• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 123 matches

• 2020
• 
  Jung-Hua Wang, Shih-Kai Lee, Yi-Chung Lai, Cheng-Chun Lin, Ting-Yuan Wang, Ying-Ren Lin, Te-Hua Hsu, Chang-Wen Huang, Chung-Ping Chiang:
  Anomalous Behaviors Detection for Underwater Fish Using AI Techniques. IEEE Access 8: 224372-224382 (2020)
• 
  Feng Zheng, Quanyun Liu:
  Anomalous Telecom Customer Behavior Detection and Clustering Analysis Based on ISP's Operating Data. IEEE Access 8: 42734-42748 (2020)
• 
  Samundra Deep, Xi Zheng, Chandan K. Karmakar, Dongjin Yu, Leonard G. C. Hamey, Jiong Jin:
  A Survey on Anomalous Behavior Detection for Elderly Care Using Dense-Sensing Networks. IEEE Commun. Surv. Tutorials 22(1): 352-370 (2020)
• 
  Rocco Langone, Alfredo Cuzzocrea, Nikolaos Skantzos:
  Interpretable Anomaly Prediction: Predicting anomalous behavior in industry 4.0 settings via regularized logistic regression tools. Data Knowl. Eng. 130: 101850 (2020)
• 
  Robert Luh, Sebastian Schrittwieser:
  Advanced threat intelligence: detection and classification of anomalous behavior in system processes. Elektrotech. Informationstechnik 137(1): 38-44 (2020)
• 
  Zhao-Yang Wang, Beihong Jin, Tingjian Ge, Taofeng Xue:
  Detecting Anomalous Bus-Driving Behaviors from Trajectories. J. Comput. Sci. Technol. 35(5): 1047-1063 (2020)
• 
  Victor Vladareanu, Valentin-Gabriel Voiculescu, Vlad-Alexandru Grosu, Luige Vladareanu, Ana-Maria Travediu, Hao Yan, Hongbo Wang, Laura Ruse:
  Detection of Anomalous Behavior in Modern Smartphones Using Software Sensor-Based Data. Sensors 20(10): 2768 (2020)
• 
  Rocco Langone, Alfredo Cuzzocrea, Nikolaos Skantzos:
  A Flexible and Interpretable Framework for Predicting Anomalous Behavior in Industry 4.0 Environments. AINA 2020: 693-702
• 
  Dingshan Cui, Lei Duan, Xinao Wang, Jyrki Nummenmaa, Ruiqi Qin, Shan Xiao:
  LOCATE: Locally Anomalous Behavior Change Detection in Behavior Information Sequence. APWeb/WAIM (2) 2020: 193-208
• 
  Kazunari Takasaki, Kento Hasegawa, Ryoichi Kida, Nozomu Togawa:
  An Anomalous Behavior Detection Method for IoT Devices by Extracting Application-Specific Power Behaviors. IOLTS 2020: 1-4
• 
  Pengcheng Fan, Yangzexi Liu, Jingqiu Guo, Yibing Wang, Min Qiu:
  Anomalous State Recognition of Lane-changing Behavior using a Hybrid Autoencoder Architecture. ITSC 2020: 1-6
• 
  Abdurhman Albasir, Q. Hu, Mustafa Al-tekreeti, Kshirasagar Naik, N. Naik, A. James Kozlowski, Nishith Goel:
  Unsupervised Detection of Anomalous Behavior in Wireless Devices based on Auto-Encoders. NOMS 2020: 1-7
• 
  Durand de Gevigney Valentin, Pierre-François Marteau, Arnaud Delhay, Damien Lolive:
  Video Latent Code Interpolation for Anomalous Behavior Detection. SMC 2020: 3037-3044
• 
  Jorge L. Suzuki, Pegah Varghaei, Ehsan Kharazmi, Mohsen Zayernouri:
  Anomalous Nonlinear Dynamics Behavior of Fractional Viscoelastic Structures. CoRR abs/2009.12214 (2020)
• 2019
• 
  Robert Luh, Helge Janicke, Sebastian Schrittwieser:
