17.1.3.8.12 Intruders, Intrusions, Intrusion Detection, Threats

Chapter Contents (Back)
Activity Recognition. Intrusion Detection. Physical, not network, which is filed elsewhere.

Vidient Systems, Inc.,
2007. Vendor, Surveillance.
WWW Link. Intrusion detection. Spin off from NEC research labs.

Viion Systems,
2009.
WWW Link. Vendor, Intrusion Detection. Actually, senses when someone leaves the computer. Presence detection. Montreal.

Mick, P.[Peter], Beck, D.[Donald],
Video-type universal motion and intrusion detection system,
US_Patent3,988,533, Oct 26, 1976
WWW Link. BibRef 7610

Harman, R.K.[R. Keith], Patchell, J.W.[John W.],
Perimeter surveillance system,
US_Patent4,249,207, Feb 3, 1981
WWW Link. BibRef 8102

Willoughby, J.S.[Jon S.],
Clock synchronized digital TV motion detector,
US_Patent5,008,745, Apr 16, 1991
WWW Link. BibRef 9104

Kuno, Y.[Yoshinori], Fukui, K.[Kazuhiro], Nakai, H.[Hiroaki],
Display monitoring system for detecting and tracking an intruder in a monitor area,
US_Patent5,243,418, Sep 7, 1993
WWW Link. BibRef 9309

Buccola, C.S.[Charles S.], Kolb, L.M.[Lawrence M.],
Automatically adjustable and self-testing dual technology intrusion detection system for minimizing false alarms,
US_Patent5,331,308, Jul 19, 1994
WWW Link. BibRef 9407

Freeman, E.J.[Edward J.],
Motion detection system,
US_Patent5,396,284, Mar 7, 1995
WWW Link. BibRef 9503

Ruckh, R.[Rainer], Argast, M.[Martin],
Method for detecting objects in a monitored area,
US_Patent5,539,199, Jul 23, 1996
WWW Link. BibRef 9607

Otsuki, A.[Akira],
Anomaly surveillance device,
US_Patent5,512,942, Apr 30, 1996
WWW Link. BibRef 9604

Aviv, D.G.[David G.],
Abnormality detection and surveillance system,
US_Patent5,666,157, Sep 9, 1997
WWW Link. BibRef 9709
And: US_Patent6,028,626, Feb 22, 2000
WWW Link. More change detection. BibRef

Guthrie, T.C.[Thomas C.],
Object tracking system for monitoring a controlled space,
US_Patent5,973,732, Oct 26, 1999
WWW Link. BibRef 9910

Baxter, K.M.[Keith M.],
Intruder alarm with trajectory display,
US_Patent5,966,074, Oct 12, 1999
WWW Link. BibRef 9910

Kuwano, Y.[Yukinori], Okino, T.[Toshiyuki], Ikeda, T.[Takashi], Arisawa, M.[Masato], Fujita, H.[Hideto], Murata, H.[Haruhiko],
Monitoring system and imaging system,
US_Patent6,456,320, Sep 24, 2002
WWW Link. Detect entering person. BibRef 0209

Ito, W.[Wataru], Ueda, H.[Hirotada], Okada, T.[Toshimichi], Endo, M.[Miyuki],
Method for tracking entering object and apparatus for tracking and monitoring entering object,
US_Patent6,404,455, Jun 11, 2002
WWW Link. BibRef 0206

Ito, W.[Wataru], Ueda, H.[Hirotada], Yamada, H.[Hiromasa],
Method of distinguishing a moving object and apparatus of tracking and monitoring a moving object,
US_Patent6,445,409, Sep 3, 2002
WWW Link. BibRef 0209

Ito, W.[Wataru], Ueda, H.[Hirotada],
Method and apparatus for automatically detecting intrusion object into view of image pickup device,
US_Patent6,754,367, Jun 22, 2004
WWW Link. BibRef 0406

Morellas, V., Pavlidis, I., Tsiamyrtzis, P.,
DETER: Detection of events for threat evaluation and recognition,
MVA(15), No. 1, October 2003, pp. 29-45.
Springer DOI 0310
BibRef

