A survey on artificial intelligence techniques for security event correlation: models, challenges, and opportunities
Abstract Information systems need to process a large amount of event monitoring data. The
process of finding the relationships between events is called correlation, which creates a …
process of finding the relationships between events is called correlation, which creates a …
In-depth feature selection for the statistical machine learning-based botnet detection in IoT networks
Attackers compromise insecure IoT devices to expand their botnets in order to launch more
influential attacks against their victims. In various studies, machine learning has been used …
influential attacks against their victims. In various studies, machine learning has been used …
Efficient detection of botnet traffic by features selection and decision trees
J Velasco-Mata, V González-Castro… - IEEE …, 2021 - ieeexplore.ieee.org
Botnets are one of the online threats with the most significant presence, causing billionaire
losses to global economies. Nowadays, the increasing number of devices connected to the …
losses to global economies. Nowadays, the increasing number of devices connected to the …
Feature selection algorithms in intrusion detection system: A survey
S Maza, M Touahria - KSII Transactions on Internet and Information …, 2018 - koreascience.kr
Regarding to the huge number of connections and the large flow of data on the Internet,
Intrusion Detection System (IDS) has a difficulty to detect attacks. Moreover, irrelevant and …
Intrusion Detection System (IDS) has a difficulty to detect attacks. Moreover, irrelevant and …
Demystifying the role of public intrusion datasets: a replication study of DoS network traffic data
Public intrusion datasets are contributing to make security research accessible to a large
community of users, but are often trusted and reused neglecting the actual impact of the …
community of users, but are often trusted and reused neglecting the actual impact of the …
Feature selection for intrusion detection using new multi-objective estimation of distribution algorithms
S Maza, M Touahria - Applied Intelligence, 2019 - Springer
The manipulation of a large number of features has become a critical problem in Intrusion
Detection Systems (IDS). Therefore, Feature Selection (FS) is integrated to select the …
Detection Systems (IDS). Therefore, Feature Selection (FS) is integrated to select the …
USB-IDS-1: a public multilayer dataset of labeled network flows for IDS evaluation
M Catillo, A Del Vecchio, L Ocone… - 2021 51st Annual …, 2021 - ieeexplore.ieee.org
The scarceness of publicly available data from real-life operational networks is a long-
standing problem for the security research community. Many public intrusion detection …
standing problem for the security research community. Many public intrusion detection …
A case study with CICIDS2017 on the robustness of machine learning against adversarial attacks in intrusion detection
Intrusion detection systems (IDS) play a key role to assure security properties of modern
computer networks. IDS are often based on machine and deep learning techniques; as …
computer networks. IDS are often based on machine and deep learning techniques; as …
MAAC: Novel alert correlation method to detect multi-step attack
X Wang, X Gong, L Yu, J Liu - … on Trust, Security and Privacy in …, 2021 - ieeexplore.ieee.org
With the continuous improvement of attack methods, there are more and more distributed,
complex, targeted attacks in which the attackers use combined attack methods to achieve …
complex, targeted attacks in which the attackers use combined attack methods to achieve …
Security in wireless sensor networks: Attacks and evasion
Wireless Sensor network is a typical research area, where energy efficiency is a key issue. It
is popular due to low cost solution and real world problem solving features. WSN is also very …
is popular due to low cost solution and real world problem solving features. WSN is also very …