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Transcript
Secure communication in cellular
and ad hoc environments
Bharat Bhargava
[email protected]
Department of Computer Sciences,
Purdue University
This is supported by Motorola Communication
Research Lab & National Science Foundation
Team at Motorola:
Jeff Bonta
George Calcev
Benetido Fouseca
Trefor Delve
Team at Purdue University:
X. Wu
Research scientist (receives his
PhD from UC-Davis)
Y. Lu
PhD student
G. Ding
PhD student
W. Wang
PhD student
Problem statement
How to provide secure, continuous,
and efficient connectivity for a
mobile unit in a structured (cellular
based) or unstructured (ad hoc)
network environment?
3
Challenges
• Dynamic topology
– Movement, node failure, etc.
• Heterogeneous and decentralized control
• Limited resources
– Bandwidth, processing ability, energy
• Unfriendly environment
– Selfish nodes, malicious attackers
4
Research contributions
• Combining advantages of cellular systems and ad
hoc networks to enable a more secure network
structure and better performance
• Designing routing protocols for ad hoc networks
that adapt to both network topology and traffic
congestion
• Designing intruder identification protocols in ad
hoc networks
• Conducting experimental studies in heterogeneous
wireless environments and evaluating our protocols
5
Research directions
• Cellular-aided Mobile Ad Hoc Network
(CAMA)
• Adaptive and Heterogeneous Mobile
Wireless Networks
• Intruder Identification in Ad Hoc Networks
6
Cellular-aided Mobile Ad Hoc
Network (CAMA)
CAMA: Problem Statement
How to realize commercial peer-to-peer
applications over mobile wireless ad hoc
networks?
Papers:
“Integrating Heterogeneous Wireless Technologies:
Cellular-Aided Mobile Wireless Ad hoc Networks
(CAMA)”, submitted to ACM Special Issues of the
Journal on Special Topics in Mobile Networking
and Applicaitons (MONET).
8
Challenges
• Authentication and accounting
– No fixed membership
• Security concern
– Open medium without any centralized control
• Real time services
– Dynamic topology and slow routing
information distribution
9
Current Environment
Cellular network provides:
• Wide coverage
• Multiple services with single cellular ID
• Small packet service in 3G network
• Wireless terminals with different protocols
10
CAMA Description
• Integration of cellular network and ad hoc
network
• CAMA agent works as centralized server
attached to the cellular network
• CAMA agent provides ad hoc nodes
information such as authentication, routing
support, keys through cellular channel
• Data transmission uses ad hoc channel
11
CAMA Environment
12
Major Ideas
• Use signals via cellular network for ad hoc
routing and security managements
• Centralized CAMA agent provides control
over distributed ad hoc network
13
CAMA vs. ad hoc network
CAMA has advantages over pure ad hoc
networks in:
• Simple network authentication and
accounting
• Routing server for more accurate routing
decisions
• Certification authority for key distribution
• Central security check point for intrusion
detection
14
CAMA vs. cellular/WLAN
CAMA has advantages over cellular/WLAN
integrated network in:
• No extra fixed infrastructure
– No access point needed
• No ad hoc channel radio coverage limit
– Multi-hop ad hoc link
• No transmission bottleneck
– Not all traffic need going through a single node
15
Impact
• Cellular service combined with low-cost,
high-data-rate wireless service
16
Research Questions
• Feasibilities in commercial applications
requires:
– Development of routing algorithm and
protocols for multimedia service
– Investigation of CAMA vulnerabilities
– Development of security protocols for key
distribution and intrusion detection
– Evaluation of gain in ad hoc network
– Evaluation of overhead in cellular network
17
Methodology of Research
• Building algorithms and protocols
• Developing bench marks and performance metrics
on multi-media service
• Conducting experimental studies
– Using ns-2
– Using common platform simulator from Motorola Inc.
• Comparing with ad hoc routing protocols
– Ad hoc on-demand distance vector routing (AODV)
– Destination source routing (DSR)
18
Research of Interest to Motorola
• Evaluating CAMA routing in realistic simulation
environment:
– Radio environment
• Adaptive data rate determined by signal-noise-ratio (SNR)
– Node mobility
• Exponentially distributed speed
– Node density
• 400 users/sq.km to 14800 users/sq.km
– Traffic pattern
• VoIP, TCP, Video
– Inaccurate position information
• Error of 5m to 100m
19
Research of Interest to Motorola (ctn.)
