Results 71 to 80 of about 4,416 (262)

Beyond the Adversarial Rivalry: A Developmental Rights‐Based Model for Minor‐on‐Minor Crime, Part 2

Behavioral Sciences &the Law, EarlyView.
ABSTRACT When children harm children, the conventional victim–perpetrator framework is ill‐equipped to address the developmental, relational, and institutional complexities involved. While juvenile justice scholarship increasingly emphasizes rehabilitation, and victims' rights literature has advanced child‐sensitive protections, minor‐on‐minor ...
Tali Gal, Ruthy Lowenstein Lazar
wiley   +1 more source

Exploring Synergy of Denoising and Distillation: Novel Method for Efficient Adversarial Defense

Applied Sciences
Escalating advancements in artificial intelligence (AI) has prompted significant security concerns, especially with its increasing commercialization. This necessitates research on safety measures to securely utilize AI models.
Inpyo Hong, Sokjoon Lee
doaj   +1 more source

Legal Professionals Use an Implicit Checklist to Assess Expert Witness Credibility

Behavioral Sciences &the Law, EarlyView.
ABSTRACT In a court of law, some forms of evidence are too technical to interpret without the help of an expert witness. However, expert testimony sometimes leads to wrongful conviction. We used an online survey to quantitatively compare how legal professionals (n = 122) and lay people (n = 109) understood what makes an expert witness credible.
Mahensingh Deonaran, Yvan I. Russell, Mandeep K. Dhami   +2 more
wiley   +1 more source

Adversarial Backdoor Defense in CLIP

CoRR
Multimodal contrastive pretraining, exemplified by models like CLIP, has been found to be vulnerable to backdoor attacks. While current backdoor defense methods primarily employ conventional data augmentation to create augmented samples aimed at feature alignment, these methods fail to capture the distinct features of backdoor samples, resulting in ...
Junhao Kuang, Siyuan Liang 0004, Jiawei Liang, Kuanrong Liu, Xiaochun Cao   +4 more
openaire   +2 more sources

Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN

CoRR, 2017
We propose a novel technique to make neural network robust to adversarial examples using a generative adversarial network. We alternately train both classifier and generator networks. The generator network generates an adversarial perturbation that can easily fool the classifier network by using a gradient of each image.
Hyeungill Lee, Sungyeob Han, Jungwoo Lee 0001   +2 more
openaire   +2 more sources

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

A divide-and-conquer reconstruction method for defending against adversarial example attacks

Visual Intelligence
In recent years, defending against adversarial examples has gained significant importance, leading to a growing body of research in this area. Among these studies, pre-processing defense approaches have emerged as a prominent research direction. However,
Xiyao Liu, Jiaxin Hu, Qingying Yang, Ming Jiang, Jianbiao He, Hui Fang   +5 more
doaj   +1 more source

Adversarial Attacks and Defense on Texts: A Survey

CoRR, 2020
Deep learning models have been used widely for various purposes in recent years in object recognition, self-driving cars, face recognition, speech recognition, sentiment analysis, and many others. However, in recent years it has been shown that these models possess weakness to noises which force the model to misclassify.
Aminul Huq, Mst. Tasnim Pervin
openaire   +2 more sources

Knowledge sourcing, geopolitics, and FDI: An empirical analysis on the US green and digital sectors

Global Strategy Journal, EarlyView.
Abstract Research Summary This paper examines how foreign direct investment (FDI) shapes firms' sourcing of knowledge in the digital and green domains under rising geopolitical frictions. We assemble a firm–country dyadic panel (2013–2020) linking US patent backward citations to firms' FDI, enriched with bilateral geopolitical distance and host‐country
Alberto Maria Radici
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