Yeung, D.Y.[Dit-Yan], Ding, Y.X.[Yu-Xin],
Host-based intrusion detection using dynamic and static behavioral models,
PR(36), No. 1, January 2003, pp. 229-243.
Elsevier DOI 0210
BibRef

Yeung, D.Y.[Dit-Yan], Chow, C.,
Parzen-window network intrusion detectors,
ICPR02(IV: 385-388).
IEEE DOI 0211
BibRef

Ito, W.[Wataru], Ueda, H.[Hirotada],
Intruding object monitoring method and intruding object monitoring system,
US_Patent6,812,835, Nov 2, 2004
WWW Link. BibRef 0411

Gutta, S.[Srinivas], Brodsky, T.[Tomas],
Intruder detection through trajectory analysis in monitoring and surveillance systems,
US_Patent6,593,852, Jul 15, 2003
WWW Link. BibRef 0307

Rao, R.[Ravishankar],
System and method for alarm generation based on the detection of the presence of a person,
US_Patent7,109,861, Sep 19, 2006
WWW Link. BibRef 0609

Han, M.[Mei], Gong, Y.H.[Yi-Hong], Tao, H.[Hai],
Video surveillance system that detects predefined behaviors based on predetermined patterns of movement through zones,
US_Patent7,088,846, Aug 8, 2006
WWW Link. BibRef 0608
And:
Video surveillance system with object detection and probability scoring based on object class,
US_Patent7,127,083, Oct 24, 2006
WWW Link. BibRef
And:
Video surveillance system with rule-based reasoning and multiple-hypothesis scoring,
US_Patent7,136,507, Nov 14, 2006
WWW Link. BibRef
And:
Video surveillance system in which trajectory hypothesis spawning allows for trajectory splitting and/or merging,
US_Patent7,148,912, Dec 12, 2006
WWW Link. BibRef

Jiang, S.Y.[Sheng-Yi], Song, X.Y.[Xiao-Yu], Wang, H.[Hui], Han, J.J.[Jian-Jun], Li, Q.H.[Qing-Hua],
A clustering-based method for unsupervised intrusion detections,
PRL(27), No. 7, May 2006, pp. 802-810.
Elsevier DOI Clustering; Threshold; Outlier factor; Intrusion detection 0604
BibRef

Alkelai, M.[Moshe], Kartoun, D.[David],
Dual sensor intruder alarm,
US_Patent7,126,476, Oct 24, 2006
WWW Link. IR and visible. BibRef 0610

Meniere, J.[Jerome], Lefebure, M.[Martin], Guichard, F.[Frederic], Belahmidi, A.[Abdelmounim],
Method for detecting new objects in an illuminated scene,
US_Patent7,302,081, Nov 27, 2007
WWW Link. BibRef 0711

Meng, L.M.[Ling-Min], di Poala, W.S.[William S.], Grimm, W.M.[Wolfgang M.],
Dual sensing intrusion detection method and system with state-level fusion,
US_Patent7,262,697, Aug 28, 2007
WWW Link. BibRef 0708

di Poala, W.S.[William S.],
Method and apparatus for reducing false alarms due to white light in a motion detection system,
US_Patent7,161,152, Jan 9, 2007
WWW Link. with IR BibRef 0701

Niwa, A.[Akimasa],
Moving body detecting apparatus,
US_Patent7,433,494, Oct 7, 2008
WWW Link. intrusion, breakin. BibRef 0810

Woo, H., Jung, Y.M., Kim, J.G., Seo, J.K.,
Environmentally Robust Motion Detection for Video Surveillance,
IP(19), No. 11, November 2010, pp. 2838-2848.
IEEE DOI 1011
To generate motion alarms. BibRef

Burghouts, G.J., Marck, J.W.,
Reasoning About Threats: From Observables to Situation Assessment,
SMC-C(41), No. 5, September 2011, pp. 608-616.
IEEE DOI 1109
BibRef

