[PDF][PDF] Collaborative ids framework for cloud
Cloud computing is used extensively to deliver utility computing over the Internet. Defending
network accessible Cloud resources and services from various threats and attacks is of great …
network accessible Cloud resources and services from various threats and attacks is of great …
A data generation framework for extremely rare case signals
T Chalongvorachai, K Woraratpanya - Heliyon, 2021 - cell.com
Unlike data augmentation, data generation for extremely rare cases is an approach that can
spawn a significant number of high-quality samples based on very few original data. This …
spawn a significant number of high-quality samples based on very few original data. This …
Anomaly detection using digital signature of network segment with adaptive ARIMA model and Paraconsistent Logic
Detecting anomalies accurately in network traffic behavior is essential for a variety of
network management and security tasks. This paper presents an anomaly detection …
network management and security tasks. This paper presents an anomaly detection …
System light-loading technology for mHealth: manifold-learning-based medical data cleansing and clinical trials in WE-CARE project
Cardiovascular disease (CVD) is a major issue to public health. It contributes 41% to the
Chinese death rate each year. This huge loss encouraged us to develop a Wearable …
Chinese death rate each year. This huge loss encouraged us to develop a Wearable …
GDTW-P-SVMs: Variable-length time series analysis using support vector machines
We describe a new technique for sequential data analysis, called GDTW-P-SVMs. It is a
maximum margin method for the construction of classifiers with variable-length input series …
maximum margin method for the construction of classifiers with variable-length input series …
[PDF][PDF] Detection, classification and visualization of anomalies using generalized entropy metrics
BM Tellenbach - 2012 - research-collection.ethz.ch
Today, the Internet allows virtually anytime, anywhere access to a seemingly unlimited
supply of information and services. Statistics such as the six-fold increase of US online retail …
supply of information and services. Statistics such as the six-fold increase of US online retail …
Study and evaluation of unsupervised algorithms used in network anomaly detection
J Dromard, P Owezarski - … of the Future Technologies Conference (FTC) …, 2020 - Springer
Network anomalies are unusual traffic mainly induced by network attacks or network failures.
Therefore it is important for network operators as end users to detect and diagnose them to …
Therefore it is important for network operators as end users to detect and diagnose them to …
Detecting anomalies in the data residing over the cloud
D Arora, KF Li - 2017 31st International Conference on …, 2017 - ieeexplore.ieee.org
With more companies turning towards cloud computing for storage and processing of their
data, the security of the cloud becomes essential. However, cloud computing is vulnerable to …
data, the security of the cloud becomes essential. However, cloud computing is vulnerable to …
[PDF][PDF] Energy data anomaly detection using unsupervised learning techniques
Smart Grid is a rising advancement that can fulfill requests by incorporating prompted
Information and Communications Technology (ICT). The specific relationship of the …
Information and Communications Technology (ICT). The specific relationship of the …
Suspicious ARP Activity Detection and Clustering Based on Autoencoder Neural Networks
Y Sun, H Ochiai, H Esaki - 2022 IEEE 19th Annual Consumer …, 2022 - ieeexplore.ieee.org
The rapidly increasing number of smart devices on the Internet necessitates an efficient
inspection system for safeguarding our networks from suspicious activities such as Address …
inspection system for safeguarding our networks from suspicious activities such as Address …