• Authentication
– By CAMA agent
– By mobile nodes
• Accounting
– Charging rate
– Award to intermediate nodes
20
Research of Interest to Motorola (ctn.)
• Key assignment
– Group key assignment
• For entire ad hoc network
• For nodes along an active route
– Session key assignment
• For peer-to-peer communication
21
Research of Interest to Motorola (ctn.)
• Intrusion detection
– Information collection
• Information for different intrusions
– Malicious judging rule
• Quick malicious node elimination vs. probability of
wrong judgment
• Detection cost vs. gain
22
Adaptive and Heterogeneous
Mobile Wireless Networks
Problem statement
How to provide continuous connectivity for
a mobile unit to a network in which every
node is moving?
Papers:
“Secure Wireless Network with Movable Base Stations”, being
revised for IEICE/IEEE Joint Special Issue on Assurance
Systems and Networks.
“Study of Distance Vector Routing Protocols for Mobile Ad
Hoc Networks”, in Proceedings of IEEE International
Conference on Pervasive Computing and Communications
(PerCom), 2003.
24
Challenges
• Dynamic topology
– Movement, node failure, energy problem, etc.
• Decentralized control
• Limited bandwidth
– Congestion is typically the norm rather than the
exception. [RFC 2501]
25
Research contributions
• Routing protocols for mobile ad hoc
networks that adapt to not only network
topology, but also traffic and congestion.
• Architecture, design of protocols, and
experimental evaluation in heterogeneous
wireless environments
26
Broad impacts
• Sensor networks
• Military networks
27
Two network environments
considered
• Mobile ad hoc networks
– No centralized control
• Large scale heterogeneous wireless
networks with control in base stations
– Wireless networks with movable base stations
(WNMBS)
28
Research questions in mobile ad
hoc networks
• Development of ad hoc routing protocols that adapt
to traffic load and network congestion.
– Identify the network parameters that impact the
performance of routing protocols.
– Determine the appropriateness of on-demand and
proactive approaches (given specific routing requirements
and network parameters).
– Identify features of ad hoc networks that can be used to
improve routing.
29
Related work (routing protocol)
• Destination-Sequenced Distance Vector (DSDV) [Perkins/Bhagwat,
SigComm’94] (Nokia)
• Ad-hoc On-demand Distance Vector (AODV) [Perkins/Royer/Das,
WMCSA’99, IETF draft 98-03] (Nokia, UCSB, SUNY-Stony Brook)
• Dynamic Source Routing (DSR) [Johnson/Maltz, Mobile Computing’96,
IETF draft 03] (Rice Univ., CMU)
• Zone Routing Protocol (ZRP) [Haas/Pearlman/Samar, ICUPC’97, IETF draft
99-02] (Cornell)
• Adaptive Distance Vector (ADV) [Boppana/Konduru, InfoCom’01] (UT-San
Antonio)
• Source-Tree Adaptive Routing (STAR) [Garcia-Luna-Aceves/Spohn,
MONET’01] (UCSC, Nokia)
• Associativity-Based Routing (ABR) [Toh, Wireless Personal
Communications Journal’97] (Cambridge Univ.)
