intrusion detection in wireless sensor networks group meeting spring 2005 presented by edith ngai
Post on 21-Dec-2015
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TRANSCRIPT
Outline
• Wireless sensor networks (WSN)• Security in WSN• Background on intrusion detection• Intrusion detection in WSN
• Types of attacks• Intrusion detection components• Required technologies• Future directions
• Conclusion
Technology trend
• Small integrated devices• Smaller, cheaper, more powerful
• PDAs, mobile phones
• Many opportunities, and research areas• Power management
• Distributed algorithms
Wireless sensor networks
• Wireless sensor node• power supply
• sensors
• embedded processor
• wireless link
• Many, cheap sensors• wireless easy to install
• intelligent collaboration
• low-power long lifetime
Possible applications
• Military• battlefield surveillance, biological attack detection,
targeting
• Ecological• fire detection, flood detection, agricultural uses
• Health related• human physiological data monitoring
• Miscellaneous• car theft detection, inventory control, home
applications
Required technologies
• Efficient data routing• ad-hoc network• one or more ‘datasinks’
• In-network data processing• large amounts of raw data• limited power and bandwidth
• Node localization
Security in WSN
• Main security threats in WSN are:• Radio links are insecure – eavesdropping /
injecting faulty information is possible
• Sensor nodes are not temper resistant – if it is compromised the attacker obtains all security information
• Protecting confidentiality, integrity, and availability of the communications and computations
Why security is different?
•Sensor Node Constraint
•Battery
•CPU power
•Memory
•Networking Constraints and Features
•Wireless
•Ad hoc
•Unattended
Network defense
Protect - Encryption - Firewalls - Authentication - Biometrics
Detect - Intrusions - Attacks - Misuse of Resources - Data Correlation - Data Visualization - Malicious Behaviors - Network Status/
Topology
React - Response - Terminate Connections - Block IP Addresses - Containment - Recovery - Reconstitute
What is intrusion detection?
• Intrusion detection is the process of discovering, analyzing, and reporting unauthorized or damaging network or computer activities
• Intrusion detection discovers violations of confidentiality, integrity, and availability of information and resources
• Intrusion detection demands:• As much information as the computing
resources can possibly collect and store
• Experienced personnel who can interpret network traffic and computer processes
• Constant improvement of technologies and processes to match pace of Internet innovation
What is intrusion detection?
How useful is intrusion detection?
• Provide digital forensic data to support post-compromise law enforcement actions
• Identify host and network misconfigurations• Improve management and customer
understanding of the Internet's inherent hostility
• Learn how hosts and networks operate at the operating system and protocol levels
Intrusion detection models
• All computer activity and network traffic falls in one of three categories:
• Normal
• Abnormal but not malicious
• Malicious
• Properly classifying these events are the single most difficult problem -- even more difficult than evidence collection
Intrusion detection models
• Two primary intrusion detection models• Network-based intrusion detection monitors
network traffic for signs of misuse
• Host-based intrusion detection monitors computer processes for signs of misuse
• So-called "hybrid" systems may do both• A hybrid IDS on a host may examine network
traffic to or from the host, as well as processes on that host
IDS paradigms
• Anomaly Detection - the AI approach
• Misuse Detection - simple and easy
• Burglar Alarms - policy based detection
• Honey Pots - lure the hackers in
• Hybrids - a bit of this and that
Anomaly detection
• Goals:• Analyze the network or system and infer what
is normal
• Apply statistical or heuristic measures to subsequent events and determine if they match the model/statistic of “normal”
• If events are outside of a probability window of “normal” then generate an alert
Misuse detection
• Goals:• Know what constitutes an attack
• Detect it
• A database of known attack signatures should be maintained
Network model
•BSj: base station at location (Xj, Yj)
•Si: sensor node at location (xi, yi)
•R: transmission range of the base station
•r: transmission range of the sensor node
•k-coverage: a node covers by k BSs
Definitions
• Coverage of a base station
• Number of coverage from base stations
• p sends data to q successfully (in 1-hop)
• p sends data to q successfully via k hops
• p fails in sending data from p to q
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):|},...,1{,(
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1111
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qpppppGppqp
iiji
ski
si
ki
skk
s
qtopfromontransmissionfailureqp f ______
Types of intrusions
• Sinkhole SH(q), HelloFlood HF(q)• A region of nodes will forward packets
destined for a BS through an adversary
• Wormhole WH(q)• An adversary tunnels messages received in
one part of the network over a low latency link and replays them in a different part
mppBSpBSqp mrilis
ks |
mppBSpBSqqp mriliss
ks |21
Types of intrusions
• Missing Data MD(p)• Missing data from p to BSi
• Wrong Data WD(p)• Inconsistent data
• Interference • Sensor p cannot send packet to its
neighboring nodes
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mis
iw dBSpNdBSpd ))(()(
)(|: ii BSpdCpi
Architecture
History
Route Tracing
Data Fusion (local,global)
TopologyNeighboringMonitoring Data Collection
RoutingMissing Data?
Inconsistent Data?
Intrusion Type Identification
Yes
Yes
Intrusion Location
Intrusion Reaction
Suspicious Behavior?
Yes
Suspicious Routes?
Yes
Intrusion detection components
• Neighbor monitoring • Watchdog
• Data fusion• Local – neighboring nodes
• Global – overlapping areas
• Topology discovery
• Route tracing
• History
Intrusion classification
Components\Attack Types I II III IV V
Neighbor Monitoring
BS Dominating intermediate node
Dominating intermediate node
Selective forwarding
--- ---
Sensor --- --- Selective forwarding
--- Interference (jamming with neighbors)
Data Comparison
Global (may have missing or inconsistent data)
(may have missing or inconsistent data)
Missing data Inconsistent data (IVa – malicious sensor or intermediate nodes)
Missing data
Local (may have missing or inconsistent data)
(may have missing or inconsistent data)
Missing data Inconsistent data (IVb – sensor failure or being compromised)
Missing data
Routing (with topology info.)
BS a region of nodes forward packet through the same adversary
An adversary tunnels messages and replays them in a different part
--- --- ---
Attack Types: I - Sinkhole, Hello Flood II – Wormhole III – Missing DataIV – Wrong Data V - Interference
Required technologies
• Collection of the audit data• Localization• Data fusion• Routing
• Analysis on the audited data• Identify the intrusion characteristics• Detect the intrusions• Locate the intrusions
• Intrusion reaction
Future direction
• Study how to collect the audit data effectively
• Complete the intrusion detection architecture
• Investigate the methods to analyze the audit data for intrusion detection
• Explore how to locate and react to the intrusions
• Formulate and evaluate our intrusion detection solution
Conclusion
• We discussed the characteristics of WSN and its security issues
• We studied traditional intrusion detection technologies
• We introduced the problem of intrusion detection in WSN
• We proposed an intrusion detection architecture and analyzed various kinds of intrusions in WSN
• We showed our future direction