information security monitoring in modern software and hardware systems and Internet of Things networks that actively exploit advantages of wireless sensor networks.
Ashiquzzaman, Md., Mitra, Shuva, Nasrin, Kazi Farjana, Hossain, Md. Sanawar, Apu, Md. Khairul Hasan.  2020.  Advanced Wireless Control amp; Feedback Based Multi-functional Automatic Security System. 2020 IEEE Region 10 Symposium (TENSYMP). :1046–1049.
In this research work, an advanced automatic multifunctional compact security system technology is developed using wireless networking system. The security system provides smart security and also alerts the user to avoid the critical circumstances in the daily security issues is held. This system provides a smart solution to the variety of different problems via remote control by the software name Cayenne. This software provides the user to control the system using smart mobile or computer from all over the world and needs to be connected via internet. The system provides general security for essential purposes as the Motion detecting system alerts for any kind of movement inside the area where it is installed, the gas detecting system alerts the user for any type of gas leakage inside the room and also clearing the leaking gas by exhaust fan automatically, the fire detection system detects instantly when a slight fire is emerged also warning the user with alarm, the LDR system is for electrical door lock and it can be controlled by Cayenne using mobile or computer and lastly a home light system which can be turned on/off by the user of Cayenne. Raspberry Pi has been used to connect and control all the necessary equipment. The system provides the most essential security for home and also for corporate world and it is very simple, easy to operate, and consumes small space.
Mancini, Federico, Bruvoll, Solveig, Melrose, John, Leve, Frederick, Mailloux, Logan, Ernst, Raphael, Rein, Kellyn, Fioravanti, Stefano, Merani, Diego, Been, Robert.  2020.  A Security Reference Model for Autonomous Vehicles in Military Operations. 2020 IEEE Conference on Communications and Network Security (CNS). :1–8.
In a previous article [1] we proposed a layered framework to support the assessment of the security risks associated with the use of autonomous vehicles in military operations and determine how to manage these risks appropriately. We established consistent terminology and defined the problem space, while exploring the first layer of the framework, namely risks from the mission assurance perspective. In this paper, we develop the second layer of the framework. This layer focuses on the risk assessment of the vehicles themselves and on producing a highlevel security design adequate for the mission defined in the first layer. To support this process, we also define a reference model for autonomous vehicles to use as a common basis for the assessment of risks and the design of the security controls.
Asci, Cihan, Wang, Wei, Sonkusale, Sameer.  2020.  Security Monitoring System Using Magnetically-Activated RFID Tags. 2020 IEEE SENSORS. :1–4.
Existing methods for home security monitoring depend on expensive custom battery-powered solutions. In this article, we present a battery-free solution that leverages any off-the-shelf passive radio frequency identification (RFID) tag for real-time entry detection. Sensor consists of a printed RFID antenna on paper, coupled to a magnetic reed switch and is affixed on the door. Opening of the door triggers the reed switch causing RFID signal transmission detected by any off-the-shelf passive RFID reader. This paper shows simulation and experimental results for such magnetically-actuated RFID (or magRFID) opening sensor.
Rieger, Craig, Kolias, Constantinos, Ulrich, Jacob, McJunkin, Timothy R..  2020.  A Cyber Resilient Design for Control Systems. 2020 Resilience Week (RWS). :18–25.
The following topics are dealt with: security of data; distributed power generation; power engineering computing; power grids; power system security; computer network security; voltage control; risk management; power system measurement; critical infrastructures.
Ahmed, Faruk, Mahmud, Md Sultan, Yeasin, Mohammed.  2020.  Assistive System for Navigating Complex Realistic Simulated World Using Reinforcement Learning. 2020 International Joint Conference on Neural Networks (IJCNN). :1–8.
Finding a free path without obstacles or situation that pose minimal risk is critical for safe navigation. People who are sighted and people who are blind or visually impaired require navigation safety while walking on a sidewalk. In this paper we develop assistive navigation on a sidewalk by integrating sensory inputs using reinforcement learning. We train the reinforcement model in a simulated robotic environment which is used to avoid sidewalk obstacles. A conversational agent is built by training with real conversation data. The reinforcement learning model along with a conversational agent improved the obstacle avoidance experience about 2.5% from the base case which is 78.75%.
Lenard, Teri, Bolboacă, Roland, Genge, Bela.  2020.  LOKI: A Lightweight Cryptographic Key Distribution Protocol for Controller Area Networks. 2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP). :513–519.
The recent advancement in the automotive sector has led to a technological explosion. As a result, the modern car provides a wide range of features supported by state of the art hardware and software. Unfortunately, while this is the case of most major components, in the same vehicle we find dozens of sensors and sub-systems built over legacy hardware and software with limited computational capabilities. This paper presents LOKI, a lightweight cryptographic key distribution scheme applicable in the case of the classical invehicle communication systems. The LOKI protocol stands out compared to already proposed protocols in the literature due to its ability to use only a single broadcast message to initiate the generation of a new cryptographic key across a group of nodes. It's lightweight key derivation algorithm takes advantage of a reverse hash chain traversal algorithm to generate fresh session keys. Experimental results consisting of a laboratory-scale system based on Vector Informatik's CANoe simulation environment demonstrate the effectiveness of the developed methodology and its seamless impact manifested on the network.
Castro-Coronado, Habib, Antonino-Daviu, Jose, Quijano-López, Alfredo, Fuster-Roig, Vicente, Llovera-Segovia, Pedro.  2020.  Evaluation of the Detectability of Damper Cage Damages in Synchronous Motors through the Advanced Analysis of the Stray Flux. 2020 IEEE Energy Conversion Congress and Exposition (ECCE). :2058–2063.
The determination of the damper cage health is a matter of great importance in those industries that use large synchronous motors in their processes. In the past, unexpected damages of that element implied economic losses amounting up to several million \$. The problem is that, in the technical literature, there is a lack of non-invasive techniques enabling the reliable condition monitoring of this element. This explains the fact that, in industry, rudimentary methods are still employed to determine its condition. This paper proposes the analysis of the stray flux as a way to determine the condition of the damper cage. The paper shows that the analysis of the stray flux under starting yields characteristic time-frequency signatures of the fault components that can be used to reliably determine the condition of the damper. Moreover, the analysis of the stray flux at steady-state operation under asynchronous mode could give useful information to this end. The paper also analyses the influence of the remanent magnetism in the rotor of some synchronous motors, which can make the damper cage diagnosis more difficult; some solutions to this problem are also suggested in the paper.