Results 81 to 90 of about 7,737 (292)

Robust Adversarial Defense by Tensor Factorization

, 2023
As machine learning techniques become increasingly prevalent in data analysis, the threat of adversarial attacks has surged, necessitating robust defense mechanisms.
Alexandrov, Boian, Barron, Ryan, Bhattarai, Manish, Kaymak, Mehmet Cagri, Nebgen, Ben, Rasmussen, Kim   +5 more
core   +1 more source

The Ecological U‐Turn in Nordic Forestry: Policy Learning, Measurement, and the Retrenchment of Ecological Ambitions

Environmental Policy and Governance, EarlyView.
ABSTRACT Since the 1990s, environmental policy has shifted toward ecosystem protection and biodiversity conservation, a development often described as an ecological turn. This article argues that in practice this turn has taken the form of an ecological “U‐turn,” as environmental ambitions are subordinated to production‐oriented objectives.
Gisle Andersen, Monika Berg, Hogne Lerøy Sataøen   +2 more
wiley   +1 more source

An enhanced ensemble defense framework for boosting adversarial robustness of intrusion detection systems

Scientific Reports
Machine learning (ML) and deep neural networks (DNN) have emerged as powerful tools for enhancing intrusion detection systems (IDS) in cybersecurity.
Zeinab Awad, Magdy Zakaria, Rasha Hassan
doaj   +1 more source

Adversarial defenses via vector quantization

Neurocomputing
This is the author-accepted version of our paper published in Neurocomputing.
Zhiyi Dong, Yongyi Mao
openaire   +2 more sources

Collective Grievance Promotes Collective Action and Aggressive Intergroup Inclinations Through Dehumanization Among Conservative Members of Dominant Groups

European Journal of Social Psychology, EarlyView.
ABSTRACT Previous research has focused on disadvantaged groups seeking social change, overlooking how dominant groups mobilize to preserve the status quo. Across three studies (two correlational, one experimental), we explored how collective grievance—the feeling of being or having been collectively wronged by an outgroup—drives system‐preserving ...
Beatriz Alba, Alexandra Vázquez
wiley   +1 more source

Active Defense Against Voice Conversion Through Generative Adversarial Network [PDF]

Active defense is an important approach to counter speech deepfakes that threaten individuals’ privacy, property, and reputation. However, the existing works in this field suffer from issues such as time-consuming and ordinary defense effectiveness. This
Zhao, Guoying, Ma, Kaijie, Chen, Beijing, Dong, Shihang   +3 more
core   +1 more source

A Review of Overcurrent Protection in Smart Grids Under Cyber‐Physical Threats With a Cyber‐Physical Evaluation Framework

Energy Science &Engineering, EarlyView.
By manipulating current and voltage measurements, an assailant can induce unwanted relay action while attempting to avoid detection. Detecting advanced cyber intrusions in power protection environments requires specialised data analysis and anomaly detection methods.
Feras Alasali, Anas AlMajali, Naser Naily, Hassen Loukil, Salah AbuGhalyon, William Holderbaum, Abdelaziz Salah Saidi   +6 more
wiley   +1 more source

Towards adversarial defense with multi-stage information fusion for visual tracking

Engineering Science and Technology, an International Journal
In recent years, the effectiveness and stealth of adversarial attack methods have been continuously improving, posing significant challenges to the robustness and accuracy of visual tracking.
Peng Gao, Wen-Jia Tang, Long Xu, Fei Wang, Ru-Yue Yuan   +4 more
doaj   +1 more source

Adversarial Traces for Website Fingerprinting Defense [PDF]

Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018
Website Fingerprinting (WF) is a traffic analysis attack that enables an eavesdropper to infer the victim's web activity even when encrypted and even when using the Tor anonymity system. Using deep learning classifiers, the attack can reach up to 98% accuracy.
Mohsen Imani, Mohammad Saidur Rahman 0002, Matthew Wright 0001   +2 more
openaire   +1 more source

MAFFN-SAT: 3-D Point Cloud Defense via Multiview Adaptive Feature Fusion and Smooth Adversarial Training

Adversarial attacks pose a significant threat to deep neural networks (DNNs) used for 3-D point cloud classification, especially in safety-critical applications.
Gao, Y, Pang, S, Zhang, S, Du, A, Zhang, J   +4 more
core   +1 more source