hybrid authentication
Post on 23-Jun-2015
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KIANOOSH MOKHTARIANMOHAMMAD-SADEGH FARAJI
Hybrid Authentication
Introduction
Authentication Explicit Implicit
Previous works Biometric authentication Regarding individual elements Mostly using a modeling method Try to authenticate users by characteristics
System Architecture
Learning Algorithm
User model Authentication module
Recent user behavior
Output
User credential
Intuition for our work
A combination of characteristics is uniqueCombination of characteristics is not
forgeableShort-term behavior sometimes differs
dramatically from long-term one.Short term behavior modeling should store
more detailsLeveraging multiple user behavior modeling Short term user behavior ought to be
considered periodically not event driven
Algorithm
I: recent user behaviorIf I is similar short term user behavior and does not violate long term behavior
update bothIf I is similar to long term behavior and does not violate short term user behavior
update bothElse
ask for credential
Modeling
All features are independentEach feature is considered as a random
variableScore is calculated independently for each
featureAn ensemble classifier will decide based on
these scoreGaussian Mixture Model for GPSBayesian belief network for long term
modeling K-nearest neighbor for short term modeling
7
Short term modelingStore all input data in the training
set
For each pattern in the test set
Search for the K nearest patterns to the input pattern using a Euclidean distance measure
For classification, compute the confidence for each class as Ci /K,
(where Ci is the number of patterns among the K nearest patterns belonging to class i.)
The classification for the input pattern is the class with the highest confidence.
8
Ensemble Classifier
OriginalTraining data
....D1D2 Dt-1 Dt
D
Step 1:Create Multiple
Data Sets
C1 C2 Ct -1 Ct
Step 2:Build Multiple
Classifiers
C*Step 3:
CombineClassifiers
Evaluation
Training period Store features over a week and detemine user model Call pattern over time
Authentication phase Calculate authentication score over last few hours and
figure delta= f- fp
If delta is acceptable, update probabilty density function from last few hours
Else reject the request
User modeling experiment
User 1
Satureday Sunday Monday Tuesday Wendneseday Thurseday Friday0
1
2
3
4
5
6
7
8:00 AM9:00 AM10:00 AM11:00 AM12:00 PM
User modeling experiment
User 2
Satu
reda
y
Sund
ay
Mon
day
Tues
day
Wen
dsed
ay
Thur
seda
y
Friday
0
1
2
3
4
5
6
7
8
8:00 AM9:00 AM10:00 AM11:00 AM12:00 PM
Authentication score - Calls
8:00 AM 9:00 AM 10:00 AM
11:00 AM
12:00 PM
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Score
ScoreUser 1
User 2
Authentication score - GPS
8:00 AM 9:00 AM 10:00 AM 5:00 PM0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Score
ScoreUser 1
User 2
User behavior modeling
0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 100
0.2
0.4
0.6
0.8
1
1.2
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