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Computer Security

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FastEmbed: Predicting vulnerability exploitation possibility based on ensemble machine learning algorithm.

PloS one
In recent years, the number of vulnerabilities discovered and publicly disclosed has shown a sharp upward trend. However, the value of exploitation of vulnerabilities varies for attackers, considering that only a small fraction of vulnerabilities are...

Deep feature transfer learning for trusted and automated malware signature generation in private cloud environments.

Neural networks : the official journal of the International Neural Network Society
This paper presents TrustSign, a novel, trusted automatic malware signature generation method based on high-level deep features transferred from a VGG-19 neural network model pretrained on the ImageNet dataset. While traditional automatic malware sig...

Privacy-enhanced multi-party deep learning.

Neural networks : the official journal of the International Neural Network Society
In multi-party deep learning, multiple participants jointly train a deep learning model through a central server to achieve common objectives without sharing their private data. Recently, a significant amount of progress has been made toward the priv...

Enhancing the security of patients' portals and websites by detecting malicious web crawlers using machine learning techniques.

International journal of medical informatics
INTRODUCTION: There is increasing demand for access to medical information via patients' portals. However, one of the challenges towards widespread utilisation of such service is maintaining the security of those portals. Recent reports show an alarm...

Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.

The Journal of pathology
In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated pa...

AULD: Large Scale Suspicious DNS Activities Detection via Unsupervised Learning in Advanced Persistent Threats.

Sensors (Basel, Switzerland)
In recent years, sensors in the Internet of things have been commonly used in Human's life. APT (Advanced Persistent Threats) has caused serious damage to network security and the sensors play an important role in the attack process. For a long time,...

Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Data sharing accelerates scientific progress but sharing individual-level data while preserving patient privacy presents a barrier.

When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time.

Neural computation
A significant threat to the recent, wide deployment of machine learning-based systems, including deep neural networks (DNNs), is adversarial learning attacks. The main focus here is on evasion attacks against DNN-based classifiers at test time. While...

Data-Driven Automated Cardiac Health Management with Robust Edge Analytics and De-Risking.

Sensors (Basel, Switzerland)
Remote and automated healthcare management has shown the prospective to significantly impact the future of human prognosis rate. Internet of Things (IoT) enables the development and implementation ecosystem to cater the need of large number of releva...