Carvalho, P.[Pedro], Oliveira, T.[Telmo], Ciobanu, L.[Lucian], Gaspar, F.[Filipe], Teixeira, L.F.[Luís F.], Bastos, R.[Rafael], Cardoso, J.S.[Jaime S.], Dias, M.S.[Miguel S.], Côrte-Real, L.[Luís],
Analysis of object description methods in a video object tracking environment,
MVA(24), No. 6, August 2013, pp. 1149-1165.
Springer DOI 1307
BibRef

Pereira, A.[Américo], Familiar, A.[Alexandra], Moreira, B.[Bruno], Terroso, T.[Teresa], Carvalho, P.[Pedro], Côrte-Real, L.[Luís],
Video Based Group Tracking and Management,
ICIAR16(423-430).
Springer DOI 1608
BibRef

Teixeira, L.F.[Luis F.], Carvalho, P.[Pedro], Cardoso, J.S.[Jaime S.], Corte-Real, L.[Luis],
Automatic description of object appearances in a wide-area surveillance scenario,
ICIP12(1609-1612).
IEEE DOI 1302
BibRef

Mitchell, R., Chen, I.R.[Ing-Ray],
Adaptive Intrusion Detection of Malicious Unmanned Air Vehicles Using Behavior Rule Specifications,
SMCS(44), No. 5, May 2014, pp. 593-604.
IEEE DOI 1405
ant colony optimisation BibRef

Lin, C., Song, K.,
Probability-Based Location Aware Design and On-Demand Robotic Intrusion Detection System,
SMCS(44), No. 6, June 2014, pp. 705-715.
IEEE DOI 1406
Mobile nodes BibRef

Penmetsa, S.[Surya], Minhuj, F.[Fatima], Singh, A.[Amarjot], Omkar, S.N.,
Autonomous UAV for Suspicious Action Detection using Pictorial Human Pose Estimation and Classification,
ELCVIA(13), No. 1, 2014, pp. xx-yy.
DOI Link 1407
BibRef

Burghouts, G.J., Schutte, K., ten Hove, R.J.M., van den Broek, S.P., Baan, J., Rajadell, O., van Huis, J.R., van Rest, J., Hanckmann, P., Bouma, H., Sanroma, G., Evans, M., Ferryman, J.,
Instantaneous threat detection based on a semantic representation of activities, zones and trajectories,
SIViP(8), No. S1, December 2014, pp. 191-200.
Springer DOI 1411
BibRef

Sanromà, G.[Gerard], Patino, L.[Luis], Burghouts, G.J.[Gertjan J.], Schutte, K.[Klamer], Ferryman, J.M.[James M.],
A unified approach to the recognition of complex actions from sequences of zone-crossings,
IVC(32), No. 5, 2014, pp. 363-378.
Elsevier DOI 1404
Threat recognition
See also Spatio-temporal layout of human actions for improved bag-of-words action detection. BibRef

Shannon, T.[Thomas], Wiltshire, B.[Ben], Spier, E.[Emmet],
Detection of people in military and security context images,
SPIE(Newsroom), September 2, 2014
DOI Link 1410
An autonomous person-detection solution could help alert surveillance operators to potential issues, reducing the cognitive burden and achieving more with less manpower. BibRef

van den Broek, S.P.[Sebastiaan P.], ten Hove, R. .J.M.[R. Johan-Martijn], den Hollander, R.[Richard], Burghouts, G.J.[Gertjan J.],
Automated recognition of human activities in video streams in real time,
SPIE(Newsroom), June 30, 2014
DOI Link 1407
A system using standard surveillance cameras senses human activities relevant for early detection of military threats. BibRef

Sanromà, G.[Gerard], Burghouts, G.J.[Gertjan J.], Schutte, K.[Klamer],
Recognition of Long-Term Behaviors by Parsing Sequences of Short-Term Actions with a Stochastic Regular Grammar,
SSSPR12(225-233).
Springer DOI 1211
BibRef

Hanckmann, P.[Patrick], Schutte, K.[Klamer], Burghouts, G.J.[Gertjan J.],
Automated Textual Descriptions for a Wide Range of Video Events with 48 Human Actions,
VECTaR12(I: 372-380).
Springer DOI 1210
BibRef

