Detection of cross-site scripting (XSS) attacks using machine learning techniques: a review
With the rising demand for E-commerce, Social Networking websites, it has become
essential to develop security protocols over the World Wide Web that can provide security …
essential to develop security protocols over the World Wide Web that can provide security …
A Comprehensive Analysis of Explainable AI for Malware Hunting
In the past decade, the number of malware variants has increased rapidly. Many
researchers have proposed to detect malware using intelligent techniques, such as Machine …
researchers have proposed to detect malware using intelligent techniques, such as Machine …
Dual-IDS: A bagging-based gradient boosting decision tree model for network anomaly intrusion detection system
The mission of an intrusion detection system (IDS) is to monitor network activities and
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
Enhancing ransomware attack detection using transfer learning and deep learning ensemble models on cloud-encrypted data
Ransomware attacks on cloud-encrypted data pose a significant risk to the security and
privacy of cloud-based businesses and their consumers. We present RANSOMNET+, a state …
privacy of cloud-based businesses and their consumers. We present RANSOMNET+, a state …
A machine learning method for distinguishing detrital zircon provenance
Zircon geochemistry provides a sensitive monitor of its parental magma composition.
However, due to the complexity of the uptake of trace elements during zircon growth …
However, due to the complexity of the uptake of trace elements during zircon growth …
Enhancing Few-Shot Learning with Integrated Data and GAN Model Approaches
Y Feng, A Shen, J Hu, Y Liang, S Wang… - ar**
M He, Y Huang, X Wang, P Wei… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Internet of Things (IoT) devices have been widely used in many fields, bringing many
conveniences to people's life. With the massive deployment and application of IoT devices …
conveniences to people's life. With the massive deployment and application of IoT devices …
Feature mining for encrypted malicious traffic detection with deep learning and other machine learning algorithms
The popularity of encryption mechanisms poses a great challenge to malicious traffic
detection. The reason is traditional detection techniques cannot work without the decryption …
detection. The reason is traditional detection techniques cannot work without the decryption …
A malicious network traffic detection model based on bidirectional temporal convolutional network with multi-head self-attention mechanism
S Cai, H Xu, M Liu, Z Chen, G Zhang - Computers & Security, 2024 - Elsevier
The increasingly frequent network intrusions have brought serious impacts to the production
and life, thus malicious network traffic detection has received more and more attention in …
and life, thus malicious network traffic detection has received more and more attention in …
An adaptable deep learning-based intrusion detection system to zero-day attacks
The main challenge of an intrusion detection system (IDS) is detecting novelties (ie, zero-
day attacks) in addition to generating a report about the known attacks (ie, classifying known …
day attacks) in addition to generating a report about the known attacks (ie, classifying known …