Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset
An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
[HTML][HTML] Two-factor authentication scheme for mobile money: A review of threat models and countermeasures
The proliferation of digital financial innovations like mobile money has led to the rise in
mobile subscriptions and transactions. It has also increased the security challenges …
mobile subscriptions and transactions. It has also increased the security challenges …
As-ids: Anomaly and signature based ids for the internet of things
Abstract The Internet of Things (IoT) is a massively extensive environment that can manage
many diverse applications. Security is critical due to potential malicious threats and the …
many diverse applications. Security is critical due to potential malicious threats and the …
[HTML][HTML] An edge based hybrid intrusion detection framework for mobile edge computing
Abstract The Mobile Edge Computing (MEC) model attracts more users to its services due to
its characteristics and rapid delivery approach. This network architecture capability enables …
its characteristics and rapid delivery approach. This network architecture capability enables …
[HTML][HTML] Ugransome1819: A novel dataset for anomaly detection and zero-day threats
This research attempts to introduce the production methodology of an anomaly detection
dataset using ten desirable requirements. Subsequently, the article presents the produced …
dataset using ten desirable requirements. Subsequently, the article presents the produced …
Design of advanced intrusion detection systems based on hybrid machine learning techniques in hierarchically wireless sensor networks
Wireless sensor networks (WSNs) are an emerging military and civilian technology that uses
sensors. Sensor networks are hierarchical and chaotic in remote, unmonitored sites …
sensors. Sensor networks are hierarchical and chaotic in remote, unmonitored sites …
[HTML][HTML] An efficient algorithm for anomaly intrusion detection in a network
T Yerriswamy, G Murtugudde - Global transitions proceedings, 2021 - Elsevier
As the number of intrusions is increasing, intrusion detection of systems and network
infrastructures Systems (IDS) is now an active research area to develop reliable and efficient …
infrastructures Systems (IDS) is now an active research area to develop reliable and efficient …
Detection of distributed denial of service (DDoS) attacks using artificial intelligence on cloud
S Alzahrani, L Hong - 2018 IEEE World Congress on Services …, 2018 - ieeexplore.ieee.org
This research proposes a system for detecting known and unknown Distributed Denial of
Service (DDoS) Attacks. The proposed system applies two different intrusion detection …
Service (DDoS) Attacks. The proposed system applies two different intrusion detection …
Detection of DDoS vulnerability in cloud computing using the perplexed bayes classifier
N Mishra, RK Singh, SK Yadav - Computational Intelligence …, 2022 - Wiley Online Library
Cloud computing security has been a critical issue with its increase in demand. One of the
most challenging problems in cloud computing is detecting distributed denial‐of‐service …
most challenging problems in cloud computing is detecting distributed denial‐of‐service …
Implementation of BFS-NB hybrid model in intrusion detection system
Recently due to rise in technology and connectivity among various components of a system,
various new cybersecurity issues are emerging. To handle this rapid growth in computer …
various new cybersecurity issues are emerging. To handle this rapid growth in computer …