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Partially Supervised Anomaly Detection Using Convex Hulls on a 2D Parameter Space
[chapter]
2013
Lecture Notes in Computer Science
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Anomaly detection is the problem of identifying objects appearing to be inconstistent with the remainder of that set of data. ...
Partially supervised methods for anomaly detection are interesting because they only need data labeled as one of the classes (normal or abnormal). ...
There are three fundamental approaches to detect anomalies: 1) unsupervised, 2) supervised and 3) partially supervised. ...
doi:10.1007/978-3-642-40705-5_1
fatcat:okjgw2iq2nbdjap6tc2scvau7q
Spatio-Temporal Network Anomaly Detection by Assessing Deviations of Empirical Measures
2009
IEEE/ACM Transactions on Networking
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We validate our techniques by analyzing real traffic traces with time-stamped anomalies. ...
We introduce an Internet traffic anomaly detection mechanism based on large deviations results for empirical measures. ...
As is common in other statistical anomaly detection approaches, we rely upon observing the system during an anomaly-free period to learn what constitutes normal behavior. ...
doi:10.1109/tnet.2008.2001468
fatcat:2bhcndjmh5d4lai2hzhpbuhsqi
Learning Models of Plant Behavior for Anomaly Detection and Condition Monitoring
2007
2007 International Conference on Intelligent Systems Applications to Power Systems
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This paper proposes the integration of a newly developed anomaly detection technique with an existing diagnosis system. ...
In dealing with the large volumes of data involved, it is possible that faults may not be noticed until serious damage has occurred. ...
Combining Anomaly Detection and Diagnostics The integration of an anomaly detection system with COM-MAS would make the system much more practical and beneficial. ...
doi:10.1109/isap.2007.4441620
fatcat:digdtknttfdrdf7rimpx7menta
Prenatal Sonographic Features of Triploidy
2007
Journal of Medical Ultrasound
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Despite that more than 90% of partial moles are associated with diandric triploidy, placental molar presentation with multiple fetal abnormalities can be observed in cases of trisomy 13 [48] ; therefore ...
However, only one case with cardiac anomalies was detected prenatally from 20 cases of triploidy [11] . ...
doi:10.1016/s0929-6441(08)60034-x
fatcat:u4qmqgxcfbeu7pqza7dgmrghdy
A Novel Approach to Combine Misuse Detection and Anomaly Detection Using POMDP in Mobile Ad-Hoc Networks
2015
International Journal of Information and Electronics Engineering
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We perform the whole system as a partially observed Markov decision process considering both system security and resource constraints. ...
We propose a novel approach to combine the misuse detection with the anomaly detection optimally to save cost associated with resource constraints and security requirements. ...
We formulate whole system as partially observed Markov decision process (POMDP). ...
doi:10.7763/ijiee.2015.v5.538
fatcat:ni4ez4df55gixomqevc4igmpym
Inductive Anomaly Detection on Attributed Networks
2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
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Nonetheless, most of the existing efforts do not naturally generalize to unseen nodes, leading to the fact that people have to retrain the detection model from scratch when dealing with newly observed ...
In this study, we propose to tackle the problem of inductive anomaly detection on attributed networks with a novel unsupervised framework: Aegis (adversarial graph differentiation networks). ...
For an inductive anomaly detection model, its training network is only partially observed. ...
doi:10.24963/ijcai.2020/179
dblp:conf/ijcai/DingLAL20
fatcat:ayeg35tdazgydkpkot44k5qwse
SunDown: Model-driven Per-Panel Solar Anomaly Detection for Residential Arrays
[article]
2020
arXiv
pre-print
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faults with 97.2% accuracy. ...
Our results also show that SunDown is able to detect and classify faults, including from snow cover, leaves and debris, and electrical failures with 99.13% accuracy, and can detect multiple concurrent ...
Such a modeldriven approach only uses the observed output of panels to detect anomalies-no other instruments or sensors are needed for anomaly detection unlike some other approaches [6] . ...
arXiv:2005.12181v1
fatcat:okhjhmhgpvdvpgtiel5zxfqyfi
Comparison and Adaptation of Two Strategies for Anomaly Detection in Load Profiles Based on Methods from the Fields of Machine Learning and Statistics
2021
Open Journal of Energy Efficiency
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Therefore, in this study two strategies for anomaly detection in load profiles are evaluated. ...
Within this program, Limón GmbH is developing software solutions in cooperation with the University of Kassel to identify efficiency potentials in load profiles by means of automated anomaly detection. ...
