Intrusion detection in cloud computing based on time series anomalies utilizing machine learning
The growth of cloud computing is hindered by concerns about privacy and security. Despite
the widespread use of network intrusion detection systems (NIDS), the issue of false …
the widespread use of network intrusion detection systems (NIDS), the issue of false …
Impact of feature selection methods on machine learning-based for detecting DDoS attacks: Literature review
Cybersecurity attacks are becoming increasingly sophisticated and increasing with the
development of technology so that they present threats to both the private and public …
development of technology so that they present threats to both the private and public …
A Deep Learning‐Based Framework for Feature Extraction and Classification of Intrusion Detection in Networks
An intrusion detection system, often known as an IDS, is extremely important for preventing
attacks on a network, violating network policies, and gaining unauthorized access to a …
attacks on a network, violating network policies, and gaining unauthorized access to a …
Optimized and efficient image-based IoT malware detection method
With the widespread use of IoT applications, malware has become a difficult and
sophisticated threat. Without robust security measures, a massive volume of confidential and …
sophisticated threat. Without robust security measures, a massive volume of confidential and …
Review of filtering based feature selection for Botnet detection in the Internet of Things
Botnets are a major security threat in the Internet of Things (IoT), posing significant risks to
user privacy, network availability, and the integrity of IoT devices. With the increasing …
user privacy, network availability, and the integrity of IoT devices. With the increasing …
[HTML][HTML] Traffic Feature Selection and Distributed Denial of Service Attack Detection in Software-Defined Networks Based on Machine Learning
D Han, H Li, X Fu, S Zhou - Sensors, 2024 - mdpi.com
As 5G technology becomes more widespread, the significant improvement in network speed
and connection density has introduced more challenges to network security. In particular …
and connection density has introduced more challenges to network security. In particular …
Review of intrusion detection system in cyber‐physical system based networks: Characteristics, industrial protocols, attacks, data sets and challenges
Abstract Cyber‐Physical Systems (CPSs) provide critical infrastructure for the betterment of
human lives thereby integrating cyber and physical components but the fusion of physical …
human lives thereby integrating cyber and physical components but the fusion of physical …
[PDF][PDF] Machine learning to improve the performance of anomaly-based network intrusion detection in big data
With the rapid growth of digital technology communications are overwhelmed by network
data traffic. The demand for the internet is growing every day in today's cyber world, raising …
data traffic. The demand for the internet is growing every day in today's cyber world, raising …
Large-scale IoT attack detection scheme based on LightGBM and feature selection using an improved salp swarm algorithm
W Chen, H Yang, L Yin, X Luo - Scientific Reports, 2024 - nature.com
Due to the swift advancement of the Internet of Things (IoT), there has been a significant
surge in the quantity of interconnected IoT devices that send and exchange vital data across …
surge in the quantity of interconnected IoT devices that send and exchange vital data across …
Hybrid feature selection method for intrusion detection systems based on an improved intelligent water drop algorithm
A critical task and a competitive research area is to secure networks against attacks. One of
the most popular security solutions is Intrusion Detection Systems (IDS). Machine learning …
the most popular security solutions is Intrusion Detection Systems (IDS). Machine learning …