Adversarial Attacks on Cognitive Self-Organizing Networks: The Challenge and the Way Forward

26 September 2018

Papers citing "Adversarial Attacks on Cognitive Self-Organizing Networks: The Challenge and the Way Forward"

21 / 21 papers shown

Title
Deep Learning in Mobile and Wireless Networking: A Survey Chaoyun Zhang P. Patras Hamed Haddadi 105 1,320 0 12 Mar 2018
Divide, Denoise, and Defend against Adversarial Attacks Seyed-Mohsen Moosavi-Dezfooli A. Shrivastava Oncel Tuzel AAML 55 45 0 19 Feb 2018
Experience-driven Networking: A Deep Reinforcement Learning based Approach Zhiyuan Xu Jian Tang Jingsong Meng Weiyi Zhang Yanzhi Wang C. Liu Dejun Yang OffRL 73 362 0 17 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey Naveed Akhtar Ajmal Mian AAML 99 1,870 0 02 Jan 2018
Adversarial Examples: Attacks and Defenses for Deep Learning Xiaoyong Yuan Pan He Qile Zhu Xiaolin Li SILM AAML 99 1,625 0 19 Dec 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 316 9,811 0 25 Oct 2017
Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges Muhammad Usama Junaid Qadir Aunn Raza Hunain Arif K. Yau Y. Elkhatib Amir Hussain Ala I. Al-Fuqaha SSL 83 327 0 19 Sep 2017
Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning M. Lotfollahi Ramin Shirali Hossein Zade Mahdi Jafari Siavoshani Mohammdsadegh Saberian 40 833 0 08 Sep 2017
Shallow and Deep Networks Intrusion Detection System: A Taxonomy and Survey Elike Hodo X. Bellekens Andrew W. Hamilton Christos Tachtatzis Robert C. Atkinson 46 237 0 09 Jan 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 282 8,587 0 16 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 547 5,912 0 08 Jul 2016
Adversarial Perturbations Against Deep Neural Networks for Malware Classification Kathrin Grosse Nicolas Papernot Praveen Manoharan Michael Backes Patrick McDaniel AAML 67 418 0 14 Jun 2016
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples Nicolas Papernot Patrick McDaniel Ian Goodfellow SILM AAML 116 1,742 0 24 May 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,685 0 08 Feb 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 117 3,968 0 24 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 118 3,077 0 14 Nov 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 367 19,745 0 09 Mar 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,129 0 20 Dec 2014
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications Mohammad Abu Alsheikh Shaowei Lin Dusit Niyato H. Tan 88 828 0 18 May 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 289 14,968 1 21 Dec 2013
A Learning-Based Approach to Reactive Security A. Barth Benjamin I. P. Rubinstein Mukund Sundararajan John C. Mitchell Basel Alomair Peter L. Bartlett 86 62 0 07 Dec 2009