Results 31 to 40 of about 160,235 (299)
Defenses in Adversarial Machine Learning: A Survey
CoRR, 2023 21 pages, 5 figures, 2 tables, 237 reference ...
Baoyuan Wu +9 more
openaire +2 more sources
SSQLi: A Black-Box Adversarial Attack Method for SQL Injection Based on Reinforcement Learning
Future Internet, 2023 SQL injection is a highly detrimental web attack technique that can result in significant data leakage and compromise system integrity. To counteract the harm caused by such attacks, researchers have devoted much attention to the examination of SQL ...
Yuting Guan +4 more
doaj +1 more source
Are Accuracy and Robustness Correlated?
, 2016 Machine learning models are vulnerable to adversarial examples formed by applying small carefully chosen perturbations to inputs that cause unexpected classification errors.
Boult, Terrance E. +2 more
core +1 more source
eXplainable and Reliable Against Adversarial Machine Learning in Data Analytics
IEEE Access, 2022 Machine learning (ML) algorithms are nowadays widely adopted in different contexts to perform autonomous decisions and predictions. Due to the high volume of data shared in the recent years, ML algorithms are more accurate and reliable since training and
Ivan Vaccari +4 more
doaj +1 more source
Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks
, 2019 Malware still constitutes a major threat in the cybersecurity landscape, also due to the widespread use of infection vectors such as documents. These infection vectors hide embedded malicious code to the victim users, facilitating the use of social ...
Biggio, Battista +2 more
core +1 more source
Adversarial attacks on machine learning-aided visualizations [PDF]
Journal of VisualizationAbstract Research in ML4VIS investigates how to use machine learning (ML) techniques to generate visualizations, and the field is rapidly growing with high societal impact. However, as with any computational pipeline that employs ML processes, ML4VIS approaches are susceptible to a range of ML-specific adversarial attacks ...
Takanori Fujiwara +5 more
openalex +5 more sources
NUST Journal of Engineering Sciences, 2022 The availability of information and its integrity and confidentiality are important factors in information and communication of the system security. The DDoS attack generally means Distributed denial of services generates many enormous packets to slow ...
Zahid Iqbal +3 more
doaj +1 more source
Data Driven Exploratory Attacks on Black Box Classifiers in Adversarial Domains
, 2017 While modern day web applications aim to create impact at the civilization level, they have become vulnerable to adversarial activity, where the next cyber-attack can take any shape and can originate from anywhere. The increasing scale and sophistication
Kantardzic, Mehmed, Sethi, Tegjyot Singh
core +1 more source
Adversarial support vector machine learning [PDF]
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, 2012 Many learning tasks such as spam filtering and credit card fraud detection face an active adversary that tries to avoid detection. For learning problems that deal with an active adversary, it is important to model the adversary's attack strategy and develop robust learning models to mitigate the attack. These are the two objectives of this paper.
Yan Zhou 0001 +3 more
openaire +1 more source
Meniscus Pixel Printing for Contact‐Lens Vision Sensing and Robotic Control
Advanced Functional Materials, EarlyView.A visual‐sensing contact lens is enabled by meniscus pixel printing (MPP), which rapidly patterns a 200 µm perovskite photodetector pixel in 1 s without masks, vacuum processing, or bulky equipment. A deep‐learning‐based super‐resolution reconstructs sparse on‐lens signals into 80 × 80 high‐resolution visual information, while AI‐driven eye‐tracking ...
Byung‐Hoon Gong +7 more
wiley +1 more source