• Ad-hoc On-demand Multipath Distance Vector (AOMDV) [Marina/Das,
ICNP’01] (Univ. of Cincinnati)
30
Related work (cont’d)
Protocol
Approach
Routing information
uses
Additional
information
DSDV
Proactive
Distance Vector
DSR
On-demand
Source routing
AODV
On-demand
Distance Vector
ZRP
Hybrid
Distance Vector
ADV
Hybrid
Distance Vector
STAR
Proactive
Link State
ABR
On-demand
Distance Vector
Associativity
AOMDV
On-demand
Distance Vector
Multipath
31
Related work (performance
comparison)
• Comparison of DSDV, TORA, AODV and DSR
[Broch/Maltz/Johnson/Hu/Jetcheva,
MobiCom’98] (CMU)
• Scenario-based performance analysis of DSDV,
AODV, and DSR
[Johansson/Larsson/Hedman/Mielczarek/Degerma
rk, MobiCom’99] (Ericsson)
• Performance comparison of AODV and DSR
[Perkins/Royer/Das/Marine, IEEE Personal
Communications’01]
32
Methodology of research
• Developing benchmarks and performance
metrics for routing protocols
• Conducting experimental studies
– Determine guidelines for design
– Evaluate protocols
• Building algorithms and protocols
33
Ongoing research
• Study of proactive and on-demand
approaches
• Congestion-aware distance vector routing
protocol
• Packet loss study
34
Research study
• Investigate the proactive and on-demand approaches
– Generalize the results obtained from protocols to the
proactive and on-demand approaches
– Introduce power consumption as a performance metric
– Inject heavy traffic load
– Identify the major causes for packet drop
– Comprehensively study in various network environments
• Propose a congestion-aware routing protocol
35
Simulation experiments
• DSDV and AODV are studied by varying
network environment parameters
– Node mobility (maximum moving speed)
– Traffic load (number of connections)
– Network size (number of mobile nodes)
• Performance metrics
–
–
–
–
Packet delivery ratio
Average end-to-end delay
Normalized protocol overhead
Normalized power consumption
36
Simulation setup for
experiments
Simulator
ns-2
Examined protocols
DSDV and AODV
Simulation duration
1000 seconds
Simulation area
Transmission range
1000 m x 1000 m
250 m
Movement model
Random waypoint
Maximum speed
4 – 24 m/s
Traffic type
Data payload
Packet rate
Node pause time
Bandwidth
CBR (UDP)
512 bytes/packet
4 packets/sec
10 seconds
1 Mb/s
37
Motivation for a new proactive protocol
• The proactive protocols provide better support
for:
– Applications requiring QoS
• Timely propagate network conditions
– Intrusion and anomaly detection
• Constantly exchange the network topology information
• The proactive approach exhibits better
scalability with respect to the number of
mobile nodes and traffic load.
38
Proposed protocol: Congestion Aware
Distance Vector (CADV)
• Problem with the proactive approach
– Congestion
• Objective:
– Dynamically detect congestion and route packets through lesscrowded paths
• Method:
– Characterize congestion and traffic load by using expected delay.
– Consider expected delay at the next hop as the secondary metric
to make routing decisions.
– Allow a one-hop longer route to be chosen.
– Use destination sequence number to avoid loop.
39
Design issues
• Use MAC layer callback to detect broken link
– Quick detection
– More triggered updates
– Whether re-queue a packet
• Allowing a one-hop longer route
– A one-hop shorter route may not replace the current one if it
introduces significantly more delay.
– To avoid short-lived loop, do not replace the current route with a
longer one if they have the same sequence number.
• Deal with fluctuation
– Use randomness in routing decisions to reduce fluctuation
40
CADV
• Components:
– Real time traffic monitor
– Traffic control
– Route maintenance module
• Route update:
– When broadcasts an update, every node advertises the expected
delay of sending a packet as:
D

E[ D ] 
i
n
L
• Route maintenance
– Apply a function f(E[D], distance) to evaluate the value of a route
41
Observations of CADV
• CADV outperforms AODV and DSDV in terms
of delivery ratio
• The end-to-end delay becomes longer because
longer routers may be chosen to forward packets
• The protocol overhead of CADV is doubled
compared with that of DSDV. It is still less than
that of AODV when the network is loaded
• CADV consumes less power per delivered packet
than DSDV and AODV do
42
Characteristics of wireless networks with
movable base stations
•
•
•
•
•
Large scale
Heterogeneity
Autonomous sub-nets
Base stations have more resources
Base stations take more responsibilities
43
Research questions
• How to organize the network?
– Minimize the effect of motion
– Minimize the involvement of mobile host
• How to build routing protocol?
– IP-compliant
– Cooperate with various intra-subnet routing protocols
• How to secure communications?
