1 / 6

cr( H )

Applied Mathematics Operations Research Simulation Science Computer Science. cr( H ). p. H. Who Are We?. Small, established scientific consulting firm ~150 employees Founded in 1982 Headquarters in Reston, Virginia 20 miles from Washington, D.C. Employing many mathematicians

olin
Download Presentation

cr( H )

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Applied Mathematics Operations Research Simulation Science Computer Science cr(H) p H

  2. Who Are We? • Small, established scientific consulting firm • ~150 employees • Founded in 1982 • Headquarters in Reston, Virginia • 20 miles from Washington, D.C. • Employing many mathematicians • Ph.D. and undergraduate • To solve challenging, technical problems • For clients in the Defense and Intelligence communities Metron Proprietary – 2

  3. What kind of undergraduate background is useful for working at Metron? • Computer skills • Java or C++ • Writing skills • Mathematics • Linear algebra • Probability and statistics • Any course that contributes to mathematical maturity

  4. Exposing Terrorist Networks Likelihood Ratio: optimal statistic for deciding whether a graph J arose from signal + noise process or noise only P(J |+) LH (J) = Noise Process P(J |) Signal + NoiseProcess Use ideas from classical detection theoryto determine presence of terroristcells in a network

  5. Example of Theorem Let H be • Kevin Bacon game: connect “actors” in same “movie” r(H) = 7 = rank of H • Yields realistic network model (high clustering coefficient, etc.) v´(H) = 8 = number of non-isolated vertices of H c(H) = 2 = number of cut vertices of H b1= 3 b2= 2 … … Break H into blocks at cut vertices Stirling numbers count partitions of bi blocks into s “movies” m “movies” … … Theorem [Lo, Ferry]: For m, n→ ∞ with constantm, the expected number of subgraphs of B*(n,m,m)isomorphic to His given by n “actors” independent links, average ofmper actor Unipartite Projection: who’s acted with whom Ratio of expected to possible number of H’s is instance ofB* • H represents a threat activity obscured by noise model B * • Formula used to detect whether H arises by chance or by design Network Detection: A Sample Theorem Random Collaboration Model: B*(n,m,m)

  6. Pattern Analysis and Link Discovery Tool for Networks (PALADIN) Components Group Detector Entity-Link Extractor Network Anomaly Detector • Customize extraction of entities and links, with attributes, from data • Statistical analyses of numerous social network metrics to discover entities and groups with anomalous properties • Hierarchical clustering algorithms to detect groups of interconnected entities Network Visualization and Exploration Tool Network Pattern Matcher • Subgraph matching to discover threat signatures • Connect related signatures to detect organized threat networks and activities • Drill-down into and compare discovered networks • Functions and features to control display layout and information fidelity

More Related