Titlebook: Risks and Security of Internet and Systems; 15th International C Joaquin Garcia-Alfaro,Jean Leneutre,Reda Yaich Conference proceedings 2021

INERT

A Deeper Analysis of Adversarial Examples in Intrusion Detection for intrusion detection. However, and despite the progress made in this area, machine learning models have been found to be vulnerable to slightly modified data samples called adversarial examples. Thereby, a small and well-computed perturbation may allow adversaries to evade intrusion detection sy

opportune

Implementation Flaws in TLS Stacks: Lessons Learned and Study of TLS 1.3 Benefitsws affecting a wide range of independent stacks. The infamous Heartbleed bug, was estimated to affect more than 20% of the most popular HTTPS servers. We propose a structured review of these implementation flaws. By considering their consequences but also their root causes, we present some lessons l

etidronate

Security Through Transparency and Openness in Computer Designn cybersecurity updates of the software and firmware running on their devices to keep their privacy and data protected from malicious use. Businesses and governments procure technology which they expect to run for long periods and be kept in line with the state of the art in security. Presently, how

跟隨

An ML Behavior-Based Security Control for Smart Home Systemsy applications (called SmartApps). However, intentional/unintentional issues would make SmartApps deviate from their expected behavior, putting the SHS owner’s security at risk. To address this issue, in this paper, we introduce an ML behavior-based approach to prevent malicious control of SHS devic

Blood-Vessels

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豎琴

maverick

Premium Access to Convolutional Neural Networksvileged users. Our solution relies on a degraded implementation which can be corrected thanks to a PIN. We explain how to select a few parameters in an NN so as to maximize the gap in the accuracy between the premium and the degraded modes. We report experiments on an implementation of our proposal