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Machine learning has witnessed tremendous growth in its adoption and advancement in the last decade.
Learning Representations by Back-Propagating Errors
David E Rumelhart, Geoffrey E Hinton, and Ronald J Williams · 1986
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Unsupervised Learning
Horace B Barlow · 1989
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Handwritten Digit Recognition with a Back-Propagation Network
Yann LeCun, Bernhard Boser, John Denker, Donnie Henderson, Richard Howard, Wayne Hubbard, and Lawrence Jackel · 1989
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Elements of Machine Learning
Pat Langley · 1996
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Analysis of a denial of service attack on TCP
Christoph L Schuba, Ivan V Krsul, Markus G Kuhn, Eugene H Spafford, Aurobindo Sundaram, and Diego Zamboni · 1997
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Machine Learning
Thomas M. Mitchell · 1997
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Long Short-Term Memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Feature Saliency Measures
Jean M Steppe and Kenneth W Bauer Jr · 1997
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Gradient-Based Learning Applied to Document Recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins
Carol J Bult · 1998
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On supervised learning from sequential data with applications for speech recognition
Michael Schuster · 1999
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Machine Learning for Medical Diagnosis: History, State of the Art and Perspective
Igor Kononenko · 2001
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Discriminative Direction for Kernel Classifiers
Polina Golland · 2001
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Advanced SQL injection in SQL server applications
Chris Anley · 2002
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Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System
S. Singh, D. Litman, M. Kearns, and M. Walker · 2002
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Inside Windows: Win32 Portable Executable File Format in Detail
Kexugit · 2002
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Mimicry Attacks on Host-Based Intrusion Detection Systems
David Wagner and Paolo Soto · 2002
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Machine Learning Techniques in Spam Filtering
Konstantin Tretyakov · 2004
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A man-in-the-middle attack on UMTS
Ulrike Meyer and Susanne Wetzel · 2004
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Internet Denial of Service: Attack and Defense Mechanisms (Radia Perlman Computer Networking and Security Book Series)
Jelena Mirkovic, Sven Dietrich, David Dittrich, and Peter Reiher · 2004
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Flow Clustering Using Machine Learning Techniques
Anthony McGregor, Mark Hall, Perry Lorier, and James Brunskill · 2004
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Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion
Nate Kohl and Peter Stone · 2004
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Feature Selection for Dimensionality Reduction
Dunja Mladenić · 2005
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Pin: Building Customized Program Analysis Tools with Dynamic Instrumentation
Chi-Keung Luk, Robert Cohn, Robert Muth, Harish Patil, Artur Klauser, Geoff Lowney, Steven Wallace, Vijay Janapa Reddi, and Kim Hazelwood · 2005
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Inferring access-control policy properties via machine learning
Evan Martin and Tao Xie · 2006
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A Classification of SQL-Injection Attacks and Countermeasures
William G Halfond, Jeremy Viegas, Alessandro Orso, et al · 2006
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Beyond PageRank: Machine Learning for Static Ranking
Matthew Richardson, Amit Prakash, and Eric Brill · 2006
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Subset Ranking Using Regression
David Cossock and Tong Zhang · 2006
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Autonomous Inverted Helicopter Flight via Reinforcement Learning
Andrew Y Ng, Adam Coates, Mark Diel, Varun Ganapathi, Jamie Schulte, Ben Tse, Eric Berger, and Eric Liang · 2006
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Learning to Detect and Classify Malicious Executables in the Wild
J Zico Kolter and Marcus A Maloof · 2006
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Anagram: A Content Anomaly Detector Resistant to Mimicry Attack
Ke Wang, Janak J Parekh, and Salvatore J Stolfo · 2006
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An empirical study of three machine learning methods for spam filtering
Chih-Chin Lai · 2007
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Supervised Machine Learning: A Review of Classification Techniques
Sotiris B Kotsiantis, I Zaharakis, P Pintelas, et al · 2007
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Clustering techniques and their applications in engineering
DT Pham and AA Afify · 2007
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Malicious Codes Detection Based on Ensemble Learning
