Results 11 to 20 of about 1,173,800 (295)
Malware Evasion Attack and Defense [PDF]
2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), 2019 Machine learning (ML) classifiers are vulnerable to adversarial examples. An adversarial example is an input sample which is slightly modified to induce misclassification in an ML classifier.
Yonghong Huang +5 more
semanticscholar +4 more sources
Attackability Characterization of Adversarial Evasion Attack on Discrete Data [PDF]
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020 Evasion attack on discrete data is a challenging, while practically interesting research topic. It is intrinsically an NP-hard combinatorial optimization problem.
Yutong Wang +6 more
semanticscholar +2 more sources
An Evasion Attack against Stacked Capsule Autoencoder [PDF]
Algorithms, 2022 Capsule networks are a type of neural network that use the spatial relationship between features to classify images. By capturing the poses and relative positions between features, this network is better able to recognize affine transformation and ...
Jiazhu Dai, Siwei Xiong
doaj +3 more sources
Complement Attack against Aspergillus and Corresponding Evasion Mechanisms
Interdisciplinary Perspectives on Infectious Diseases, 2012 Invasive aspergillosis shows a high mortality rate particularly in immunocompromised patients. Perpetually increasing numbers of affected patients highlight the importance of a clearer understanding of interactions between innate immunity and fungi ...
Cornelia Speth, Günter Rambach
doaj +3 more sources
Adversarial attacks against supervised machine learning based network intrusion detection systems
PLoS ONE, 2022 Adversarial machine learning is a recent area of study that explores both adversarial attack strategy and detection systems of adversarial attacks, which are inputs specially crafted to outwit the classification of detection systems or disrupt the ...
Ebtihaj Alshahrani +3 more
doaj +2 more sources
Fall of Giants: How popular text-based MLaaS fall against a simple evasion attack [PDF]
European Symposium on Security and Privacy, 2021 The increased demand for machine learning applications made companies offer Machine-Learning-as-a-Service (MLaaS). In MLaaS (a market estimated 8000M USD by 2025), users pay for well-performing ML models without dealing with the complicated training ...
Luca Pajola, M. Conti
semanticscholar +1 more source
Countering Evasion Attacks for Smart Grid Reinforcement Learning-Based Detectors
IEEE Access, 2023 Fraudulent customers in smart power grids employ cyber-attacks by manipulating their smart meters and reporting false consumption readings to reduce their bills.
Ahmed T. El-Toukhy +4 more
doaj +1 more source
Kernel-based adversarial attacks and defenses on support vector classification
Digital Communications and Networks, 2022 While malicious samples are widely found in many application fields of machine learning, suitable countermeasures have been investigated in the field of adversarial machine learning. Due to the importance and popularity of Support Vector Machines (SVMs),
Wanman Li +3 more
doaj +1 more source
Attack Tree Analysis for Adversarial Evasion Attacks
2023 IEEE 28th Pacific Rim International Symposium on Dependable Computing (PRDC), 2023 10 ...
Yamaguchi, Yuki, Aoki, Toshiaki
openaire +2 more sources
Adversarial Feature Selection Against Evasion Attacks [PDF]
IEEE Transactions on Cybernetics, 2016 Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed.
Zhang F +4 more
openaire +4 more sources