US2013318616A1PendingUtilityA1

Predicting attacks based on probabilistic game-theory

Assignee: CHRISTODORESCU MIHAIPriority: May 23, 2012Filed: Jun 4, 2012Published: Nov 28, 2013
Est. expiryMay 23, 2032(~5.8 yrs left)· nominal 20-yr term from priority
G06Q 10/06375H04L 63/1408G06F 21/00H04L 63/20G06F 21/552
57
PatentIndex Score
0
Cited by
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References
0
Claims

Abstract

Systems for determining cyber-attack target include a network monitor module configured to collect network event information from sensors in one or more network nodes; a processor configured to extract information regarding an attacker from the network event information, to form an attack scenario tree that encodes network topology and vulnerability information including a plurality of paths from known compromised nodes to a set of potential targets, to calculate a likelihood for each of the paths, to calculate a probability distribution for the set of potential targets to determine which potential targets are most likely pursued by the attacker, to calculate a probability distribution over a set of nodes and node vulnerability types already accessed by the attacker, and to determine a network graph edge to remove that minimizes a defender's expected uncertainty over the potential targets; and a network management module configured to remove the determined network graph edge.

Claims

exact text as granted — not AI-modified
1 . A system for determining cyber-attack target, comprising:
 a network monitor module configured to collect network event information from sensors in one or more network nodes;   a processor configured to extract information regarding an attacker from the network event information, to form an attack scenario tree that encodes network topology and vulnerability information including a plurality of paths from known compromised nodes to a set of potential targets, to calculate a likelihood for each of the plurality of paths, and to calculate a probability distribution for the set of potential targets to determine which potential targets are most likely pursued by the attacker.   
     
     
         2 . The system of  claim 1 , wherein the network event information comprises network traffic information. 
     
     
         3 . The system of  claim 1 , wherein the network event information comprises node system calls. 
     
     
         4 . The system of  claim 1 , wherein the network event information comprises activity logs. 
     
     
         5 . The system of  claim 1 , wherein the processor is configured to compute likelihood l for each of the plurality of paths π as 
       
         
           
             
               
                 
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       where p(o q     i   |π r     i   ) is a probability of making an observation o q     i    when a node π r     i    is attacked and  p (π j ) is the probability of the node π j  being attacked without triggering any observations. 
     
     
         6 . The system of  claim 1 , wherein processor is configured to compute the probability distribution for the set of potential targets using a Monte Carlo simulation. 
     
     
         7 . The system of  claim 1 , wherein the processor is configured to compute the probability distribution for the set of potential targets as 
       
         
           
             
               
                 
                   P 
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       where P]t|A] is a probability of an attacker pursuing a target node t given a set of occupied nodes A, and l(A) is a likelihood of the set of nodes A being occupied. 
     
     
         8 . A system for determining cyber-attack targets, comprising:
 a network monitor module configured to collect network event information from sensors in one or more network nodes;   a processor configured to extract information regarding an attacker from the network event information, to form an attack scenario tree that encodes network topology and vulnerability information including a plurality of paths from known compromised nodes to a set of potential targets, to calculate a probability distribution over a set of nodes and node vulnerability types already accessed by the attacker, and to determine a network graph edge to remove that minimizes a defender's expected uncertainty over the potential targets; and   a network management module configured to remove the determined network graph edge.   
     
     
         9 . The system of  claim 8 , wherein the network event information comprises network traffic information. 
     
     
         10 . The system of  claim 8 , wherein the network event information comprises node system calls. 
     
     
         11 . The system of  claim 8 , wherein the network event information comprises activity logs. 
     
     
         12 . The system of  claim 8 , wherein the processor is configured to determine the defender's expected uncertainty over the potential targets as a Shannon entropy. 
     
     
         13 . The system of  claim 8 , wherein the network management module is configured to remove the determined network graph edge by disconnecting a corresponding network communication link. 
     
     
         14 . The system of  claim 8 , wherein the network management module is configured to remove the determined network graph edge by adapting a corresponding network communication link to block the attacker's use of the determined network graph edge. 
     
     
         15 . A system for determining cyber-attack target, comprising:
 a network monitor module configured to collect network event information from sensors in one or more network nodes;   a processor configured to extract information regarding an attacker from the network event information, to form an attack scenario tree that encodes network topology and vulnerability information including a plurality of paths from known compromised nodes to a set of potential targets, to calculate a likelihood for each of the plurality of paths, to calculate a probability distribution for the set of potential targets to determine which potential targets are most likely pursued by the attacker, to calculate a probability distribution over a set of nodes and node vulnerability types already accessed by the attacker, and to determine a network graph edge to remove that minimizes a defender's expected uncertainty over the potential targets; and   a network management module configured to remove the determined network graph edge.   
     
     
         16 . The system of  claim 15 , wherein the network event information comprises network traffic information. 
     
     
         17 . The system of  claim 15 , wherein the network event information comprises node system calls. 
     
     
         18 . The system of  claim 15 , wherein the network event information comprises activity logs. 
     
     
         19 . The system of  claim 15 , wherein the network management module is configured to remove the determined network graph edge by disconnecting a corresponding network communication link. 
     
     
         20 . The system of  claim 15 , wherein the network management module is configured to remove the determined network graph edge by adapting a corresponding network communication link to block the attacker's use of the determined network graph edge.

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