– Authenticate
– Maintain authentication when a host is roaming
44
Related work
• Integrating ad hoc and cellular
– Mobile-Assisted Connection-Admission (MACA)
[Wu/Mukherjee/Chan, GlobeCom’00] (UC-Davis)
– Integrated Cellular and Ad-hoc Relaying (iCAR)
[Wu/Qiao/De/Tonguz, JSAC’01] (SUNY-Buffalo)
– Multihop Cellular Networks (MCN) [Lin/Hsu, InfoCom’00] (Taiwan)
• Mobile base station
– Distributed, dynamic channel allocation [Nesargi/Prakash, IEEE
Transactions on Vehicular Technology’02] (UT-Dallas)
• Hierarchical structure
– Multimedia support for Mobile Wireless Networks (MMWN)
[Ramanathan/Steenstrup, MONET’98] (BBN Technologies)
– Clustering scheme for hierarchical control in multi-hop wireless
networks [Banerjee/Khuller, InfoCom’01] (UMD)
45
Methodology of research
• Building architecture, developing
algorithms and protocols
– Membership management
– Inter-subnet routing
– Intra- and inter-subnet authentication
• Evaluation through experiments
46
Research results
• Hierarchical mobile wireless network
(HMWN)
– Hierarchical membership management scheme
– Segmented membership-based group routing
protocol
– Protection of network infrastructure
– Secure roaming and fault-tolerant
authentication
47
Future research plan
• Develop congestion avoidance routing
protocol for ad hoc networks.
• Conduct experiments to study the effect of
implementing congestion avoidance at
different layers.
• Conduct a series of experiments to evaluate
HMWN.
48
Intruder Identification in Ad
Hoc Networks
Problem Statement
• Intruder identification in ad hoc networks is the
procedure of identifying the user or host that conducts
the inappropriate, incorrect, or anomalous activities
that threaten the connectivity or reliability of the
networks and the authenticity of the data traffic in the
networks.
Papers:
“On Security Study of Two Distance Vector Routing Protocols
for Mobile Ad Hoc Networks”, in Proceedings of IEEE
International Conference on Pervasive Computing and
Communications (PerCom), 2003.
“On Vulnerability and Protection of Ad Hoc On-demand
Distance Vector Protocol”, in Proceedings of 10th IEEE
International Conference on Telecommunication (ICT), 2003.
50
Research Motivation
• More than ten routing protocols for Ad Hoc
networks have been proposed (AODV, DSR,
DSDV, TORA, ZRP, etc.)
• Research focus has been on performance
comparison and optimizations such as multicast
and multiple path detection
• Research is needed on the security of Ad Hoc
networks.
• Applications: Battlefields, Disaster recovery.
51
Research Motivation
• Two types of attacks target Ad Hoc network
• External attacks:
• MAC layer jamming
• Traffic analysis
• Internal attacks:
• Compromised host sending false routing
information
• Fake authentication and authorization
• Traffic flooding
52
Research Motivation
• Protection of Ad Hoc networks
• Intrusion Prevention
• Traffic encryption
• Sending data through multiple paths
• Authentication and authorization
• Intrusion Detection
• Anomaly pattern examination
• Protocol analytical study
53
Research Motivation
• Deficiencies of intrusion prevention
• Increases the overhead during normal
operations of Ad Hoc networks
• Restriction on power consumption and
computation capability prevent the usage of
complex encryption algorithms
• Flat infrastructure increases the difficulty for
the key management and distribution
• Cannot guard against internal attacks
54
Research Motivation
• Why intrusion detection itself is not enough
• Detecting intrusion without removing the
malicious host leaves the protection in a passive
mode
• Identifying the source of the attack may
accelerate the detection of other attacks
55
Research Motivation
• Research problem: Intruder Identification
• Research challenges:
• How to locate the source of an attack ?
• How to safely combine the information from
multiple hosts and enable individual host to
make decision by itself ?
• How to achieve consistency among the
conclusions of a group of hosts ?
56
Related Work in wired Networks
• Secure routing / intrusion detection in wired
networks
• Routers have more bandwidth and CPU power
• Steady network topology enables the use of
static routing and default routers
• Large storage and history of operations enable
the system to collect enough information to
extract traffic patterns
• Easier to establish trust relation in the
hierarchical infrastructure
57
Related Work in wired networks
• Attack on RIP (Distance Vector)
• False distance vector
• Solution (Bellovin 89)
•
•
•
•
Static routing
Listen to specific IP address
Default router
Cannot apply in Ad Hoc networks
58
Related Work in wired networks
• Attack on OSPF (Link State)
• False connectivity
• Attack on Sequence Number
• Attack on lifetime
• Solution
• JiNAO:NCSU and MCNC
• Encryption and digital signature
59
Related Work in Ad Hoc Networks
• Lee at GaTech summarizes the difficulties in
building IDS in Ad Hoc networks and raises
questions:
• what is a good architecture and response system?