Riffo, V., Mery, D.,
Automated Detection of Threat Objects Using Adapted Implicit Shape Model,
SMCS(46), No. 4, April 2016, pp. 472-482.
IEEE DOI 1604
Blades BibRef

Al-Yaseen, W.L.[Wathiq Laftah], Othman, Z.A.[Zulaiha Ali], Nazri, M.Z.A.[Mohd Zakree Ahmad],
Real-time multi-agent system for an adaptive intrusion detection system,
PRL(85), No. 1, 2017, pp. 56-64.
Elsevier DOI 1612
Adaptive intrusion detection system BibRef

Zhou, C., Huang, S., Xiong, N., Yang, S., Li, H., Qin, Y., Li, X.,
Design and Analysis of Multimodel-Based Anomaly Intrusion Detection Systems in Industrial Process Automation,
SMCS(45), No. 10, October 2015, pp. 1345-1360.
IEEE DOI 1509
Automation BibRef

Huang, K., Zhang, Q., Zhou, C., Xiong, N., Qin, Y.,
An Efficient Intrusion Detection Approach for Visual Sensor Networks Based on Traffic Pattern Learning,
SMCS(47), No. 10, October 2017, pp. 2704-2713.
IEEE DOI 1709
Computational modeling, Feature extraction, Intrusion detection, Self-organizing feature maps, Training, Visualization, Wireless sensor networks, Active learning, big data, intrusion detection, self-organizing map (SOM), visual sensor networks (VSNs) BibRef

Hu, K.[Kelu], Zheng, C.L.[Chun-Lei], He, W.[Wei], Bao, X.H.[Xing-He], Wang, Y.G.[Ying-Guan],
Multi-Channels LSTM Networks for Fence Activity Classification,
IEICE(E101-D), No. 8, August 2018, pp. 2173-2177.
WWW Link. 1808
Sensor attached to a fence, detect intrusions. BibRef

Yang, A.[Aimin], Liu, H.X.[Hui-Xiang], Chen, Y.J.[Yong-Jie], Zhang, C.Y.[Chun-Ying], Yang, K.[Ke],
Digital video intrusion intelligent detection method based on narrowband Internet of Things and its application,
IVC(97), 2020, pp. 103914.
Elsevier DOI 2005
NB-IoT, Video intrusion detection, Support vector machines BibRef

Villamizar, M., Martínez-González, A., Canévet, O., Odobez, J.M.,
WatchNet++: efficient and accurate depth-based network for detecting people attacks and intrusion,
MVA(31), No. 6, August 2020, pp. Article41.
Springer DOI 2008
BibRef

Zhao, H.W.[Hong-Wei], Li, M.Z.[Ming-Zhao], Zhao, H.Y.[Hao-Yu],
Artificial intelligence based ensemble approach for intrusion detection systems,
JVCIR(71), 2020, pp. 102736.
Elsevier DOI 2009
Artificial Intelligence, Ensembles, Internet attacks, Neural networks BibRef

Miao, Y.M.[Yi-Ming], Tang, Y.[Yuan], Alzahrani, B.A.[Bander A.], Barnawi, A.[Ahmed], Alafif, T.[Tarik], Hu, L.[Long],
Airborne LiDAR Assisted Obstacle Recognition and Intrusion Detection Towards Unmanned Aerial Vehicle: Architecture, Modeling and Evaluation,
ITS(22), No. 7, July 2021, pp. 4531-4540.
IEEE DOI 2107
Laser radar, Unmanned aerial vehicles, Intrusion detection, Clustering algorithms, Monitoring, Image edge detection, unmanned aerial vehicle BibRef

Gong, X.[Xiao], Chen, X.[Xi], Zhong, Z.D.[Zhang-Dui], Chen, W.[Wei],
Enhanced Few-Shot Learning for Intrusion Detection in Railway Video Surveillance,
ITS(23), No. 8, August 2022, pp. 11301-11313.
IEEE DOI 2208
Rail transportation, Intrusion detection, Task analysis, Training, Video surveillance, Streaming media, Cameras, video surveillance BibRef

