Visible to the public Biblio

Filters: Author is Layman, Lucas  [Clear All Filters]
2014-09-17
Layman, Lucas, Diffo, Sylvain David, Zazworka, Nico.  2014.  Human Factors in Webserver Log File Analysis: A Controlled Experiment on Investigating Malicious Activity. Proceedings of the 2014 Symposium and Bootcamp on the Science of Security. :9:1–9:11.

While automated methods are the first line of defense for detecting attacks on webservers, a human agent is required to understand the attacker's intent and the attack process. The goal of this research is to understand the value of various log fields and the cognitive processes by which log information is grouped, searched, and correlated. Such knowledge will enable the development of human-focused log file investigation technologies. We performed controlled experiments with 65 subjects (IT professionals and novices) who investigated excerpts from six webserver log files. Quantitative and qualitative data were gathered to: 1) analyze subject accuracy in identifying malicious activity; 2) identify the most useful pieces of log file information; and 3) understand the techniques and strategies used by subjects to process the information. Statistically significant effects were observed in the accuracy of identifying attacks and time taken depending on the type of attack. Systematic differences were also observed in the log fields used by high-performing and low-performing groups. The findings include: 1) new insights into how specific log data fields are used to effectively assess potentially malicious activity; 2) obfuscating factors in log data from a human cognitive perspective; and 3) practical implications for tools to support log file investigations.

Layman, Lucas, Zazworka, Nico.  2014.  InViz: Instant Visualization of Security Attacks. Proceedings of the 2014 Symposium and Bootcamp on the Science of Security. :15:1–15:2.

The InViz tool is a functional prototype that provides graphical visualizations of log file events to support real-time attack investigation. Through visualization, both experts and novices in cybersecurity can analyze patterns of application behavior and investigate potential cybersecurity attacks. The goal of this research is to identify and evaluate the cybersecurity information to visualize that reduces the amount of time required to perform cyber forensics.