Boyun Zhang, Jianping Yin, Jingbo Hao, Dingxing Zhang, and Shulin Wang · 2007
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Opcodes as Predictor for Malware
Daniel Bilar · 2007
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Limits of Static Analysis for Malware Detection
Andreas Moser, Christopher Kruegel, and Engin Kirda · 2007
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Toward Automated Dynamic Malware Analysis Using CWSandbox
Carsten Willems, Thorsten Holz, and Felix Freiling · 2007
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Efficient signature based malware detection on mobile devices
Deepak Venugopal and Guoning Hu · 2008
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A review of machine learning approaches to Spam filtering
Thiago S Guzella and Walmir M Caminhas · 2009
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Wifi networks and malware epidemiology
Hao Hu, Steven Myers, Vittoria Colizza, and Alessandro Vespignani · 2009
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Man-in-the-Middle Attack to the HTTPS Protocol
Franco Callegati, Walter Cerroni, and Marco Ramilli · 2009
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Automatic creation of SQL injection and cross-site scripting attacks
Adam Kieyzun, Philip J Guo, Karthick Jayaraman, and Michael D Ernst · 2009
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ImageNet: A Large-scale Hierarchical Image Database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Overview of Supervised Learning
Trevor Hastie, Robert Tibshirani, and Jerome Friedman · 2009
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Unsupervised Learning
Trevor Hastie, Robert Tibshirani, and Jerome Friedman · 2009
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Introduction to Semi-Supervised Learning
Xiaojin Zhu and Andrew B Goldberg · 2009
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Machine Learning in Medical Imaging
Miles N Wernick, Yongyi Yang, Jovan G Brankov, Grigori Yourganov, and Stephen C Strother · 2010
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The security of machine learning
Marco Barreno, Blaine Nelson, Anthony Joseph, and J. Tygar · 2010
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Ranking Chemical Structures for Drug Discovery: A New Machine Learning Approach
Shivani Agarwal, Deepak Dugar, and Shiladitya Sengupta · 2010
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Algorithms for Reinforcement Learning
Csaba Szepesvári · 2010
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Signature Tree Generation for Polymorphic Worms
Yong Tang, Bin Xiao, and Xicheng Lu · 2010
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Malicious Executables Classification Based on Behavioral Factor Analysis
Hengli Zhao, Ming Xu, Ning Zheng, Jingjing Yao, and Qiang Ho · 2010
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Differentiating Malware from Cleanware Using Behavioural Analysis
Ronghua Tian, Rafiqul Islam, Lynn Batten, and Steve Versteeg · 2010
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Platform-Independent Programs
Sang Kil Cha, Brian Pak, David Brumley, and Richard Jay Lipton · 2010
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Automatic analysis of malware behavior using machine learning
Konrad Rieck, Philipp Trinius, Carsten Willems, and Thorsten Holz · 2011
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A machine learning approach to Twitter user classification
Marco Pennacchiotti and Ana-Maria Popescu · 2011
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Recurrent Neural Network Based Language Modeling in Meeting Recognition
Stefan Kombrink, Tomáš Mikolov, Martin Karafiát, and Lukáš Burget · 2011
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Graph-based Malware Detection Using Dynamic Analysis
Blake Anderson, Daniel Quist, Joshua Neil, Curtis Storlie, and Terran Lane · 2011
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Detecting Environment-Sensitive Malware
Martina Lindorfer, Clemens Kolbitsch, and Paolo Milani Comparetti · 2011
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Combining Static and Dynamic Analysis for the Detection of Malicious Documents
Zacharias Tzermias, Giorgos Sykiotakis, Michalis Polychronakis, and Evangelos P Markatos · 2011
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Malware Images: Visualization and Automatic Classification
Lakshmanan Nataraj, Sreejith Karthikeyan, Gregoire Jacob, and Bangalore S Manjunath · 2011
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Static Detection of Malicious JavaScript-Bearing PDF Documents
Pavel Laskov and Nedim Šrndić · 2011
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Static Detection of Malicious JavaScript-Bearing PDF Documents
Pavel Laskov and Nedim Šrndić · 2011
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Combining Static and Dynamic Analysis for the Detection of Malicious Documents
Zacharias Tzermias, Giorgos Sykiotakis, Michalis Polychronakis, and Evangelos P Markatos · 2011
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A machine learning approach to android malware detection
Justin Sahs and Latifur Khan · 2012
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Maximum Damage Malware Attack in Mobile Wireless Networks