Chakraborty, M.[Mainak], Kumawat, H.C.[Harish C.], Dhavale, S.V.[Sunita Vikrant], Raj A, A.B.[Arockia Bazil],
Application of DNN for radar micro-doppler signature-based human suspicious activity recognition,
PRL(162), 2022, pp. 1-6.
Elsevier DOI 2210
CW radar, Human activity recognition, Micro-Doppler signatures, Spectrogram, Dataset, Convolutional neural network BibRef

Mansour, Z.[Ziad], Lounis, K.[Karim], Ding, S.H.H.[Steven H. H.], Zulkernine, M.[Mohammad],
AdaptIDS: Adaptive Intrusion Detection for Mission-Critical Aerospace Vehicles,
ITS(23), No. 12, December 2022, pp. 23459-23473.
IEEE DOI 2212
Military standards, Security, Intrusion detection, Protocols, Aerospace electronics, Data transfer, Synchronization, security analytics BibRef

Wang, Y.[Yalu], Li, J.[Jie], Zhao, W.[Wei], Han, Z.J.[Zhi-Jie], Zhao, H.[Hang], Wang, L.[Lei], He, X.[Xin],
N-STGAT: Spatio-Temporal Graph Neural Network Based Network Intrusion Detection for Near-Earth Remote Sensing,
RS(15), No. 14, 2023, pp. 3611.
DOI Link 2307
BibRef

Hassler, S.C.[Samuel Chase], Mughal, U.A.[Umair Ahmad], Ismail, M.[Muhammad],
Cyber-Physical Intrusion Detection System for Unmanned Aerial Vehicles,
ITS(25), No. 6, June 2024, pp. 6106-6117.
IEEE DOI 2406
Autonomous aerial vehicles, Feature extraction, Cyberattack, Complexity theory, Support vector machines, Training data, and machine learning BibRef

Jiang, Z.[Zhufeng], Wang, H.[Hui], Luo, G.L.[Guo-Liang], Fan, Z.Z.[Zi-Zhu], Xu, L.[Lu],
Pedestrian Intrusion Detection in Railway Station Based on Mirror Translation Attention and Feature Pooling Enhancement,
SPLetters(31), 2024, pp. 2730-2734.
IEEE DOI 2410
Pedestrians, Feature extraction, Rail transportation, Computational modeling, Dictionaries, Convolution, Mirrors, Encoding, self-attention BibRef

Khorramshahi, P.[Pirazh], Wu, Z.[Zhe], Wang, T.C.[Tian-Chen], Deluccia, L.[Luke], Wang, H.C.[Hong-Cheng],
Lightweight Delivery Detection on Doorbell Cameras,
WACV24(6947-6956)
IEEE DOI 2404
Training, Uncertainty, Computational modeling, System performance, Pipelines, Predictive models, Cameras, Algorithms, Commercial / retail BibRef

Li, X.M.[Xiao-Min], Li, X.R.[Xin-Ran], Gu, S.M.[Shu-Ming],
An intrusion monitoring system design based on 3D face recognition,
CVIDL23(280-283)
IEEE DOI 2403
Training, Computer hacking, Face recognition, Stereo image processing, Sensors, Intrusion Monitoring BibRef

Yang, T.[Tao], Wang, J.X.[Jun-Xiang], Deng, H.L.[Hong-Li], Li, M.Y.[Ming-Yang],
A Data Enhancement Model for Intrusion Detection In Smart Home,
CVIDL23(314-317)
IEEE DOI 2403
Training, Performance evaluation, Deep learning, Intrusion detection, Smart homes, Throughput, Few Shot Learning BibRef

Lohani, D.[Devashish], Crispim-Junior, C.[Carlos], Barthélemy, Q.[Quentin], Bertrand, S.[Sarah], Robinault, L.[Lionel], Rodet, L.T.[Laure Tougne],
Unsupervised and Adaptive Perimeter Intrusion Detector,
ICIP22(3621-3625)
IEEE DOI 2211
Deep learning, Training, Adaptive systems, Thresholding (Imaging), Intrusion detection, Detectors, Perimeter intrusion detection, i-LIDS dataset BibRef

