RNNIDS: Enhancing network intrusion detection systems through deep learning

[1]  E. Mark Gold,et al.  Complexity of Automaton Identification from Given Data , 1978, Inf. Control..

[2]  Jeffrey D. Ullman,et al.  Introduction to Automata Theory, Languages and Computation , 1979 .

[3]  Carl H. Smith,et al.  Inductive Inference: Theory and Methods , 1983, CSUR.

[4]  Dorothy E. Denning,et al.  An Intrusion-Detection Model , 1987, IEEE Transactions on Software Engineering.

[5]  C. Lee Giles,et al.  Higher Order Recurrent Networks and Grammatical Inference , 1989, NIPS.

[6]  C. Lee Giles,et al.  Extracting and Learning an Unknown Grammar with Recurrent Neural Networks , 1991, NIPS.

[7]  C. Lee Giles,et al.  Learning and Extracting Finite State Automata with Second-Order Recurrent Neural Networks , 1992, Neural Computation.

[8]  C. Lee Giles,et al.  Constructing deterministic finite-state automata in recurrent neural networks , 1996, JACM.

[9]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[10]  Salvatore J. Stolfo,et al.  Data Mining Approaches for Intrusion Detection , 1998, USENIX Security Symposium.

[11]  Jürgen Schmidhuber,et al.  Learning to forget: continual prediction with LSTM , 1999 .

[12]  Jürgen Schmidhuber,et al.  Learning to Forget: Continual Prediction with LSTM , 2000, Neural Computation.

[13]  C. Lee Giles,et al.  Sequence learning: from recognition and prediction to sequential decision making , 2001, IEEE Intelligent Systems.

[14]  Ömer Egecioglu,et al.  A new approach to sequence comparison: normalized sequence alignment , 2001, RECOMB.

[15]  Ömer Egecioglu,et al.  A new approach to sequence comparison: normalized sequence alignment , 2001, Bioinform..

[16]  H. Lipson.  Tracking and Tracing Cyber-Attacks: Technical Challenges and Global Policy Issues , 2002 .

[17]  David Moore,et al.  Code-Red: a case study on the spread and victims of an internet worm , 2002, IMW '02.

[18]  Salvatore J. Stolfo,et al.  Anomalous Payload-Based Network Intrusion Detection , 2004, RAID.

[19]  J. Crowcroft,et al.  Honeycomb , 2004 .

[20]  Giovanni Vigna,et al.  Testing network-based intrusion detection signatures using mutant exploits , 2004, CCS '04.

[21]  James Newsome,et al.  Polygraph: automatically generating signatures for polymorphic worms , 2005, 2005 IEEE Symposium on Security and Privacy (S&P'05).

[22]  Ronald Saul,et al.  Discrete sequence prediction and its applications , 2005, Machine Learning.

[23]  Ming-Yang Kao,et al.  Hamsa: fast signature generation for zero-day polymorphic worms with provable attack resilience , 2006, 2006 IEEE Symposium on Security and Privacy (S&P'06).

[24]  Vitaly Shmatikov,et al.  Robust De-anonymization of Large Sparse Datasets , 2008, 2008 IEEE Symposium on Security and Privacy (sp 2008).

[25]  Gregory J. Conti,et al.  Toward Instrumenting Network Warfare Competitions to Generate Labeled Datasets , 2009, CSET.

[26]  Wei-Yang Lin,et al.  Intrusion detection by machine learning: A review , 2009, Expert Syst. Appl..

[27]  Salvatore J. Stolfo,et al.  On the infeasibility of modeling polymorphic shellcode , 2009, Machine Learning.

[28]  Yong Tang,et al.  Using a bioinformatics approach to generate accurate exploit-based signatures for polymorphic worms , 2009, Comput. Secur..

[29]  Gabriel Maciá-Fernández,et al.  Anomaly-based network intrusion detection: Techniques, systems and challenges , 2009, Comput. Secur..

[30]  Amin Vahdat,et al.  Swing: realistic and responsive network traffic generation , 2009, TNET.

[31]  Rajat Raina,et al.  Large-scale deep unsupervised learning using graphics processors , 2009, ICML '09.

[32]  Nicole Krämer,et al.  ASAP: Automatic Semantics-Aware Analysis of Network Payloads , 2010, PSDML.

[33]  Georgios Loukas,et al.  Protection Against Denial of Service Attacks: A Survey , 2010, Comput. J..

[34]  Andreas Haeberlen,et al.  Challenges in Experimenting with Botnet Detection Systems , 2011, CSET.

[35]  Yang Xiang,et al.  Malware Variant Detection Using Similarity Search over Sets of Control Flow Graphs , 2011, 2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications.

[36]  Jason Andress.  The basics of information security - understanding the fundamentals of InfoSec in theory and practice, Second edition , 2011 .

[37]  Hiroki Takakura,et al.  Statistical analysis of honeypot data and building of Kyoto 2006+ dataset for NIDS evaluation , 2011, BADGERS '11.

[38]  Gianluca Stringhini,et al.  The Underground Economy of Spam: A Botmaster's Perspective of Coordinating Large-Scale Spam Campaigns , 2011, LEET.

[39]  Geoffrey E. Hinton,et al.  Generating Text with Recurrent Neural Networks , 2011, ICML.

[40]  Alex Graves,et al.  Supervised Sequence Labelling , 2012 .

[41]  Geoffrey E. Hinton,et al.  Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[42]  Tao Wang,et al.  Deep learning with COTS HPC systems , 2013, ICML.

[43]  Neminath Hubballi,et al.  False alarm minimization techniques in signature-based intrusion detection systems: A survey , 2014, Comput. Commun..

[44]  Hannes Holm,et al.  Signature Based Intrusion Detection for Zero-Day Attacks: (Not) A Closed Chapter? , 2014, 2014 47th Hawaii International Conference on System Sciences.

[45]  Xinyuan Wang,et al.  CodeXt: Automatic Extraction of Obfuscated Attack Code from Memory Dump , 2014, ISC.

[46]  Ali A. Ghorbani,et al.  Towards effective feature selection in machine learning-based botnet detection approaches , 2014, 2014 IEEE Conference on Communications and Network Security.

[47]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[48]  Taghi M. Khoshgoftaar,et al.  A New Intrusion Detection Benchmarking System , 2015, FLAIRS Conference.

[49]  Guigang Zhang,et al.  Deep Learning , 2016, Int. J. Semantic Comput..

[50]  Lior Rokach,et al.  Scalable attack propagation model and algorithms for honeypot systems , 2016, 2016 IEEE International Conference on Big Data (Big Data).

[51]  Erhan Guven,et al.  A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection , 2016, IEEE Communications Surveys & Tutorials.

[52]  Ewa Niewiadomska-Szynkiewicz,et al.  Design and evaluation of a system for network threat signatures generation , 2017, J. Comput. Sci..

[53]  Lior Wolf,et al.  Language Generation with Recurrent Generative Adversarial Networks without Pre-training , 2017, ArXiv.

[54]  Aaron C. Courville,et al.  Improved Training of Wasserstein GANs , 2017, NIPS.

[55]  Mikhail V. Chester,et al.  Perspective: The Cyber Frontier and Infrastructure , 2020, IEEE Access.