• what are the appropriated audit data sources?
• what is the good model to separate normal and
anomaly patterns?
• Haas at Cornell lists the 2 challenges in
securing Ad Hoc networks:
• secure routing
• key management service
60
Related Work in Ad Hoc Networks
• Agrawal at University of Cincinnati presents the
general security schemes for the secure routing in
Ad Hoc networks
• Nikander at Helsinki discusses the authentication,
authorization, and accounting in Ad Hoc networks
• Bhargavan at UIUC presents the method to
enhance security by dynamic virtual infrastructure
• Vaidya at UIUC presents the idea of securing Ad
Hoc networks with directional antennas
61
Related Work ongoing projects
• TIARA: Techniques for Intrusion Resistant Ad-Hoc
Routing Algorithm (DARPA)
• develop general design techniques
• focus on DoS attack
• sustain continued network operations
• Secure Communication for Ad Hoc Networking (NSF)
• Two main principles:
• redundancy in networking topology, route discovery and
maintenance
• distribution of trust, quorum for trust
62
Related Work ongoing projects
• On Robust and Secure Mobile Ad Hoc and Sensor
Network (NSF)
• local route repair
• performance analysis
• malicious traffic profile extraction
• distributed IDs
• proposed a scalable routing protocol
• Adaptive Intrusion Detection System (NSF)
• enable data mining approach
• proactive intrusion detection
• establish algorithms for auditing data
63
Problem Statement
• Intruder identification in ad hoc networks is
the procedure of identifying the user or host
that conducts the inappropriate, incorrect, or
anomalous activities that threaten the
connectivity or reliability of the networks
and the authenticity of the data traffic in the
networks.
64
Evaluation Criteria
• Accuracy
• False coverage: Number of normal hosts that are
incorrectly marked as suspected.
• False exclusion: Number of malicious hosts that are not
identified as such.
• Overhead
• Overhead measures the increases in control packets and
computation costs for identifying the attackers (e.g.
verifying signed packets, updating blacklists).
• Workload of identifying the malicious hosts in multiple
rounds
65
Evaluation Criteria
• Effectiveness
– Effectiveness: Increase in the performance of ad hoc
networks after the malicious hosts are identified and
isolated. Metrics include the increase of the packet
delivery ratio, the decrease of average delay, or the
decrease of normalized protocol overhead (control
packets/delivered packets).
• Robustness
– Robustness of the algorithm: Its ability to resist
different kinds of attacks.
66
Assumptions
A1. Every host can be uniquely identified and its ID cannot be changed
throughout the lifetime of the ad hoc network. The ID is used in the
identification procedure.
A2. A malicious host has total control on the time, the target and the
mechanism of an attack. The malicious hosts continue attacking the
network.
A3. Digital signature and verification keys of the hosts have been
distributed to every host. The key distribution in ad hoc networks is a
tough problem and deserves further research. Several solutions have
been proposed. We assume that the distribution procedure is finished,
so that all hosts can examine the genuineness of the signed packets.
A4. Every host has a local blacklist to record the hosts it suspects. The host
has total control on adding and deleting elements from its list. For the
clarity of the remainder of this paper, we call the real attacker as
“malicious host”, while the hosts in blacklists are called “suspected
hosts”.
67
Applying Reverse Labeling Restriction to
Protect AODV
• Introduction to AODV
• Attacks on AODV and their impacts
• Detecting False Destination Sequence
Attack
• Reverse Labeling Restriction Protocol
• Simulation results
68
Introduction to AODV
• Introduced in 97 by Perkins at NOKIA, Royer at
UCSB
• 12 versions of IETF draft in 3 years, 4 academic
implementations, 2 simulations
• Combines on-demand and distance vector
• Broadcast Route Query, Unicast Route Reply
• Quick adaptation to dynamic link condition and
scalability to large scale network
• Support Multicast
69
Security Considerations for AODV
“AODV does not specify any special security measures.
