Crafting Adversarial Samples for Anomaly Detectors in Industrial Control Systems

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Towards Crafting Text Adversarial Samples

Adversarial samples are strategically modified samples, which are crafted with the purpose of fooling a classifier at hand. An attacker introduces specially crafted adversarial samples to a deployed classifier, which are being mis-classified by the classifier. However, the samples are perceived to be drawn from entirely different classes and thus it becomes hard to detect the adversarial sample...

متن کامل

Crafting Adversarial Examples For Speech Paralinguistics Applications

Computational paralinguistic analysis is increasingly being used in a wide range of applications, including securitysensitive applications such as speaker verification, deceptive speech detection, and medical diagnostics. While state-ofthe-art machine learning techniques, such as deep neural networks, can provide robust and accurate speech analysis, they are susceptible to adversarial attacks. ...

متن کامل

Show-and-Fool: Crafting Adversarial Examples for Neural Image Captioning

Modern neural image captioning systems typically adopt the encoder-decoder framework consisting of two principal components: a convolutional neural network (CNN) for image feature extraction and a recurrent neural network (RNN) for caption generation. Inspired by the robustness analysis of CNN-based image classifiers to adversarial perturbations, we propose Show-and-Fool, a novel algorithm for ...

متن کامل

Generalizable Data-free Objective for Crafting Universal Adversarial Perturbations

Machine learning models are susceptible to adversarial perturbations: small changes to input that can cause large changes in output. It is also demonstrated that there exist input-agnostic perturbations, called universal adversarial perturbations, which can change the inference of target model on most of the data samples. However, existing methods to craft universal perturbations are (i) task s...

متن کامل

Adversarial Examples that Fool Detectors

An adversarial example is an example that has been adjusted to produce a wrong label when presented to a system at test time. To date, adversarial example constructions have been demonstrated for classifiers, but not for detectors. If adversarial examples that could fool a detector exist, they could be used to (for example) maliciously create security hazards on roads populated with smart vehic...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Procedia Computer Science

سال: 2021

ISSN: 1877-0509

DOI: 10.1016/j.procs.2021.03.072