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Sequential Anomaly Detection Using Wireless Sensor Networks in Unknown Environment [chapter]

Yuanyuan Li, Michael Thomason, Lynne E. Parker
2014 Human Behavior Understanding in Networked Sensing  
Anomaly detection is an important problem for environment, fault diagnosis and intruder detection in Wireless Sensor Networks (WSNs).  ...  We present a machine learning (ML) framework that is suitable for WSNs to sequentially detect sensory level anomalies and time-related anomalies in an unknown environment.  ...  The main objective of this chapter is to propose a distributed sequential anomaly detection system in an unknown environment using a WSN.  ... 
doi:10.1007/978-3-319-10807-0_5 fatcat:64w4xspjlrftzjirybgnafn5gy

On-Device Learning: A Neural Network Based Field-Trainable Edge AI [article]

Hiroki Matsutani, Mineto Tsukada, Masaaki Kondo
2022 arXiv   pre-print
Experiments using vibration patterns of rotating machines demonstrate that retraining by the on-device learning significantly improves an anomaly detection accuracy at a noisy environment while saving  ...  In real-world edge AI applications, their accuracy is often affected by various environmental factors, such as noises, location/calibration of sensors, and time-related changes.  ...  Anomaly detection is conducted at the noisy environment.  ... 
arXiv:2203.01077v2 fatcat:s2qg7jpcz5cmxaskjiay5iftsy

A Survey on Data Mining Approaches for Network Intrusion Detection System

Anirudha A., Mangesh G., Ritesh V.
2017 International Journal of Computer Applications  
Network intrusion detection is the process of monitoring the events occurring in a computing system or network and analysing them for signs of intrusions.  ...  By using these set of relevant system features to compute classifiers that recognize anomalies & known intrusion.  ...  The term sensor is typically used for intrusion detection systems that monitor networks, including network-based, wireless, and network behaviour analysis technologies.  ... 
doi:10.5120/ijca2017912615 fatcat:2qtbbqz7ajdhvixfk6j77e76zq

Examination of Different Intrusion Detection System in Wireless Sensor Network Environment

2019 International journal of recent technology and engineering  
But Wireless Sensor Networks are susceptible to a large number of attacks due to its wireless nature. Security plays an important role for many real-world applications in WSNs.  ...  To develop secured WSNs, the intrusions should be detected before the attackers affect the sensor network.  ...  Intrusion detection in wireless sensor network consumes high energy for the detection process.  ... 
doi:10.35940/ijrte.d1122.1284s219 fatcat:dgladfogrzgyhnh72kss4nkdqm

Detecting time-related changes in Wireless Sensor Networks using symbol compression and Probabilistic Suffix Trees

YuanYuan Li, M Thomason, L E Parker
2010 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems  
Our research focuses on anomaly detection problems in unknown environments using Wireless Sensor Networks (WSN).  ...  Finally, a Variable Memory Markov (VMM) model in the form of a Probabilistic Suffix Tree (PST) is used to model and detect time-related anomalies in the environment.  ...  INTRODUCTION Wireless Sensor Networks (WSNs) are widely used in environment monitoring applications.  ... 
doi:10.1109/iros.2010.5649660 dblp:conf/iros/LiTP10 fatcat:uwfxqgpoabdq7m4irjnovf6ml4

Intelligent Prediction and Rural Financial Development Based on Abnormal Detection of Sensor Data

Jiong Liu, Akshi Kumar
2022 Computational Intelligence and Neuroscience  
The two main functions of wireless sensor network security are abnormal node detection and data anomaly detection. These two directions are mutually independent and complementary.  ...  Wireless sensor network is a multisensor wireless network system, which consists of multiple sensors and is configured independently.  ...  [13] . e literature introduced the basic problems of wireless sensor networks, introduced the anomaly detection datasets commonly used in wireless sensor networks, and explained the architecture of wireless  ... 
doi:10.1155/2022/6404825 pmid:35265112 pmcid:PMC8901299 fatcat:ye54vlwng5co3pn33s6nbgudke

Security Issues and Challenges in Event-Driven Wireless Sensor Networks

Lu Lu Liang, Qi Zou, Guang Yang, Lei Shi
2013 Advanced Materials Research  
Recently, wireless sensor networks (WSNs) have attracted a lot of attention from the network research community, especially in the aspect of event-driven wireless sensor networks (EWSNs), such as adversary  ...  locating, fire detection and so on.As the nature of importance of event monitoring, security has to be assured in both of communication and processing.  ...  The rule-based IDS is used to detect know attacks of intrusion [27] , while anomaly-based IDS is used to detect unknown intrusion [28] .  ... 
doi:10.4028/ fatcat:vkejfrc4fjbx3jhmmyxrzvapm4

IoTGaze: IoT Security Enforcement via Wireless Context Analysis [article]

