Black Hat·47 min
Presenters detail vulnerability discovery and exploitation in A Hacker's Guide to Reducing Side-Channel Attack Surfaces Using Deep-Learning.
side-channeldeep-learningguide+2
deep-learning
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Black Hat·41 min
Engineers explore architecture and security mechanisms for Deep Learning On Disassembly.
deep-learningdeeplearning+1
Black Hat·48 min
Presenters detail vulnerability discovery and exploitation in Lowering the Bar: Deep Learning for Side Channel Analysis.
side-channeldeep-learninglowering+3
Black Hat·26 min
Analysts investigate attack surfaces and defenses concerning The Applications Of Deep Learning On Traffic Identification.
deep-learningapplicationdeep+3
Black Hat·40 min
Karim Abdellatif
Presenters detail vulnerability discovery and exploitation in Using Deep Learning Attribution Methods for Fault Injection Attacks.
injection-attacksattributiondeep-learning+2
Ekoparty Security Conference·34 min
Explores #Eko2020 Main Track | AudioNet: A deep learning convolutional approach to audio spoofing detection and evaluates key implications for security practitioners.
eko2020-mainmain-tracktrack-audionet+2
hardwear.io·35 min
Industry experts analyze emerging threats surrounding Practical Hardware Attacks on Deep Learning | Sanghyun Hong | Hardwear.io Webinar 2021.
hardwaredeep-learninghardware-attacks
IEEE Symposium on Security and Privacy·2 hr 30 min
Analysts investigate attack surfaces and defenses concerning [DLS2021] 4th Deep Learning And Security Workshop -- Part 1.
deep-learningworkshopdls2021+3
IEEE Symposium on Security and Privacy·3 hr 29 min
Analysts investigate attack surfaces and defenses concerning [DLS2021] 4th Deep Learning And Security Workshop -- Part 2.
deep-learningworkshopdls2021+3
IEEE Symposium on Security and Privacy·1 hr 9 min
Industry experts analyze emerging threats surrounding 3rd Deep Learning and Security Workshop Part I.
deep-learningworkshopdeep+2
IEEE Symposium on Security and Privacy·1 hr 47 min
Presenters detail vulnerability discovery and exploitation in 3rd Deep Learning and Security Workshop Part II.
deep-learningworkshopdeep+2
IEEE Symposium on Security and Privacy·1 hr 50 min
Engineers explore architecture and security mechanisms for 3rd Deep Learning and Security Workshop Part III.
deep-learningworkshopdeep+2
IEEE Symposium on Security and Privacy·2 hr
Presenters detail vulnerability discovery and exploitation in 3rd Deep Learning and Security Workshop Part IV.
deep-learningworkshopdeep+2
IEEE Symposium on Security and Privacy·15 min
Analysts investigate attack surfaces and defenses concerning A Deep Learning Approach to Fast, Format-agnostic Detection of Malicious Web Content.
webdetectiondeep-learning
IEEE Symposium on Security and Privacy·16 min
Security researchers examine technical aspects of Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers.
deep-learningblack-boxgeneration+3
IEEE Symposium on Security and Privacy·17 min
Presenters detail vulnerability discovery and exploitation in Comprehensive Privacy Analysis of Deep Learning.
privacydeep-learningcomprehensive+3
IEEE Symposium on Security and Privacy·19 min
Industry experts analyze emerging threats surrounding Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models.
deep-learningcopyrightframework
IEEE Symposium on Security and Privacy·23 min
Presenters detail vulnerability discovery and exploitation in Differentially Private Model Publishing For Deep Learning.
deep-learningdifferentiallyprivate+3
IEEE Symposium on Security and Privacy·19 min
Analysts investigate attack surfaces and defenses concerning Hark: A Deep Learning System for Navigating Privacy Feedback at Scale.
privacydeep-learninghark+3
IEEE Symposium on Security and Privacy·16 min
ABSTRACT This paper
Analysts investigate attack surfaces and defenses concerning HeNet: A Deep Learning Approach on Intel® Processor Trace for Effective Exploit Detection.
detectiondeep-learninghenet+3
IEEE Symposium on Security and Privacy·27 min
Engineers explore architecture and security mechanisms for Membership Inference Attacks against Adversarially Robust Deep Learning Models.
deep-learningmembershipinference+2
IEEE Symposium on Security and Privacy·15 min
Presenters detail vulnerability discovery and exploitation in REDEEM MYSELF: Purifying Backdoors in Deep Learning Models using Self Attention Distillation.
deep-learningredeemmyself+3
IEEE Symposium on Security and Privacy·13 min
Industry experts analyze emerging threats surrounding Security Risks in Deep Learning Implementation.
deep-learningriskdeep+3
IEEE Symposium on Security and Privacy·17 min
Engineers explore architecture and security mechanisms for Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering.
deep-learningspectral-dpdifferentially+3