MHR Khouzani, Saswati Sarkar, and Eitan Altman · 2012
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The State of Phishing Attacks
Jason Hong · 2012
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A Practical Man-In-The-Middle Attack on Signal-Based Key Generation Protocols
Simon Eberz, Martin Strohmeier, Matthias Wilhelm, and Ivan Martinovic · 2012
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Reinforcement Learning
Marco A Wiering and Martijn Van Otterlo · 2012
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Learning Hierarchical Features for Scene Labeling
Clement Farabet, Camille Couprie, Laurent Najman, and Yann LeCun · 2012
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ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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LSTM Neural Networks for Language Modeling
Martin Sundermeyer, Ralf Schlüter, and Hermann Ney · 2012
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Tracking Concept Drift in Malware Families
Anshuman Singh, Andrew Walenstein, and Arun Lakhotia · 2012
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Malicious PDF detection using metadata and structural features
Charles Smutz and Angelos Stavrou · 2012
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A Pattern Recognition System for Malicious PDF Files Detection
Davide Maiorca, Giorgio Giacinto, and Igino Corona · 2012
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Abusing File Processing in Malware Detectors for Fun and Profit
Suman Jana and Vitaly Shmatikov · 2012
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A Survey on Heuristic Malware Detection Techniques
Zahra Bazrafshan, Hashem Hashemi, Seyed Mehdi Hazrati Fard, and Ali Hamzeh · 2013
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DroidAnalytics: A Signature Based Analytic System to Collect, Extract, Analyze and Associate Android Malware
Min Zheng, Mingshen Sun, and John CS Lui · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Big Data for Dummies
Judith S Hurwitz, Alan Nugent, Fern Halper, and Marcia Kaufman · 2013
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Big Data: A Review
Seref Sagiroglu and Duygu Sinanc · 2013
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Clustering and its Applications
LV Bijuraj · 2013
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Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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New Types of Deep Neural Network Learning for Speech Recognition and Related Applications: An Overview
Li Deng, Geoffrey Hinton, and Brian Kingsbury · 2013
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Speech Recognition With Deep Recurrent Neural Networks
Alex Graves, Abdel-rahman Mohamed, and Geoffrey Hinton · 2013
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On the Feasibility of Online Malware Detection with Performance Counters
John Demme, Matthew Maycock, Jared Schmitz, Adrian Tang, Adam Waksman, Simha Sethumadhavan, and Salvatore Stolfo · 2013
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Maxout Networks
Ian Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, and Yoshua Bengio · 2013
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Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2013
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A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms
Pinar Civicioglu and Erkan Besdok · 2013
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Evasion Attacks against Machine Learning at Test Time
Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Šrndić, Pavel Laskov, Giorgio Giacinto, and Fabio Roli · 2013
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Image Visualization based Malware Detection
Kesav Kancherla and Srinivas Mukkamala · 2013
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Looking at the Bag is Not Enough to Find the Bomb: An Evasion of Structural Methods for Malicious PDF Files Detection
Davide Maiorca, Igino Corona, and Giorgio Giacinto · 2013
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Evasion Attacks against Machine Learning at Test Time
Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Šrndić, Pavel Laskov, Giorgio Giacinto, and Fabio Roli · 2013
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Detection of Malicious PDF Files Based on Hierarchical Document Structure
Nedim Šrndic and Pavel Laskov · 2013
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Signature based malware detection for unstructured data in Hadoop
Abhaya Kumar Sahoo, Kshira Sagar Sahoo, and Mayank Tiwary · 2014
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Explaining and Harnessing Adversarial Examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Big Data and Management
Gerard George, Martine R Haas, and Alex Pentland · 2014
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Machine Learning Classification over Encrypted Data
Raphael Bost, Raluca Ada Popa, Stephen Tu, and Shafi Goldwasser · 2014
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Risk prediction with machine learning and regression methods
Ewout W Steyerberg, Tjeerd van der Ploeg, and Ben Van Calster · 2014
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Understanding Machine Learning: From Theory to Algorithms
Shai Shalev-Shwartz and Shai Ben-David · 2014
