Black Hat·44 min
Security researchers examine technical aspects of Applied Machine Learning for Data Exfil and Other Fun Topics.
machine-learningappliedmachine+2
machine-learning
275 talks tagged with this topic.
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Black Hat·20 min
Dou Goodman · Yang Wang · Hao Xin
Analysts investigate attack surfaces and defenses concerning Attacking and Defending Machine Learning Applications of Public Cloud.
machine-learningattackingdefending+3
Black Hat·51 min
Industry experts analyze emerging threats surrounding Beyond the Blacklists: Detecting Malicious URL Through Machine Learning.
machine-learningblacklistdetecting+1
Black Hat·25 min
Engineers explore architecture and security mechanisms for Bot vs. Bot for Evading Machine Learning Malware Detection.
machine-learningdetectionmalware-detection
Black Hat·51 min
Presenters detail vulnerability discovery and exploitation in Defeating Machine Learning: What Your Security Vendor Is Not Telling You.
machine-learningdefeatingmachine+1
Black Hat·27 min
Machine Learning
Security researchers examine technical aspects of Effective Vulnerability Discovery with Machine Learning.
machine-learningvulnerability-discoveryeffective+3
Black Hat·28 min
Garbage In, Garbage Out: How Purportedly Great Machine Learning Models can be Screwed Up by Bad Data
Garbage In · Garbage Out
Security researchers examine technical aspects of Garbage In, Garbage Out: How Purportedly Great Machine Learning Models can be Screwed Up by Bad Data.
machine-learninggarbagepurportedly+2
Black Hat·11 min
Analysts investigate attack surfaces and defenses concerning How is Machine Learning and Data Science Transforming Cyber Security?.
machine-learningdata-sciencemachine+1
Black Hat·35 min
Joshua Saxe
Security researchers examine technical aspects of How We Can Power Real Security Machine Learning Progress Through Open Algorithms and Benchmarks.
machine-learningalgorithmsmachine+1
Black Hat·31 min
Security researchers examine technical aspects of Practical Defenses Against Adversarial Machine Learning.
machine-learningadversarial-machine-learningpractical+1
Black Hat·50 min
Analysts investigate attack surfaces and defenses concerning Protecting the Protector, Hardening Machine Learning Defenses Against Adversarial Attacks.
machine-learninghardeningadversarial-attacks
Black Hat·29 min
Joshua Saxe
Engineers explore architecture and security mechanisms for USA 2013 - CrowdSource: Crowd Trained Machine Learning Model for Malware Capability Det..
machine-learningcrowdsourcecrowd+2
Black Hat·57 min
Alexandre Pinto
Industry experts analyze emerging threats surrounding USA 2013 - Defending Networks with Incomplete Information: A Machine Learning Approach.
machine-learningnetworksdefending+2
Black Hat·24 min
Presenters detail vulnerability discovery and exploitation in Wire Me Through Machine Learning.
machine-learningwiremachine+1
Black Hat·44 min
Presenters detail vulnerability discovery and exploitation in Zen and the Art of Adversarial Machine Learning.
machine-learningadversarial-machine-learningadversarial+2
Blacks in Cybersecurity Village·33 min
Levone Campbell
Explores the dual role of artificial intelligence in scaling hyper-targeted phishing campaigns while powering real-time behavioral defenses.
aiphishingai-security+2
Briefings·41 min
David Mahdi · Ido Rozen
However, these methods struggle against adaptive fraud schemes, emerging attack vectors, and low-frequency fraud patterns.
machine-learningevasionfraud+3
Briefings·41 min
Ben Nassi · Or Yair · Stav Cohen
Researchers uncover indirect prompt injection attack surfaces in workspace agents, demonstrating unauthorized cross-application data extraction.
security-researchmachine-learningphishing+3
Briefings·37 min
Ji'an Zhou · Li'shuo Song
PyTorch is a machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.
cloudmachine-learningai+3
Briefings·22 min
Hariharan Shanmugam
Apple's on device AI frameworks CoreML, Vision, AVFoundation enable powerful automation and advanced media processing.
aiencryptionmachine-learning+3
Car Hacking Village·19 min
Ravi Rajput
Introduces a sequence-learning approach that analyzes inter-signal correlations in raw CAN bus payloads to detect stealthy contextual automotive attacks.
automotivecan-busanomaly-detection+2
CODE BLUE·48 min
Isao Takaesu
Security researchers examine technical aspects of [CB16] Method of detecting vulnerability in WebApps using Machine Learning by Isao Takaesu.
machine-learningmethoddetecting+2
CODE BLUE·26 min
Industry experts analyze emerging threats surrounding ［CB20］Vulnerabilities of Machine Learning Infrastructure.
machine-learningvulnerabilitiesinfrastructure
CODE BLUE·1 hr
2015 investigates Making & Breaking Machine Learning Anomaly Detectors in Real Life by Clarence Chio.
machine-learningmakingbreaking+3