  AIDIS: Detecting and classifying anomalous behavior in ubiquitous kernel processes. Comput. Secur. 84: 120-147 (2019)
• 
  Joo-Sung Kim, Jin-Suk Lee, Kwang-Il Kim:
  Anomalous Vessel Behavior Detection Based on SVR Seaway Model. Int. J. Fuzzy Log. Intell. Syst. 19(1): 18-27 (2019)
• 
  Jian Mao, Shishi Zhu, Jingdong Bian, Qixiao Lin, Jianwei Liu:
  Anomalous Power-Usage Behavior Detection from Smart Home Wireless Communications. J. Commun. Inf. Networks 4(1): 13-23 (2019)
• 
  Navneet Nayan, Sitanshu Sekhar Sahu, Sanjeet Kumar:
  Detecting anomalous crowd behavior using correlation analysis of optical flow. Signal Image Video Process. 13(6): 1233-1241 (2019)
• 
  Biao Yang, Jinmeng Cao, Nan Wang, Xiaofeng Liu:
  Anomalous Behaviors Detection in Moving Crowds Based on a Weighted Convolutional Autoencoder-Long Short-Term Memory Network. IEEE Trans. Cogn. Dev. Syst. 11(4): 473-482 (2019)
• 
  Waqas Haider, Jiankun Hu, Yi Xie, Xinghuo Yu, Qianhong Wu:
  Detecting Anomalous Behavior in Cloud Servers by Nested-Arc Hidden SEMI-Markov Model with State Summarization. IEEE Trans. Big Data 5(3): 305-316 (2019)
• 
  Huan Wang, Jia Wu, Wenbin Hu, Xindong Wu:
  Detecting and Assessing Anomalous Evolutionary Behaviors of Nodes in Evolving Social Networks. ACM Trans. Knowl. Discov. Data 13(1): 12:1-12:24 (2019)
• 
  Athanasios Naskos, Anastasios Gounaris, Ifigeneia Metaxa, Daniel Köchling:
  Detecting Anomalous Behavior Towards Predictive Maintenance. CAiSE Workshops 2019: 73-82
• 
  Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai:
  Model-based Approach with ACT-R about Benefits of Memory-based Strategy on Anomalous Behaviors. CogSci 2019: 776-781
• 
  Hyunyoung Oh, Hayoon Yi, Hyeokjun Choe, Yeongpil Cho, Sungroh Yoon, Yunheung Paek:
  Real-Time Anomalous Branch Behavior Inference with a GPU-inspired Engine for Machine Learning Models. DATE 2019: 908-913
• 
  Lindsey Coffee-Johnson, Debbie Perouli:
  Detecting Anomalous Behavior of Socially Assistive Robots in Geriatric Care Facilities. HRI 2019: 582-583
• 
  Cong Xie, Wonyong Jeong, Gyorgy Matyasfalvi, Hubertus Van Dam, Klaus Mueller, Shinjae Yoo, Wei Xu:
  Exploratory Visual Analysis of Anomalous Runtime Behavior in Streaming High Performance Computing Applications. ICCS (1) 2019: 153-167
• 
  Ricardo Manzano, Abdurhman Albasir, Kshirasagar Naik, Jim Kozlowski, Nishith Goel:
  Detection of Anomalous Behavior in Wireless Devices Using Changepoint Analysis. ICIOT 2019: 82-90
• 
  Nong Ye, Douglas Montgomery, Kevin Mills, Mark Carson:
  Multivariate Metrics of Normal and Anomalous Network Behaviors. IM 2019: 55-58
• 
  Teik-Toe Teoh, Elias Jaddoo Yeaz, Nguwi Yok Yen:
  Machine Learning Based Detection and Categorization of Anomalous Behavior in Enterprise Network Traffic. ISKE 2019: 750-754
• 
  Veena Mendiratta, Zhuoran Liu, Mrinmoy Bhattacharjee, Yu Zhou:
  Detecting and Diagnosing Anomalous Behavior in Large Systems with Change Detection Algorithms. ISSRE Workshops 2019: 47-52

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