CMU SCS Big (graph) data analytics Christos Faloutsos CMU.

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Presentation transcript:

CMU SCS Big (graph) data analytics Christos Faloutsos CMU

CMU SCS CMU visit '14C. Faloutsos2 Outline Problem definition / Motivation Anomaly detection Time series analysis Conclusions

CMU SCS CMU visit '14C. Faloutsos3 Motivation Data mining: ~ find patterns (rules, outliers) How do real graphs look like? Anomalies? Time series / Monitoring PA, NY, …

CMU SCS CMU visit '14C. Faloutsos4 Graphs - why should we care?

CMU SCS C. Faloutsos5 Graphs - why should we care? Internet Map [lumeta.com] Food Web [Martinez ’91] ~1B users $10-$100B revenue CMU visit '14

CMU SCS CMU visit '14C. Faloutsos6 Outline Problem definition / Motivation Anomaly/fraud detection –Financial fraud –Ebay fraud Time Series Analysis Conclusions

CMU SCS Network Effect Tools: SNARE 7 Some accounts are sort-of-suspicious – how to combine weak signals? Before CMU visit '14C. Faloutsos

CMU SCS Network Effect Tools: SNARE 8 A: Belief Propagation. Before CMU visit '14C. Faloutsos

CMU SCS Network Effect Tools: SNARE 9 A: Belief Propagation. After Before CMU visit '14C. Faloutsos Mary McGlohon, Stephen Bay, Markus G. Anderle, David M. Steier, Christos Faloutsos: SNARE: a link analytic system for graph labeling and risk detection. KDD 2009:

CMU SCS Network Effect Tools: SNARE 10 Produces improvement over simply using flags –Up to 6.5 lift –Improvement especially for low false positive rate False positive rate True positive rate Results for accounts data (ROC Curve) Ideal SNARE Baseline (flags only) CMU visit '14C. Faloutsos

CMU SCS Network Effect Tools: SNARE 11 Accurate- Produces large improvement over simply using flags Flexible- Can be applied to other domains Scalable- One iteration BP runs in linear time (# edges) Robust- Works on large range of parameters CMU visit '14C. Faloutsos

CMU SCS CMU visit '14C. Faloutsos12 Outline Problem definition / Motivation Anomaly/fraud detection –Financial fraud –Ebay fraud Time series analysis Conclusions

CMU SCS C. Faloutsos E-bay Fraud detection Detects ‘non-delivery’ fraud: seller takes $$ and disappears CMU visit '14 Shashank Pandit, Duen Horng Chau, Samuel Wang, and Christos Faloutsos. NetProbe: A Fast and Scalable System for Fraud Detection in Online Auction Networks WWW 07.

CMU SCS C. Faloutsos E-bay Fraud detection - NetProbe CMU visit '14

CMU SCS App-store fraud Opinion Fraud Detection in Online Reviews using Network Effects Leman Akoglu, Rishi Chandy, CF ICWSM’13 CMU visit '14C. Faloutsos15

CMU SCS Problem Given –user-product review network –review sign (+/-) Classify –objects into type-specific classes: users: `honest’ / `fraudster’ products: `good’ / `bad’ reviews: `genuine’ / `fake’ No side data! (e.g., timestamp, review text) CMU visit '14C. Faloutsos16

CMU SCS Formulation: BP UserProduct honestbad honestgood CMU visit '14C. Faloutsos17 – + Before After

CMU SCS Top scorers CMU visit '14C. Faloutsos18 + positive (4-5) rating o negative (1-2) rating Users Products

CMU SCS Top scorers CMU visit '14C. Faloutsos19 + positive (4-5) rating o negative (1-2) rating Users Products

CMU SCS ‘Fraud-bot’ member reviews CMU visit '14C. Faloutsos20 Same developer!Duplicated text! Same day activity!

CMU SCS CMU visit '14C. Faloutsos21 Outline Problem definition / Motivation Anomaly/fraud detection Time series, monitoring / forecasting Conclusions

CMU SCS ‘Tycho’ – epidemics analysis CMU visit '1422C. Faloutsos Yasuko Matsubara 50 states x 46 diseases

CMU SCS ‘Tycho’ – epidemics analysis CMU visit '1423C. Faloutsos Prof. Yasuko Matsubara

CMU SCS ‘Tycho’ – epidemics analysis CMU visit '1424C. Faloutsos Prof. Yasuko Matsubara Flu? Measles? August? No periodicity?

CMU SCS ‘Tycho’ – epidemics analysis CMU visit '1425C. Faloutsos Prof. Yasuko Matsubara Flu? Measles? August? No periodicity?

CMU SCS ‘Tycho’ – epidemics analysis CMU visit '1426C. Faloutsos Prof. Yasuko Matsubara Flu? Measles? August? No periodicity?

CMU SCS ‘Tycho’ – epidemics analysis CMU visit '1427C. Faloutsos Prof. Yasuko Matsubara Flu? Measles? August? No periodicity?

CMU SCS ‘Tycho’ – epidemics analysis CMU visit '1428C. Faloutsos Prof. Yasuko Matsubara Flu? Measles? August? No periodicity?

CMU SCS ‘Tycho’ – epidemics analysis CMU visit '1429C. Faloutsos Prof. Yasuko Matsubara from U. Pitt (epidemiology dept.) Yasuko Matsubara, Yasushi Sakurai, Willem van Panhuis, and Christos Faloutsos, FUNNEL: Automatic Mining of Spatially Coevolving Epidemics, KDD 2014, New York City, NY, USA, Aug , 2014.

CMU SCS Open research questions Patterns/anomalies for time-evolving graphs (Call graph, 3M people x 6mo) Spot fraudsters in soc-net (eg., Twitter ‘$10 -> 1000 followers’) CMU visit '14C. Faloutsos30

CMU SCS CMU visit '14C. Faloutsos31 Contact info GHC 8019 Ph#: x8.1457