A Comprehensive Survey of Machine Learning Methods for Surveillance Videos Anomaly Detection
Video Surveillance Systems (VSSs) are used in a wide range of applications including
public safety and perimeter security. They are deployed in places such as markets …
public safety and perimeter security. They are deployed in places such as markets …
AAE-DSVDD: A one-class classification model for VPN traffic identification
S Lv, C Wang, Z Wang, S Wang, B Wang, Y Zhang - Computer Networks, 2023 - Elsevier
Abstract Virtual Private Network (VPN) can provide a concealed transmission channel for
communication and protect the privacy of users. However, it also brings hidden dangers to …
communication and protect the privacy of users. However, it also brings hidden dangers to …
{VOGUES}: Validation of Object Guise using Estimated Components
Object Detection (OD) and Object Tracking (OT) are an important part of autonomous
systems (AS), enabling them to perceive and reason about their surroundings. While both …
systems (AS), enabling them to perceive and reason about their surroundings. While both …
Network policy enforcement: An intrusion prevention approach for critical infrastructures
The recent years have witnessed the growth of network attacks in the Intrusion Detection
System (IDS) domain, and zero-day exploits are also increasing at an alarming speed …
System (IDS) domain, and zero-day exploits are also increasing at an alarming speed …
Enhanced network traffic anomaly detection: Integration of tensor eigenvector centrality with low-rank recovery models
In service computing, network traffic anomaly detection is pivotal for monitoring and
identifying irregularities in network traffic to uphold the security, reliability, and stability of …
identifying irregularities in network traffic to uphold the security, reliability, and stability of …
A robust deep learning-based approach for network traffic classification using CNNs and RNNs
A Jenefa, S Sam, V Nair, BG Thomas… - 2023 4th …, 2023 - ieeexplore.ieee.org
The application of deep learning has become prevalent in the area of network traffic
classification. Deep learning has acquired widespread use in network traffic classification …
classification. Deep learning has acquired widespread use in network traffic classification …
Combining security and reliability of critical infrastructures: The concept of securability
The digital revolution has made people more dependent on ICT technology to perform
everyday tasks, whether at home or at work. The systems that support critical aspects of this …
everyday tasks, whether at home or at work. The systems that support critical aspects of this …
Anomaly detection of metallurgical energy data based on iforest-ae
Z **ong, D Zhu, D Liu, S He, L Zhao - Applied Sciences, 2022 - mdpi.com
With the proliferation of the Internet of Things, a large amount of data is generated constantly
by industrial systems, corresponding in many cases to critical tasks. It is particularly …
by industrial systems, corresponding in many cases to critical tasks. It is particularly …
Beyond known threats: A novel strategy for isolating and detecting unknown malicious traffic
Q Meng, Q Yuan, X Wang, Y Wang, G Li, Y Zhu… - Journal of Information …, 2025 - Elsevier
Traditional network intrusion detection systems excel at screening known attack types, but
face significant challenges when dealing with unseen malicious traffic, often misclassifying …
face significant challenges when dealing with unseen malicious traffic, often misclassifying …
PUNet: A Semi-Supervised Anomaly Detection Model for Network Anomaly Detection Based on Positive Unlabeled Data.
G Long, Z Zhang - Computers, Materials & Continua, 2024 - search.ebscohost.com
Network anomaly detection plays a vital role in safeguarding network security. However, the
existing network anomaly detection task is typically based on the one-class zero-positive …
existing network anomaly detection task is typically based on the one-class zero-positive …