Black Hat·44 min
Engineers explore architecture and security mechanisms for Deep Neural Networks for Hackers: Methods, Applications, and Open Source Tools.
open-sourceneural-networksnetworks
neural-networks
34 talks tagged with this topic.
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Black Hat·40 min
Presenters detail vulnerability discovery and exploitation in Repurposing Neural Networks to Generate Synthetic Media for Information Operations.
neural-networksmedianetworks+1
Black Hat·30 min
The Cost of Learning from the Best: How Prior Knowledge Weakens the Security of Deep Neural Networks
Security researchers examine technical aspects of The Cost of Learning from the Best: How Prior Knowledge Weakens the Security of Deep Neural Networks.
neural-networksnetworkscost+2
CypherCon 8.0·49 min
Ben Hawks | CypherCon 8.0
Ben Hawks | CypherCon 8.0 examines AI Ward - Introduction to Neural Networks.
aineural-networksnetworks
HITCON·48 min
Presenters detail vulnerability discovery and exploitation in Malware Behavior Analysis Acceleration based on Graph Neural Networks｜HITCON PEACE 2022.
neural-networksgraphnetworks
IEEE Symposium on Security and Privacy·14 min
Analysts investigate attack surfaces and defenses concerning AI2: Safety and Robustness Certification of Neural Networks.
safetyneural-networksrobustness+2
IEEE Symposium on Security and Privacy·22 min
Engineers explore architecture and security mechanisms for Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks.
neural-networksnetworksdistillation+3
IEEE Symposium on Security and Privacy·16 min
Industry experts analyze emerging threats surrounding LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis.
neural-networksgraphnetworks
IEEE Symposium on Security and Privacy·19 min
Engineers explore architecture and security mechanisms for Model Orthogonalization: Class Distance Hardening in Neural Networks for Better Security.
neural-networkshardeningnetworks
IEEE Symposium on Security and Privacy·18 min
Presenters detail vulnerability discovery and exploitation in Model Stealing Attacks Against Inductive Graph Neural Networks.
neural-networksgraphnetworks
IEEE Symposium on Security and Privacy·19 min
Engineers explore architecture and security mechanisms for Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks.
backdoorneural-networksnetworks
IEEE Symposium on Security and Privacy·17 min
Engineers explore architecture and security mechanisms for Neutaint: Efficient Dynamic Taint Analysis with Neural Networks.
neural-networksnetworksneutaint+3
IEEE Symposium on Security and Privacy·15 min
ShadowNet: A Secure and Efficient On-device Model Inference System for Convolutional Neural Networks
Security researchers examine technical aspects of ShadowNet: A Secure and Efficient On-device Model Inference System for Convolutional Neural Networks.
neural-networksnetworksshadownet+3
IEEE Symposium on Security and Privacy·15 min
Security researchers examine technical aspects of SoK: Certified Robustness for Deep Neural Networks.
neural-networksrobustnessnetworks
IEEE Symposium on Security and Privacy·21 min
Presenters detail vulnerability discovery and exploitation in Towards Evaluating the Robustness of Neural Networks.
neural-networksrobustnessnetworks
IEEE Symposium on Security and Privacy·21 min
Industry experts analyze emerging threats surrounding WtaGraph: Web Tracking and Advertising Detection using Graph Neural Networks.
webdetectionneural-networks+2
IEEE Symposium on Security and Privacy 2025·7 min
520 CipherSteal: Stealing Input Data from TEE-Shielded Neural Networks with Ciphertext Side Channels
Security researchers examine technical aspects of 520 CipherSteal: Stealing Input Data from TEE-Shielded Neural Networks with Ciphertext Side Channels.
neural-networksnetworksciphersteal+2
Microsoft Security Response Center (MSRC)·22 min
Security researchers examine technical aspects of BlueHat v18|| Malicious User profiling using deep neural networks.
neural-networksprofilingnetworks
PROIDEA Events·50 min
Analysts investigate attack surfaces and defenses concerning JDD 2018: Building Deep Neural Networks using Deep Learning for Java(DL4J) by Olgun Aydin.
deep-learningneural-networksnetworks
Hack In The Box Security Conference·1 hr
Ivan Novikov
Ivan Novikov explores #HITBGSEC 2017 Conf D2 - Neuralfuzz: Neural Networks For Fuzzing Web Apps.
fuzzingwebneural-networks+2
Hack In The Box Security Conference·31 min
Jay Xiong
Jay Xiong examines #HITBGSEC COMMSEC: Hacking Object Detectors Is Just Like Training Neural Networks.
trainingneural-networksnetworks
IEEE Symposium on Security and Privacy·9 min
Presenters detail vulnerability discovery and exploitation in 95 Preserving Node level Privacy in Graph Neural Networks ZH X.
privacyneural-networksgraph+1
RSAC Cybersecurity·48 min
Analysts investigate attack surfaces and defenses concerning Attacking Machine Learning: On the Security and Privacy of Neural Networks.
privacymachine-learningneural-networks+1
CarolinaCon·57 min
Riccardo Terrell
Fast Neural Networks... a no brainer! The Actor model as neuron (by Riccardo Terrell).
neural-networksnetworksfast+3