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DESCRIPTION:   'Title: Generative Adversarial Network (GAN) based autonomou
 s\n   penetration testing for Web Applications\n   When: Friday\, Aug 11\,
  11:00 - 11:45 PDT\n   Where: Flamingo - Savoy - AppSec Village - Main Sta
 ge - [1]Map\n\n   SpeakerBio:Ankur Chowdhary\n   Dr. Ankur Chowdhary is a 
 cybersecurity researcher. He received Ph.D.\n   (2020) and M.S. (2015) wit
 h specialization in cybersecurity from\n   Arizona State University (ASU).
  His research interests include appsec\,\n   cloud security and AI/ML in c
 ybersecurity.\n\n   Description:\n   The web application market has shown 
 rapid growth in recent years.\n   Current security research utilizes sourc
 e code analysis\, and manual\n   exploitation of web applications to ident
 ify security vulnerabilities\n   such as Cross-site Scripting\, SQL Inject
 ion. The attack samples\n   generated as part of web application penetrati
 on testing can be easily\n   blocked using Web Application Firewalls (WAFs
 ). In this talk\, I will\n   discuss the use of conditional generative adv
 ersarial network (GAN) to\n   identify key features for XSS attacks\, and 
 train a generative model\n   based on attack labels\, and attack features.
  The attack features are\n   identified using semantic tokenization\, and 
 the attack payloads are\n   generated using conditional GAN. The generated
  attack samples can be\n   used to target web applications protected by WA
 Fs in an automated\n   manner. This model scales well on a large-scale web
  application\n   platform and saves significant effort invested by the pen
 etration\n   testing team.\n   '\n\n   1. #FlamingoThirdFloor\n\n\n
DTEND:20230811T184500Z
DTSTART:20230811T180000Z
LOCATION:APV - Flamingo - Savoy - AppSec Village - Main Stage
SUMMARY:Generative Adversarial Network (GAN) based autonomous penetration t
 esting for Web Applications
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