A survey of malware analysis using community detection algorithms
In recent years, we have witnessed an overwhelming and fast proliferation of different types
of malware targeting organizations and individuals, which considerably increased the time …
of malware targeting organizations and individuals, which considerably increased the time …
Generating network intrusion detection dataset based on real and encrypted synthetic attack traffic
A Ferriyan, AH Thamrin, K Takeda, J Murai - applied sciences, 2021 - mdpi.com
The lack of publicly available up-to-date datasets contributes to the difficulty in evaluating
intrusion detection systems. This paper introduces HIKARI-2021, a dataset that contains …
intrusion detection systems. This paper introduces HIKARI-2021, a dataset that contains …
Botnet detection based on anomaly and community detection
J Wang, IC Paschalidis - IEEE Transactions on Control of …, 2016 - ieeexplore.ieee.org
We introduce a novel two-stage approach for the important cybersecurity problem of
detecting the presence of a botnet and identifying the compromised nodes (the bots), ideally …
detecting the presence of a botnet and identifying the compromised nodes (the bots), ideally …
Flow whitelisting in SCADA networks
Supervisory control and data acquisition (SCADA) networks are commonly deployed in
large industrial facilities. Modern SCADA networks are becoming more vulnerable to cyber …
large industrial facilities. Modern SCADA networks are becoming more vulnerable to cyber …
On generating network traffic datasets with synthetic attacks for intrusion detection
Most research in the field of network intrusion detection heavily relies on datasets. Datasets
in this field, however, are scarce and difficult to reproduce. To compare, evaluate, and test …
in this field, however, are scarce and difficult to reproduce. To compare, evaluate, and test …
Investigating generalized performance of data-constrained supervised machine learning models on novel, related samples in intrusion detection
Recently proposed methods in intrusion detection are iterating on machine learning
methods as a potential solution. These novel methods are validated on one or more …
methods as a potential solution. These novel methods are validated on one or more …
Malware traffic detection using tamper resistant features
This paper presents a framework for evaluating the transport layer feature space of malware
heartbeat traffic. We utilize these features in a prototype detection system to distinguish …
heartbeat traffic. We utilize these features in a prototype detection system to distinguish …
Difficulties in modeling SCADA traffic: a comparative analysis
Modern critical infrastructures, such as water distribution and power generation, are large
facilities that are distributed over large geographical areas. Supervisory Control and Data …
facilities that are distributed over large geographical areas. Supervisory Control and Data …
Internet traffic volumes are not Gaussian—They are log-normal: An 18-year longitudinal study with implications for modelling and prediction
Getting good statistical models of traffic on network links is a well-known, often-studied
problem. A lot of attention has been given to correlation patterns and flow duration. The …
problem. A lot of attention has been given to correlation patterns and flow duration. The …
Anomaly detection in SCADA systems: a network based approach
RRR Barbosa - 2014 - research.utwente.nl
Abstract Supervisory Control and Data Acquisition (SCADA) networks are commonly
deployed to aid the operation of large industrial facilities, such as water treatment facilities …
deployed to aid the operation of large industrial facilities, such as water treatment facilities …