A Comprehensive Survey of Machine Learning Methods for Surveillance Videos Anomaly Detection

N Choudhry, J Abawajy, S Huda, I Rao - IEEE Access, 2023 - ieeexplore.ieee.org
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 …

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 …

{VOGUES}: Validation of Object Guise using Estimated Components

R Muller, Y Man, M Li, R Gerdes, J Petit… - 33rd USENIX Security …, 2024 - usenix.org
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 …

Network policy enforcement: An intrusion prevention approach for critical infrastructures

M Nkongolo, JP Van Deventer… - 2022 6th …, 2022 - ieeexplore.ieee.org
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 …

Enhanced network traffic anomaly detection: Integration of tensor eigenvector centrality with low-rank recovery models

W Lin, C Li, L Xu, K **e - IEEE Transactions on Services …, 2024 - ieeexplore.ieee.org
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 …

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 …

Combining security and reliability of critical infrastructures: The concept of securability

L Maglaras, H Janicke, MA Ferrag - Applied Sciences, 2022 - mdpi.com
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 …

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 …

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 …

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 …