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Securing Information through Trust Manage= ment in Wireless Networks
Mohit Virendra, Shambhu Upadhyaya
Computer Science and Engineering
The State University of New York at Buffalo
Buffalo, NY
Sep 24, 2004
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CEISARE @
2
Trust Schemes: Wireless Domain
  2. Central Authority
1.Independent Ad-hoc
Wireless Network Classification=
a. Independently Mutual information exchange between the nodes
 
b. Using a Trusted Central Authority
Trust-based Security Schemes=
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CEISARE @
3
Trust management through Domain Heads in ad-hoc <= span style=3D'position:absolute;top:83.75%;left:10.67%;width:79.02%;height:4.7= 5%'>networks
Trust based security scheme for ad-hoc networks: Physical and Logical Security Domains
Actu= al Condition Review-based Peer Monitoring Scheme<= /span>
Trust monitoring through Intent Graphs in wireless domai= n
Trust b= ased Admission Control scheme with a first yes policy = for WLANs
Overvie= w
Defining trust schemes for securing information in WLANs = and Ad-hoc networks   <= /span>
Problem Statement:
Contribut= ions:
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CEISARE @
4
CA Assisted Scenario: WLAN model
WLAN Architecture: Two servers on the Distribution System: (a) Admission Controller (AC), (b) Global Monitor (GM)
Trust = Based Admission Control
admission time trust establishment 
Optimistic Approach: Trust eve= ryone until misbehavior detected
Intent query scheme between = AC and the new node
 <= /span>A= dmission decision depends on  “= trust v= alue” and “intent” of the new node
Perfunctory check policy for node with unknown trust
“First Yes Policy”: Node proves and maintains trust value to be in session. Trust verified while node is in the system=
Looks Naïve!
But very effective in selective admission control
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CEISARE @
5
WLAN model: Trust Establishment
Nodes use symmetric key pairs for communication with AP, key durati= on dependent on trust value and “incrementing” trust also
Trust Levels: Used to (dis)allow a n= ode to perform certain operations 
During the operation, AC/GM monitors node using GHMS [10], checks against Intent Map and builds <= /span>its Trust History
Three Trust Levels: Low, = Medium and High
 <= /span><= b>Intent Map (Graph) Generation: models node’s int= ended behavior
FSM based on resources required &a= mp; steps to be followed
Benign transactions increase node’s trust val= ue
Relationship between transactions completed  and trust value depicted by graph on next slide
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Operations
3D"Text
Trust Value
Misbehavior Threshold
High
Medium
Low/ Unknown
(Benign)
(Malicious)
(Intrusion Flagged)
Trust Value vs. Operations
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CEISARE @
7
Intent Graphs and ACR generation
Tolerance in Intent Graphs
Tolerance Level and Misbehavior Threshold
Dealing with excess data rates: calculat= ing threshold  as an incremental= percentage or probability as a function of data rates = [11]
Flagging an intrusion =3D=3D premature expiration of the session key between node and AP
Each deviation =3D> closer to threshold ~ severity of misbehavior
Trust Values help in Leader Selection
Peer Trust Monitoring: Actual Condition Review  (= ACR) report generation schem= e
FORWARD MONITORING: APs generate ACRs about nodes
REVERSE MONITORING: Nodes generate ACRs about APs
S= ELF MONITORING: Nodes forced to submit their own progress report
<= b>Result: A self correcting trust monitoring system <= /span>
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WLAN Logical Implementation
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