For the PEWMA based strategy 2 it can be observed that the efficacy of the anomaly detection is influenced by the context in which the anomalies are located. ...
doi:10.4236/ojee.2020.102003
fatcat:cj4wpr6f5zelpfjw6ov63blxai
CIoTA: Collaborative IoT Anomaly Detection via Blockchain
[article]
2018
arXiv
pre-print
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This approach is vulnerable to adversarial attacks since all observations are assumed to be benign while training the anomaly detection model. ...
In this paper, we propose CIoTA, a lightweight framework that utilizes the blockchain concept to perform distributed and collaborative anomaly detection for devices with limited resources. ...
Assume that all IoT devices of the same type simultaneously begin training their own anomaly detection model, based on their own locally observed behaviors. ...
arXiv:1803.03807v2
fatcat:ewmcyqrkxre33jqja4eg734ccu
Chromosomal Microarray Analysis in Pregnancies With Corpus Callosum or Posterior Fossa Anomalies
2021
Neurology: Genetics
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are observed. ...
ObjectiveWe investigated the detection rate of clinically significant chromosomal microarray analysis (CMA) results in pregnancies with sonographic diagnosis of fetal corpus callosum anomalies (CCA) or ...
Of them, only 4/9 (44.4%) could have been detected by standard karyotype, and none by NIPS. VUS was observed in a single case. ...
doi:10.1212/nxg.0000000000000585
pmid:34079909
pmcid:PMC8163489
fatcat:bwqcrvkboberbbh657jl6fepgq
Efficient Anomaly Detection Using Self-Supervised Multi-Cue Tasks
[article]
2022
arXiv
pre-print
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Anomaly detection is important in many real-life applications. Recently, self-supervised learning has greatly helped deep anomaly detection by recognizing several geometric transformations. ...
Finally, we evaluate our method on an extensive protocol composed of various anomaly types, from object anomalies, style anomalies with fine-grained classification to local anomalies with face anti-spoofing ...
To detect whether or not an observation x is an anomaly, we produce the OOD scores of the re-colorization and the nsp sampled permutations along with tint rotation tasks. ...
arXiv:2111.12379v2
fatcat:lb5vav3ebvhznnmyechdzgywdm
Outage Detection in Partially Observable Distribution Systems using Smart Meters and Generative Adversarial Networks
[article]
2019
arXiv
pre-print
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In this paper, we present a novel data-driven approach to detect outage events in partially observable distribution systems by capturing the changes in smart meters' (SMs) data distribution. ...
To achieve this, first, a breadth-first search (BFS)-based mechanism is proposed to decompose the network into a set of zones that maximize outage location information in partially observable systems. ...
Index Terms-Outage detection, generative adversarial networks, zone, partially observable system, smart meter.
I. ...
arXiv:1912.04992v1
fatcat:atb5la2mkzflhivzlqrvz52diu
Diagnosing Device-Specific Anomalies in Cellular Networks
2014
Proceedings of the 2014 CoNEXT on Student Workshop - CoNEXT Student Workshop '14
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One of these relates to the detection and diagnosis of network traffic anomalies caused by specific devices and applications. ...
As case study, we present the analysis of a large scale traffic anomaly observed in a real cellular network, linked to smartphones. ...
We notice that some of the observed diagnostic signals are correlated in a minor way to the anomaly. ...
doi:10.1145/2680821.2680831
dblp:conf/conext/SchiavoneRFC14
fatcat:e2lb6qfglrhjrpb5u4cmb5ohlq
A Large Deviations Approach to Statistical Traffic Anomaly Detection
2006
Proceedings of the 45th IEEE Conference on Decision and Control
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Index Terms-Network security, intrusion detection, statistical anomaly detection, method of types, large deviations. ...
We validate our techniques by analyzing real traffic traces with time-stamped anomalies. ...
Acknowledgments: We are grateful to Anukool Lakhina (Boston University) for providing us with the Abilene data set and for very helpful discussions. ...
doi:10.1109/cdc.2006.377716
dblp:conf/cdc/PaschalidisS06
fatcat:kesjffsb7naxdex7zyqqbpqhe4
Fetal US and MRI in detection of craniospinal anomalies with postnatal correlation: single-center experience
2021
Turkish Journal of Medical Sciences
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anomalies on fetal US and later on imaged with MRI were evaluated and in 179 of those cases prenatal imaging findings were compared with postnatal findings. ...
A total of 191 fetal craniospinal anomalies were detected in 179 pregnant women. MRI and US diagnosis were completely correct in 145 (75.9%) and 112 (58.6%), respectively. ...
MRI findings were partially compatible with US in 19 5 (6%) cases. ...
doi:10.3906/sag-2011-122
pmid:33517612
pmcid:PMC8283491
fatcat:5xzezbnwufgkdc3njo5csw4pte
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