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Semi-Supervised Learning with Deep Generative Models
Diederik P Kingma, Shakir Mohamed, Danilo Jimenez Rezende, and Max Welling · 2014
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Deep Speech: Scaling up end-to-end speech recognition
Awni Hannun, Carl Case, Jared Casper, Bryan Catanzaro, Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, Adam Coates, et al · 2014
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Droid-Sec: Deep Learning in Android Malware Detection
Zhenlong Yuan, Yongqiang Lu, Zhaoguo Wang, and Yibo Xue · 2014
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Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan and Andrew Zisserman · 2014
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Haşim Sak, Andrew Senior, and Françoise Beaufays · 2014
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Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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DroidDolphin: a Dynamic Android Malware Detection Framework Using Big Data and Machine Learning
Wen-Chieh Wu and Shih-Hao Hung · 2014
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Security Evaluation of Pattern Classifiers under Attack
Battista Biggio, Giorgio Fumera, and Fabio Roli · 2014
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DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket
Dan Arp, Michael Spreitzenbarth, M. Hubner, Hugo Gascon, and K. Rieck · 2014
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Security Evaluation of Support Vector Machines in Adversarial Environments
Battista Biggio, Igino Corona, Blaine Nelson, Benjamin IP Rubinstein, Davide Maiorca, Giorgio Fumera, Giorgio Giacinto, and Fabio Roli · 2014
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Practical Evasion of a Learning-Based Classifier: A Case Study
Pavel Laskov et al · 2014
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Detecting Malicious Javascript in PDF through Document Instrumentation
Daiping Liu, Haining Wang, and Angelos Stavrou · 2014
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Optimal Randomized Classification in Adversarial Settings
Yevgeniy Vorobeychik and Bo Li · 2014
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PCANet: A Simple Deep Learning Baseline for Image Classification?
Tsung-Han Chan, Kui Jia, Shenghua Gao, Jiwen Lu, Zinan Zeng, and Yi Ma · 2015
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An Empirical Evaluation of Deep Learning on Highway Driving
Brody Huval, Tao Wang, Sameep Tandon, Jeff Kiske, Will Song, Joel Pazhayampallil, Mykhaylo Andriluka, Pranav Rajpurkar, Toki Migimatsu, Royce Cheng-Yue, et al · 2015
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Spear-Phishing in the Wild: A Real-World Study of Personality, Phishing Self-Efficacy and Vulnerability to Spear-Phishing Attacks
Tzipora Halevi, Nasir Memon, and Oded Nov · 2015
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Going Deeper with Convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Deep Learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Continuous Control with Deep Reinforcement Learning
Timothy P Lillicrap, Jonathan J Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2015
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Human-level control through Deep Reinforcement Learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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A Critical Review of Recurrent Neural Networks for Sequence Learning
Zachary C Lipton, John Berkowitz, and Charles Elkan · 2015
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Bayesian Recurrent Neural Network for Language Modeling
Jen-Tzung Chien and Yuan-Chu Ku · 2015
Cited alongside, same era.
EESEN: End-to-end speech recognition using deep RNN models and WFST-based decoding
Yajie Miao, Mohammad Gowayyed, and Florian Metze · 2015
Cited alongside, same era.
Unsupervised Representation Learning With Deep Convolutional Generative Adversarial Networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
Cited alongside, same era.
Malware behavioural detection and vaccine development by using a support vector model classifier
Ping Wang and Yu-Shih Wang · 2015
Cited alongside, same era.
Story Scrambler-Automatic Text Generation Using Word Level RNN-LSTM
D Pawade, A Sakhapara, Mansi Jain, Neha Jain, and Krushi Gada · 2018
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Neural Text Generation: Past, Present and Beyond
Sidi Lu, Yaoming Zhu, Weinan Zhang, Jun Wang, and Yong Yu · 2018
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Order-Planning Neural Text Generation From Structured Data
Lei Sha, Lili Mou, Tianyu Liu, Pascal Poupart, Sujian Li, Baobao Chang, and Zhifang Sui · 2018
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Generative adversarial networks: An overview
Antonia Creswell, Tom White, Vincent Dumoulin, Kai Arulkumaran, Biswa Sengupta, and Anil A Bharath · 2018
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Spectral Normalization for Generative Adversarial Networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
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Integrated Static and Dynamic Analysis for Malware Detection
PV Shijo and AJPCS Salim · 2015
Cited alongside, same era.
