The following navigation utilizes arrow, enter, escape, and space bar key commands. Left and right arrows move through main tier links and expand / close menus in sub tiers. Up and Down arrows will open main tier menus and toggle through sub tier links. Enter and space open menus and escape closes them as well. Tab will move on to the next part of the site rather than go through menu items.
Kyle Wiseman, Dr. Jason M. Pittman, Department of Computer Science, High Point University, 1 University Parkway, High Point, NC 27268
Computers connected to a network such as the internet are apt to be attacked. This is a consequence of having open and discoverable services. While some such services must be public as is the case with web or email, remote access is a necessary risk in the modern telecommuting gestalt. Of course, one way to prevent this scenario is by not exposing services in the first place. A computer without available services is not very useful though. Fortunately, such an extreme is not necessary due to port knocking. Port knocking is a technology which keeps services concealed until a client sends a specially crafted communication sequence or knock. The literature demonstrates a plethora of port knocking models and implementations. Furthermore, research shows all port knocking methodologies are susceptible to having the knock sequence eavesdropped or captured. The eavesdropping and capturing are made possible because knock sequences are static. That is, the same sequence is repeated. For that reason, this work proposes a novel port knocking algorithm which employs dynamic password generation to achieve stochastic port sequences. By using non-repeating, non-predictable port knocks, the chance of having the port knock sequence observed ought to be dramatically reduced. To that end, we provide preliminary experimental results as validation of algorithm effectiveness in comparison to existing data on detecting traditional port knocking.
Presenter: Kyle Wiseman
Institution: High Point University
Type: Poster
Subject: Computer Science
Status: Approved