PPT-Adversarial Models for Wireless Communication

Andrea W Richa Arizona State University SIROCCO13 Andrea Richa 1 Motivation Channel availability hard to model Mobility Packet injection Temporary Obstacles Background noise Physical Interference. Wireless. . and. Mobile Networks. Spring. . 2011-2012. Marmara . University. – . Computer. . Engineering. Assist. . Prof. Ömer . Korçak. . mimoza.. marmara. .edu.tr/~. omer. .. korcak. o. mer. Cormac. Flanagan & Stephen Freund. UC Santa Cruz Williams . College. PLDI 2010. Slides by Michelle Goodstein. LBA Reading Group, June 2 2010. Motivation. Multi-threaded programs often contain data races. by Mike Denko, Alex Motalleb, and Tony Qian . Image taken from: http://findicons.com/icon/84804/wifi. Purpose. Want to make an embedded application where a wired connection isn't practical, things to consider with a wireless solution:. January 2013. Avaya IP Wireless Telephones. Campus Nomad. The “Campus Nomad” is mobile within the boundaries of the enterprise. This is most common in healthcare, retail and manufacturing environments.. Fabian Kuhn. Algorithms and Complexity Group. University of Freiburg. Germany. 2. Modeling Wireless Communication. Network modeled as a graph . k. nown as “radio network model” or “protocol model”. etc. Convnets. (optimize weights to predict bus). bus. Convnets. (optimize input to predict ostrich). ostrich. Work on Adversarial examples by . Goodfellow. et al. , . Szegedy. et. al., etc.. Generative Adversarial Networks (GAN) [. Statistical Relational AI. Daniel Lowd. University of Oregon. Outline. Why do we need adversarial modeling?. Because of the dream of AI. Because of current reality. Because of possible dangers. Our initial approach and results. WHY WIRELESS COMMUNICATION?. Freedom from wires.. No bunch of wires running from here and there.. “Auto Magical” instantaneous communication without physical connection setup e.g.- Bluetooth, Wi-Fi.. Nets. İlke Çuğu 1881739. NIPS 2014 . Ian. . Goodfellow. et al.. At a . glance. (. http://www.kdnuggets.com/2017/01/generative-adversarial-networks-hot-topic-machine-learning.html. ). Idea. . Behind. January 2013. Avaya IP Wireless Telephones. Campus Nomad. The “Campus Nomad” is mobile within the boundaries of the enterprise. This is most common in healthcare, retail and manufacturing environments.. Presenters: Pooja Harekoppa, Daniel Friedman. Explaining and Harnessing Adversarial Examples. Ian J. . Goodfellow. , Jonathon . Shlens. and Christian . Szegedy. Google Inc., Mountain View, CA. Highlights . Akrit Mohapatra. ECE Department, Virginia Tech. What are GANs?. System of . two neural networks competing against each other in a zero-sum game framework. . They were first introduced by . Ian Goodfellow. Dr. Alex Vakanski. Lecture 6. GANs for Adversarial Machine Learning. Lecture Outline. Mohamed Hassan presentation. Introduction to Generative Adversarial Networks (GANs). Jeffrey Wyrick presentation. BY. Dr.K.Gopi. Associate professor. Department of ECE. SITAMS. Unit-1 Introduction to wireless networks. Introduction. Difference between wireless and fixed telephone networks. Development of wireless networks,.