NDLI: Evaluating information assurance performance and the impact of data characteristics

Content Provider	IEEE Xplore Digital Library
Author	DeVale, J.P. Tan, K.M.C.
Copyright Year	2010
Description	Author affiliation: Carnegie Mellon University, Pittsburgh, PA (Tan, K.M.C.) \|\| Milton S. Eisenhower Research Center, Johns Hopkins University Applied Physics Lab, Laurel, MD (DeVale, J.P.)
Abstract	Research and development of new information assurance techniques and technologies is ongoing and varied. Each new proposal and technique arrives with great promise and anticipated success as research teams struggle to develop new and innovative responses to emerging threats. Unfortunately, these techniques frequently fall short of expectation when deployed due to difficulties with false alarms, trouble operating in a non-idealized or new domain, or flexibility limiting assumptions which are only valid with specific input sets. We believe these failures are due to fundamental problems with the experimental method for evaluating the effectiveness of new ideas and techniques. This work explores the effect of a poorly understood data synthesis process on the evaluation of IA devices. The point of an evaluation is to independently determine what a detector can and cannot detect, i.e. the metric of detection. This can only be done when the data contains carefully controlled ground truth. We broadly define the term “similarity class” to facilitate discussion about the different ways data (and more specifically test data) can be similar, and use these ideas to illustrate the pre-requisites for correct evaluation of anomaly detectors. We focus on how anomaly detectors function and should be evaluated in 2 specific domains with disparate system architectures and data: a sensor and data transport network for air frame tracking and display, and a deep space mission spacecraft command link. Finally, we present empirical evidence illustrating the effectiveness of our approach in these domains, and introduce the entropy of a time series sensor as a critical measure of data similarity for test data in these domains.
Starting Page	15
Ending Page	21
File Size	3150815
Page Count	7
File Format	PDF
ISBN	9781424460472
e-ISBN	9781424460489
DOI	10.1109/THS.2010.5655105
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Space vehicles data generation experimental method Detectors Markov processes Radar tracking Generators Entropy information assurance similarity classes
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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