Mobile-Sandbox: Combining Static and Dynamic Analysis with Machine-Learning Techniques
Michael Spreitzenbarth, Thomas Schreck, Florian Echtler, Daniel Arp, and Johannes Hoffmann · 2015
Cited alongside, same era.
Semantics-Based Online Malware Detection: Towards Efficient Real-Time Protection Against Malware
Sanjeev Das, Yang Liu, Wei Zhang, and Mahintham Chandramohan · 2015
Cited alongside, same era.
Malware-Aware Processors: A Framework for Efficient Online Malware Detection
Meltem Ozsoy, Caleb Donovick, Iakov Gorelik, Nael Abu-Ghazaleh, and Dmitry Ponomarev · 2015
Cited alongside, same era.
Text Understanding from Scratch
Xiang Zhang and Yann LeCun · 2015
Cited alongside, same era.
Obfuscator-LLVM–Software Protection for the Masses
Pascal Junod, Julien Rinaldini, Johan Wehrli, and Julie Michielin · 2015
Cited alongside, same era.
MALWARE CLASSIFICATION WITH RECURRENT NETWORKS
Razvan Pascanu, Jack W. Stokes, Hermineh Sanossian, Mady Marinescu, and Anil Thomas · 2015
Cited alongside, same era.
To Learn Image Super-Resolution, Use a GAN To Learn How To Do Image Degradation First
Adrian Bulat, Jing Yang, and Georgios Tzimiropoulos · 2018
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Conditional Generative Adversarial Network for Structured Domain Adaptation
Weixiang Hong, Zhenzhen Wang, Ming Yang, and Junsong Yuan · 2018
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Mastering Sketching: Adversarial Augmentation for Structured Prediction
Edgar Simo-Serra, Satoshi Iizuka, and Hiroshi Ishikawa · 2018
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Generative Adversarial Network Training is a Continual Learning Problem
Kevin J Liang, Chunyuan Li, Guoyin Wang, and Lawrence Carin · 2018
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Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers
Ishai Rosenberg, Asaf Shabtai, Lior Rokach, and Yuval Elovici · 2018
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A state-of-the-art survey of malware detection approaches using data mining techniques
Alireza Souri and Rahil Hosseini · 2018
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Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-virus
William Fleshman, Edward Raff, Richard Zak, Mark McLean, and Charles Nicholas · 2018
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A Novel Dynamic Android Malware Detection System With Ensemble Learning
Pengbin Feng, Jianfeng Ma, Cong Sun, Xinpeng Xu, and Yuwan Ma · 2018
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Black-Box Attacks against RNN based Malware Detection Algorithms
Weiwei Hu and Ying Tan · 2018
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Gray-box Adversarial Training
BS Vivek, Konda Reddy Mopuri, and R Venkatesh Babu · 2018
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Adversarial Attacks and Defences: A Survey
Anirban Chakraborty, Manaar Alam, Vishal Dey, Anupam Chattopadhyay, and Debdeep Mukhopadhyay · 2018
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Data Poisoning Attacks against Online Learning
Yizhen Wang and Kamalika Chaudhuri · 2018
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Stronger Data Poisoning Attacks Break Data Sanitization Defenses
Pang Wei Koh, Jacob Steinhardt, and Percy Liang · 2018
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Malware Detection by Eating a Whole EXE
Edward Raff, Jon Barker, Jared Sylvester, Robert Brandon, Bryan Catanzaro, and Charles K Nicholas · 2018
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Adversarial Examples on Discrete Sequences for Beating Whole-Binary Malware Detection
F. Kreuk, A. Barak, Shir Aviv-Reuven, Moran Baruch, Benny Pinkas, and Joseph Keshet · 2018
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Ember: An Open Dataset for Training Static PE Malware Machine Learning Models
Hyrum S Anderson and Phil Roth · 2018
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Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Felix Kreuk, Assi Barak, Shir Aviv-Reuven, Moran Baruch, Benny Pinkas, and Joseph Keshet · 2018
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Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning
Hyrum S Anderson, Anant Kharkar, Bobby Filar, David Evans, and Phil Roth · 2018