Nahler, C.[Caterina], Plank, H.[Hannes], Steger, C.[Christian], Druml, N.[Norbert],
Resource-Constrained Human Presence Detection for Indirect Time-of-Flight Sensors,
DICTA21(1-5)
IEEE DOI 2201
Reflectivity, Image sensors, Performance evaluation, Histograms, Power measurement, Laser radar, Face recognition, Time-of-Flight, reflectance BibRef

Demir, U.[Ugur], Rawat, Y.S.[Yogesh S.], Shah, M.[Mubarak],
TinyVIRAT: Low-resolution Video Action Recognition,
ICPR21(7387-7394)
IEEE DOI 2105
Location awareness, Surveillance, Superresolution, Semantics, Pipelines, Benchmark testing BibRef

Swetha, S.[Sirnam], Kuehne, H.[Hilde], Rawat, Y.S.[Yogesh S.], Shah, M.[Mubarak],
Unsupervised Discriminative Embedding for Sub-Action Learning in Complex Activities,
ICIP21(2588-2592)
IEEE DOI 2201
Training, Visualization, Image coding, Viterbi algorithm, Benchmark testing, Task analysis, Complex activity, Action detection BibRef

Rizve, M.N.[Mamshad Nayeem], Demir, U.[Ugur], Tirupattur, P.[Praveen], Rana, A.J.[Aayush Jung], Duarte, K.[Kevin], Dave, I.R.[Ishan R.], Rawat, Y.S.[Yogesh S.], Shah, M.[Mubarak],
Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Security Videos,
ICPR21(4237-4244)
IEEE DOI 2105
Location awareness, Computational modeling, Merging, Object detection, Real-time systems, Classification algorithms BibRef

Lee, S.C.[Sung Chun], Qian, G.[Gang], Beach, A.[Allison],
Real-time Person Tracking and Association on Doorbell Cameras,
ISVC20(II:458-469).
Springer DOI 2103
BibRef

Ikrissi, G., Mazri, T.,
A Study of Smart Campus Environment and Its Security Attacks,
SmartCityApp20(255-261).
DOI Link 2012
BibRef

Wang, H.[Hao], Ning, X.G.[Xiao-Gang], Dong, Q.[Quan], Liu, Y.F.[Ya-Fei], Hao, M.H.[Ming-Hui], Zhang, H.C.[Han-Chao], Wang, H.[Han], Chang, W.T.[Wen-Tao], Cao, Y.X.[Yin-Xuan], Liu, C.J.[Cai-Juan],
Quarterly Monitoring of Suspected Illegal Human Activities In National Nature Reserves of China with Sentinel-2 and High-resolution Images On the Cloud Platform,
ISPRS20(B3:1657-1662).
DOI Link 2012
BibRef

Perera, P., Fierrez, J., Patel, V.M.,
Quickest Intruder Detection For Multiple User Active Authentication,
ICIP20(1341-1345)
IEEE DOI 2011
Active Authentication, mobile-based biometrics, multiple user authentication BibRef

Cokbas, M., Ishwar, P., Konrad, J.,
Low-Resolution Overhead Thermal Tripwire for Occupancy Estimation,
PBVS20(398-406)
IEEE DOI 2008
Thermal sensors, Cameras, Event detection, Tracking, Land surface temperature, Feature extraction BibRef

Raglin, A.[Adrienne], Michealis, J.[James], Dennison, M.[Mark], Harrison, A.[Andre], Trout, T.[Theron], Schaffer, J.[James],
MxR Framework for Uncertainty Based Explanation for Uncovering Adversarial Behavior,
VAMR18(II: 354-368).
Springer DOI 1807
BibRef

Liu, Z., Zhang, J., Geng, L.,
An Intelligent Building Occupancy Detection System Based on Sparse Auto-Encoder,
SoftBio17(17-22)
IEEE DOI 1609
building management systems, energy conservation, image coding, learning (artificial intelligence), object detection, power engineering computing, data analysis, deep learning technology, energy saving, BibRef