Route protocols, however, are prime targets for
impersonation attacks. If there is danger of such
attacks, AODV control messages must be protected
by use of authentication techniques, such as those
involving generation of unforgeable and
cryptographically strong message digests or digital
signatures.
”
- http://www.ietf.org/internet-drafts/draft-ietf-manet-aodv-11.txt
70
Message Types in AODV
• RREQ: route request
• RREP: route reply
• RERR: route error
71
Route Discovery in AODV
D
Establish path to
Unicast reply
the destination
Establish Broadcast
path to
the sourcerequest
S1
S3
Establish Broadcast
path to
the sourcerequest
Establish path to
Unicast reply
the destination
S2
S4
Establish path to
Unicast reply
the destination
Establish
Broadcast
path to
the source
request
S
72
Introduction to AODV (con’d)
• Security Features of AODV
• Combination of Broadcast and Unicast
• Route reply is sent out along a single path, prevent
the disclosure of routing information
• Fast Expiration of Reverse Route Entry
• Route entry created by un-replied route request will
expire in a short time
• Freshness of Routing Information
• Unique, monotonic destination sequence for every
host, could only be updated by destination/request
initiator
73
Attacks on AODV
• Malicious route request
– query non-existing host (RREQ will flood throughout the network)
• False route error
– route broken message sent back to source (route discovery is reinitiated)
• False distance vector
– reply “one hop to destination” to every request and select a large
enough sequence number
• False destination sequence
– select a large number (even beat the reply from real destination)
74
Impacts of Attacks on AODV
No Attacks
Packet Delivery
Ratio
96%
Protocol Overhead
38%
Silent Discard
91%
41%
False Distance
75%
38%
False Destination
Sequence
Vicious Flooding
53%
66%
91%
293%
75
False Destination Sequence Attack
RREP(D, 5)
RREQ(D,5)3)
S3 RREP(D,
RREQ(D, 3)
S
RREQ(D,20)
3)
RREP(D,
S1
D
RREQ(D, 3)
RREP(D, 20) RREP(D, 20)
S2
M
76
Attacks on AODV and Simulation Results
• Simulation of Attacks
• A module called “AODV Attack” added into
ns2
• Four attacks have been implemented
•
•
•
•
malicious route request
silently discard
false distance vector
false destination sequence
77
Attacks to AODV and Simulation Results
• Simulation parameters
Simulator
ns2
Simulation duration
1000 seconds
Simulation area
1000 * 1000 m
Number of mobile hosts
Transmission range
Maximum speed
Number of CBR connection
Packet rate
Simulated attacks
30
250 m (Lucent WaveLAN Card
Specification)
5 -- 20 m/s
25
2 pkt / sec
False distance vector and false
destination sequence
78
Attacks to AODV and Simulation Results
X-axis is max moving speed, which evaluates the mobility of host. Yaxis is delivery ratio. Two attacks: false distance vector and false
destination sequence, are considered. They lead to about 30% and 50%
of packets to be dropped.
79
Detecting false destination sequence attack
by destination host during route rediscovery
(1). S broadcasts a
request that carries the
old sequence + 1 = 21
D
S3
RREQ(D, 21)
S
(2) D receives the RREQ.
Local sequence is 5, but the
sequence in RREQ is 21. D
detects the false destination sequence attack.
S1
S2
M
S4
Propagation of RREQ
80
Reverse Labeling Restriction (RLR)
• Basic Ideas
• Every host maintains a blacklist to record suspicious hosts.
Suspicious hosts can be released from the blacklist or put
there permanently.
• The destination host will broadcast an INVALID packet
with its signature when it finds that the system is under
attack on sequence. The packet carries the host’s
identification, current sequence, new sequence, and its
own blacklist.
• Every host receiving this packet will examine its route
entry to the destination host. If the sequence number is
larger than the current sequence in INVALID packet, the
presence of an attack is noted. The next hop to the
destination will be added into this host’s blacklist.
81
Reverse Labeling Restriction (RLR)
• All routing information or intruder identification packets
from hosts in blacklist will be ignored, unless the
information is about themselves.