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Boosting Adversarial Attacks with Momentum
Yinpeng Dong, Fangzhou Liao, Tianyu Pang, Hang Su, Jun Zhu, Xiaolin Hu, and Jianguo Li · 2018
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Designing Subspecies of Hardware Trojans and Their Detection Using Neural Network Approach
Tomotaka Inoue, Kento Hasegawa, Yuki Kobayashi, Masao Yanagisawa, and Nozomu Togawa · 2018
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Dynamic Malware Analysis Using Cuckoo Sandbox
Sainadh Jamalpur, Yamini Sai Navya, Perla Raja, Gampala Tagore, and G Rama Koteswara Rao · 2018
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Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer
Alvin Chan, Lei Ma, Felix Juefei-Xu, Xiaofei Xie, Yang Liu, and Yew Soon Ong · 2018
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Defense against Adversarial Attacks using High-Level Representation Guided Denoiser
Fangzhou Liao, Ming Liang, Yinpeng Dong, Tianyu Pang, Xiaolin Hu, and Jun Zhu · 2018
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Defense-GAN: Protecting Classifiers against Adversarial Attacks using Generative Models
Pouya Samangouei, Maya Kabkab, and Rama Chellappa · 2018
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Deep learning-based image recognition for autonomous driving
Hironobu Fujiyoshi, Tsubasa Hirakawa, and Takayoshi Yamashita · 2019
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A Deep Learning Framework for Neuroscience
Blake A Richards, Timothy P Lillicrap, Philippe Beaudoin, Yoshua Bengio, Rafal Bogacz, Amelia Christensen, Claudia Clopath, Rui Ponte Costa, Archy de Berker, Surya Ganguli, et al · 2019
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From Deep Learning to Mechanistic Understanding in Neuroscience: The Structure of Retinal Prediction
Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan, Lane McIntosh, Stephen A Baccus, and Surya Ganguli · 2019
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Machine Learning for Email Spam Filtering: Review, Approaches and Open Research Problems
Emmanuel Gbenga Dada, Joseph Stephen Bassi, Haruna Chiroma, Adebayo Olusola Adetunmbi, Opeyemi Emmanuel Ajibuwa, et al · 2019
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Credit Card Fraud Detection-Machine Learning methods
Dejan Varmedja, Mirjana Karanovic, Srdjan Sladojevic, Marko Arsenovic, and Andras Anderla · 2019
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Practical enclave malware with Intel SGX
Michael Schwarz, Samuel Weiser, and Daniel Gruss · 2019
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A Unified Framework for Data Poisoning Attack to Graph-Based Semi-supervised Learning
Xuanqing Liu, Si Si, Xiaojin Zhu, Yang Li, and Cho-Jui Hsieh · 2019
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Understanding Distributed Poisoning Attack in Federated Learning
Di Cao, Shan Chang, Zhijian Lin, Guohua Liu, and Donghong Sun · 2019
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TensorClog: An Imperceptible Poisoning Attack on Deep Neural Network Applications
Juncheng Shen, Xiaolei Zhu, and De Ma · 2019
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These Chinese hackers tricked Tesla’s Autopilot into suddenly switching lanes
Tom Huddleston Jr · 2019
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Adversarial examples: Attacks and defenses for deep learning
Xiaoyong Yuan, Pan He, Qile Zhu, and Xiaolin Li · 2019
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A taxonomy and survey of attacks against machine learning
Nikolaos Pitropakis, Emmanouil A. Panaousis, Thanassis Giannetsos, Eleftherios Anastasiadis, and George Loukas · 2019
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The security of machine learning in an adversarial setting: A survey
Xianmin Wang, Jing Li, Xiaohui Kuang, Yu an Tan, and Jin Li · 2019
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Review of Artificial Intelligence Adversarial Attack and Defense Technologies
Shilin Qiu, Qihe Liu, Shijie Zhou, and Chunjiang Wu · 2019
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Masataka Kawai, Kaoru Ota, and Mianxing Dong · 2019
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Xinbo Liu, Jiliang Zhang, Yaping Lin, and He Li · 2019
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