Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Utilizing Graphics Processing Units For Network Anomaly Detection, Jonathan D. Hersack
Utilizing Graphics Processing Units For Network Anomaly Detection, Jonathan D. Hersack
Theses and Dissertations
This research explores the benefits of using commonly-available graphics processing units (GPUs) to perform classification of network traffic using supervised machine learning algorithms. Two full factorial experiments are conducted using a NVIDIA GeForce GTX 280 graphics card. The goal of the first experiment is to create a baseline for the relative performance of the CPU and GPU implementations of artificial neural network (ANN) and support vector machine (SVM) detection methods under varying loads. The goal of the second experiment is to determine the optimal ensemble configuration for classifying processed packet payloads using the GPU anomaly detector. The GPU ANN achieves …
The White-Hat Bot: A Novel Botnet Defense Strategy, Tyrone C. Gubler
The White-Hat Bot: A Novel Botnet Defense Strategy, Tyrone C. Gubler
Theses and Dissertations
Botnets are a threat to computer systems and users around the world. Botmasters can range from annoying spam email propagators to nefarious criminals. These criminals attempt to take down networks or web servers through distributed denial-of-service attacks, to steal corporate secrets, or to launder money from individuals or corporations. As the number and severity of successful botnet attacks rise, computer security experts need to develop better early-detection and removal techniques to protect computer networks and individual computer users from these very real threats. I will define botnets and describe some of their common purposes and current uses. Next, I will …
Scalable Wavelet-Based Active Network Stepping Stone Detection, Joseph I. Gilbert
Scalable Wavelet-Based Active Network Stepping Stone Detection, Joseph I. Gilbert
Theses and Dissertations
Network intrusions leverage vulnerable hosts as stepping stones to penetrate deeper into a network and mask malicious actions from detection. This research focuses on a novel active watermark technique using Discrete Wavelet Transformations to mark and detect interactive network sessions. This technique is scalable, nearly invisible and resilient to multi-flow attacks. The watermark is simulated using extracted timestamps from the CAIDA 2009 dataset and replicated in a live environment. The simulation results demonstrate that the technique accurately detects the presence of a watermark at a 5% False Positive and False Negative rate for both the extracted timestamps as well as …
Mfire-2: A Multi Agent System For Flow-Based Intrusion Detection Using Stochastic Search, Timothy J. Wilson
Mfire-2: A Multi Agent System For Flow-Based Intrusion Detection Using Stochastic Search, Timothy J. Wilson
Theses and Dissertations
Detecting attacks targeted against military and commercial computer networks is a crucial element in the domain of cyberwarfare. The traditional method of signature-based intrusion detection is a primary mechanism to alert administrators to malicious activity. However, signature-based methods are not capable of detecting new or novel attacks. This research continues the development of a novel simulated, multiagent, flow-based intrusion detection system called MFIRE. Agents in the network are trained to recognize common attacks, and they share data with other agents to improve the overall effectiveness of the system. A Support Vector Machine (SVM) is the primary classifier with which agents …