Closeness and uncertainty aware adversarial examples detection in adversarial machine learning
Künye
Tuna, Ö. F., Çatak, F. Ö. & Eskil, M. T. (2022). Closeness and uncertainty aware adversarial examples detection in adversarial machine learning. Computers and Electrical Engineering, 101, 1-12. doi:10.1016/j.compeleceng.2022.107986Özet
While deep learning models are thought to be resistant to random perturbations, it has been demonstrated that these architectures are vulnerable to deliberately crafted perturbations, albeit being quasi-imperceptible. These vulnerabilities make it challenging to deploy Deep Neural Network (DNN) models in security-critical areas. Recently, many research studies have been conducted to develop defense techniques enabling more robust models. In this paper, we target detecting adversarial samples by differentiating them from their clean equivalents. We investigate various metrics for detecting adversarial samples. We first leverage moment-based predictive uncertainty estimates of DNN classifiers derived through Monte-Carlo (MC) Dropout Sampling. We also introduce a new method that operates in the subspace of deep features obtained by the model. We verified the effectiveness of our approach on different datasets. Our experiments show that these approaches complement each other, and combined usage of all metrics yields 99 % ROC-AUC adversarial detection score for well-known attack algorithms.
Kaynak
Computers and Electrical EngineeringCilt
101İlgili Öğeler
Başlık, yazar, küratör ve konuya göre gösterilen ilgili öğeler.
-
Extension of conventional co-training learning strategies to three-view and committee-based learning strategies for effective automatic sentence segmentation
Dalva, Doğan; Güz, Ümit; Gürkan, Hakan (IEEE, 2018)The objective of this work is to develop effective multi-view semi-supervised machine learning strategies for sentence boundary classification problem when only small sets of sentence boundary labeled data are available. ... -
Effective semi-supervised learning strategies for automatic sentence segmentation
Dalva, Doğan; Güz, Ümit; Gürkan, Hakan (Elsevier Science BV, 2018-04-01)The primary objective of sentence segmentation process is to determine the sentence boundaries of a stream of words output by the automatic speech recognizers. Statistical methods developed for sentence segmentation requires ... -
Aynı oteli temsil eden farklı kayıtlar için akıllı eşleştirme
Bayrak, Ahmet Tuğrul; Özbek, Eyüp Erkan; Kestepe, Sedat; Yıldız, Olcay Taner (Institute of Electrical and Electronics Engineers Inc., 2019-09)Otel sayısının her geçen gün arttığı turizm sektöründe, aracı firmaların tüm oteller ile ayrı ayrı çalışma imkanı bulunmadığından, firmalar dünya üzerinde bir çok otelle anlaşması bulunan servis sağlayıcılarıyla beraber ...