• After a host is released from the blacklist, the routing
information or identification results from it will be
processed.
82
Example to illustrate RLR
BL {}
S3
S
BL {S1}
D
INVALID ( D, 5, 21,
{}, SIGN )
S1 BL {S2}
S2
BL {M}
M BL {}
S4
BL {}
D sends INVALID packet with current sequence = 5, new sequence = 21. S3
examines its route table, the entry to D is not false. S3 forward packet to S1. S1
finds that its route entry to D has sequence 20, which is > 5. It knows that the
route is false. The hop which provides this false route to S1 was S2. S2 will be put
into S1’s blacklist. S1 forward packet to S2 and S. S2 adds M into its blacklist. S
adds S1 into its blacklist. S forward packet to S4. S4 does not change its blacklist
since it is not involved in this route.
83
Reverse Labeling Restriction (con’d)
• Update Blacklist by INVALID Packet
• Next hop on the invalid route will be put into local
blacklist, a timer starts, a counter ++
• Labeling process will be done in the reverse direction
of route
• When timer expires, the suspicious host will be
released from the blacklist and routing information
from it will be accepted
• If counter > threshold, the suspicious host will be
permanently put into blacklist
84
RLR creates suspicion trees. If a host is the root of a
quorum of suspicion trees, it is labeled as the attacker.
85
Reverse Labeling Restriction (con’d)
• Update local blacklist by other hosts’ blacklist
• Attach local blacklist to INVALID packet with
digital signature to prevent impersonation
• Every host will count the hosts involved in
different routes that say a specific host is
suspicious. If the number > threshold, it will be
permanently added into local blacklist and
identified as an attacker.
• Threshold can be dynamically changed or can
be different on various hosts
86
Reverse Labeling Restriction (con’d)
• Two other effects of INVALID packets
• Establish routes to the destination host: when
the host sends out INVALID packet with digital
signature, every host receiving this packet can
update its route to the destination host through
the path it gets the INVALID packet.
• Enable new sequence: When the destination
sequence reaches its max number (0x7fffffff)
and needs to round back to 0, the host sends an
INVALID packet with current sequence =
0x7fffffff, new sequence = 0.
87
Reverse Labeling Restriction (con’d)
• Packets from suspicious hosts
• Route request: If the request is from suspicious hosts,
ignore it.
• Route reply: If the previous hop is suspicious and the
query destination is not the previous hop, the reply will
be ignored.
• Route error: will be processed as usual. RERR will
activate re-discovery, which will help to detect attacks
on destination sequence.
• INVALID: if the sender is suspicious, the packet will be
processed but the blacklist will be ignored.
88
Simulation parameter
Simulation duration
1000 seconds
Simulation area
1000 * 1000 m
Number of mobile hosts
Transmission range
Pause time between the host reaches
current target and moves to next
target
30
250 m
0 – 60 seconds
Maximum speed
5 m/s
Number of CBR connection
25/50
Packet rate
2 pkt / sec
89
Reverse Labeling Restriction (con’d)
Simulation results
The following metrics are chosen:
• Delivery ratio (evaluate effectiveness of RLR)
• Number of normal hosts that identify the attacker
(evaluate accuracy of RLR)
• Number of normal hosts that are marked as attacker by
mistake (evaluate accuracy of RLR)
• Normalized overhead (evaluate communication
overhead of RLR)
• Number of packets to be signed (evaluate computation
overhead of RLR)
90
Reverse Labeling Restriction (con’d)
X-axis is host pause time, which evaluates the mobility of host. Y-axis is
delivery ratio. 25 connections and 50 connections are considered. RLR
brings a 30% increase in delivery ratio. 100% delivery is difficult to
achieve due to network partition, route discovery delay and buffer.
91
Reverse Labeling Restriction (con’d)
X-axis is number of attackers. Y-axis is delivery ratio. 25 connections
and 50 connections are considered. RLR brings a 20% to 30% increase
in delivery ratio.
