TY - GEN
T1 - Enavis
T2 - 22nd Large Installation System Administration Conference, LISA 2008
AU - Liao, Qi
AU - Blaich, Andrew
AU - Striegel, Aaron
AU - Thain, Douglas
N1 - Funding Information:
This work was supported in part by the National Science Foundation (CNS-03-47392, CNS-05-49087) as well as a Sun Academic Excellence Grant (AEG) (EDUD-7824-080234-US).
Funding Information:
Dr. Aaron Striegel is currently an assistant professor in the Department of Computer Science & Engineering at the University of Notre Dame. He received his Ph.D. in December 2002 in Computer Engineering at Iowa State University under the direction of Dr. G. Manimaran. His research interests include networking (bandwidth conservation, QoS), computer security, grid computing, and real-time systems. During his tenure as a student at Iowa State, he worked for various companies in research and development that included Sun Microsystems, Architecture Technology Corporation, and Emerson Process. He has received research and equipment funding from NSF, DARPA, Sun Microsystems, Hewlett Packard, Architecture Technology Corporation, and Intel. Dr. Striegel was the recipient of an NSF CAREER award in 2004. Dr. Striegel can be reached at striegel@nd.edu .
Publisher Copyright:
© LISA 2008.All right reserved.
PY - 2008
Y1 - 2008
N2 - With the prevalence of multi-user environments, it has become an increasingly challenging task to precisely identify who is doing what on an enterprise network. Current management systems that rely on inferring user identity and application usage via log files from routers and switches are not capable of accurately reporting and managing a large-scale network due to the coarseness of the collected data. We propose a system that utilizes finer-grained data in the form of local context, i.e., the precise user and application associated with a network connection. Through the use of dynamic correlation and graph modeling, we developed a visualization tool called ENAVis (Enterprise Network Activities Visualization). ENAVis aids a real-world administrator in allowing them to more efficiently manage and gain insight about the connectivity between hosts, users, and applications that is otherwise obfuscated, lost or not collected in systems currently deployed in an enterprise setting.
AB - With the prevalence of multi-user environments, it has become an increasingly challenging task to precisely identify who is doing what on an enterprise network. Current management systems that rely on inferring user identity and application usage via log files from routers and switches are not capable of accurately reporting and managing a large-scale network due to the coarseness of the collected data. We propose a system that utilizes finer-grained data in the form of local context, i.e., the precise user and application associated with a network connection. Through the use of dynamic correlation and graph modeling, we developed a visualization tool called ENAVis (Enterprise Network Activities Visualization). ENAVis aids a real-world administrator in allowing them to more efficiently manage and gain insight about the connectivity between hosts, users, and applications that is otherwise obfuscated, lost or not collected in systems currently deployed in an enterprise setting.
UR - http://www.scopus.com/inward/record.url?scp=85047359787&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85047359787
T3 - Proceedings of the 22nd Large Installation System Administration Conference, LISA 2008
SP - 59
EP - 74
BT - Proceedings of the 22nd Large Installation System Administration Conference, LISA 2008
PB - USENIX Association
Y2 - 9 November 2008 through 14 November 2008
ER -