Tianbo Gu, Zheng Fang, Allaukik Abhishek, Hao Fu, Pengfei Hu, Prasant Mohapatra
2020 arXiv   pre-print
We propose a novel framework called IoTGaze, which can discover potential anomalies and vulnerabilities in the IoT system via wireless traffic analysis.  ...  In this work, we creatively change the angle to consider security problems from a wireless context perspective.  ...  We utilize limited features extracted from the encrypted wireless traffic and generate effective fingerprints to detect IoT events. (2) How to use the sequential packets to generate the sequential IoT  ... 
arXiv:2006.15827v1 fatcat:pvp4sd3vlnfxbne4u4zeacm4u4

Trust-assisted anomaly detection and localization in wireless sensor networks

Shanshan Zheng, John S. Baras
2011 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks  
Fast anomaly detection and localization is critical to ensure effective functioning of wireless sensor networks.  ...  In this paper, we propose a trust-assisted framework for detecting and localizing network anomalies in a hierarchical sensor network.  ...  CONCLUSIONS In this paper, we present a trust-assisted framework for anomaly detection and localization in resource constrained wireless sensor networks using end-to-end measurements.  ... 
doi:10.1109/sahcn.2011.5984922 dblp:conf/secon/ZhengB11 fatcat:c5aesrdlxvhxjij3skohdzjpoe

Network anomaly detection research: a survey

Kurniabudi Kurniabudi, Benni Purnama, Sharipuddin Sharipuddin, Darmawijoyo Darmawijoyo, Deris Stiawan, Samsuryadi Samsuryadi, Ahmad Heryanto, Rahmat Budiarto
2019 Indonesian Journal of Electrical Engineering and Informatics (IJEEI)  
Researchers in [62] , propose an ensemble of five binary classifiers to detect anomalies from wireless sensor network.  ...  Research in [37] and [38] each introduces detecting anomalous traffic, and special anomaly detection of wireless sensor networks, respectively.  ... 
doi:10.11591/ijeei.v7i1.773 fatcat:pvvz2u47sfajfiddvpiyt55ely

An edge-cloud collaboration architecture for pattern anomaly detection of time series in wireless sensor networks

Cong Gao, Ping Yang, Yanping Chen, Zhongmin Wang, Yue Wang
2021 Complex & Intelligent Systems  
AbstractWith large deployment of wireless sensor networks, anomaly detection for sensor data is becoming increasingly important in various fields.  ...  In production environments, the analysis of pattern anomaly is the most rewarding one.  ...  However, the migration of anomaly detection task reckons without unknown correlation among time series in wireless sensor networks.  ... 
doi:10.1007/s40747-021-00442-6 fatcat:nc77ij3nx5glvi7qoxg2ba6hcy

Denial of Service Defence for Resource Availability in Wireless Sensor Networks

Opeyemi A. Osanaiye, Attahiru S. Alfa, Gerhard P. Hancke
2018 IEEE Access  
Index Terms-Denial of Service (DoS), detection techniques, intrusion detection system (IDS), resource availability, resource depletion, wireless sensor networks (WSNs).  ...  Common applications include its use for military operations, monitoring environmental conditions (such as volcano detection, agriculture and management), distributed control systems, healthcare and detection  ...  ACKNOWLEDGEMENTS This research is funded by the Advanced Sensor Networks SARChI Chair program, co-hosted by University of Pretoria (UP) and Council for Scientific and Industrial Research (CSIR), through  ... 
doi:10.1109/access.2018.2793841 fatcat:chajqpv6arfphif46zj3w2f5da

Deep Predictive Coding Neural Network for RF Anomaly Detection in Wireless Networks [article]

Nistha Tandiya, Ahmad Jauhar, Vuk Marojevic, Jeffrey H. Reed
2018 arXiv   pre-print
Intrusion detection has become one of the most critical tasks in a wireless network to prevent service outages that can take long to fix.  ...  This paper proposes an anomaly detection methodology for wireless systems that is based on monitoring and analyzing radio frequency (RF) spectrum activities.  ...  anomaly detection in wireless networks.  ... 
arXiv:1803.06054v1 fatcat:minngrp5yzf6fkw3bslkdf6eyu

Intrusion Detection Techniques in Wireless Sensor Network using Data Mining Algorithms: Comparative Evaluation Based on Attacks Detection

2015 International Journal of Advanced Computer Science and Applications  
Wireless sensor network (WSN) consists of sensor nodes.  ...  , and used the most relevant attributes for the classification process.  ...  This paper has compared and evaluated the newest anomaly detection intrusion techniques used in wireless sensor network, to improve the efficient technique for IDS in WSN.  ... 
doi:10.14569/ijacsa.2015.060922 fatcat:vfkdneylivea3dqrszneipi4fq

The Selective Forwarding Attack in Sensor Networks: Detections and Countermeasures

Wazir Zada Khan, Yang Xiang, Mohammed Y Aalsalem, Quratulain Arshad
2012 International Journal of Wireless and Microwave Technologies  
Selective forwarding attack is one of the harmful attacks against sensor networks and can affect the whole sensor network communication.  ...  Sensor networks are becoming closer towards wide-spread deployment so security issues become a vital concern.  ...  Detecting Selective Forwarding Attacks in Wireless Sensor Networks using SVMs K.  ... 
doi:10.5815/ijwmt.2012.02.06 fatcat:fjsjva2tljhrrcmz6ilypc64aq
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