92
Reverse Labeling Restriction (con’d)
30 hosts, 25 connections
Host Pause time
(sec)
# of normal
hosts identify
the attacker
# of normal
hosts marked as
malicious
30 hosts, 50 connections
# of normal
hosts identify
the attacker
# of normal
hosts marked as
malicious
0
24
0.22
29
2.2
10
25
0
29
1.4
20
24
0
25
1.1
30
28
0
29
1.1
40
24
0
29
0.6
50
24
0.07
29
1.1
60
24
0.07
24
1.0
The accuracy of RLR when there is only one attacker in
the system
93
Reverse Labeling Restriction (con’d)
# of attackers
30 hosts, 25 connections
30 hosts, 50 connections
# of normal
# of normal
hosts identify all hosts marked as
attackers
malicious
# of normal
# of normal
hosts identify all hosts marked as
attackers
malicious
1
28
0
29
1.1
2
28
0.65
28
2.6
3
25
1
27
1.4
4
21
0.62
25
2.2
5
15
0.67
19
4.1
The accuracy of RLR when there are multiple attackers
94
Reverse Labeling Restriction (con’d)
X-axis is host pause time, which evaluates the mobility of host. Yaxis is normalized overhead (# of control packet / # of delivered
data packet). 25 connections and 50 connections are considered.
RLR increases the overhead slightly.
95
Reverse Labeling Restriction (con’d)
X-axis is host pause time, which evaluates the mobility of host. Yaxis is the number of signed packets processed by every host. 25
connections and 50 connections are considered. RLR does not
severely increase the computation overhead to mobile host.
96
Reverse Labeling Restriction (con’d)
X-axis is number of attackers. Y-axis is number of signed packets
processed by every host. 25 connections and 50 connections are
considered. RLR does not severely increase the computation
overhead of mobile host.
97
Robustness of RLR
• If the malicious host sends false INVALID
packet
• Because the INVALID packets are signed, it cannot
send the packets in other hosts’ name
• If it sends INVALID in its own name, the reverse
labeling procedure will converge on the malicious
host and identify the attacker. The normal hosts
will put it into their blacklists.
98
Robustness of RLR
• If the malicious host frames other innocent hosts
by sending false Blacklist
• If the malicious host has been identified, the blacklist
will be ignored
• If the malicious host has not been identified, this
operation can only lower the threshold by one. If the
threshold is selected properly, it will not impact the
identification results.
99
Robustness of RLR
• If the malicious host only sends false
destination sequence about some special host
• The special host will detect the attack and send
INVALID packets.
• Other hosts can establish new routes to the
destination by receiving the INVALID packets.
100
Securing Ad Hoc networks -- Establish trust
relationship in open area
• Evaluate known knowledge
 Known knowledge:
• Interpretations of observations
• Recommendations
 An algorithm that evaluates trust among hosts is being
developed
 A host’s trustworthiness affects the trust toward the
hosts on the route
• Predict of trustworthiness of a host
 Current approach uses the result of evaluation as
prediction.
101
Securing Ad Hoc networks -- Establish trust
relationship in open area
• What trust information is needed when adding/
removing suspicious host from blacklist?
 The trust opinion of S1 towards an entity S2 in
a certain context R
• What characteristics of trust need to be included in
the model?
 Dependability: combination of competence,
benevolence, and integrity
 Predictability
102
Securing Ad Hoc networks -- Establish trust
relationship in open area
What is the suitable representation of trust?
• A random variable is used to represent trust so
that the inherent uncertainty of deriving trust
from behaviors can be accommodated.
How to represent the interpretation of an observation?
• A trust distribution function
103
Further Work
• Design a set of formalized criteria to evaluate
identification algorithms
• Study more features of Ad Hoc networks and
exploit their vulnerability
• Simulate attacks on RLR, examine its robustness
• Integrate with research on trust
• Methods to identify the non-attackers and release
them from blacklist
• Mechanisms to release hosts from the permanent
blacklist
104
• More information may be found at
http://raidlab.cs.purdue.edu
• Our papers and tech reports
W. Wang, Y. Lu, B. Bhargava, On vulnerability and protection of
AODV, CERIAS Tech Report TR-02-18.
B. Bhargava, Y. Zhong, Authorization based on Evidence and Trust,
in Proceedings of Data Warehouse and Knowledge Management
Conference (DaWak), 2002
Y. Lu, B. Bhargava and M. Hefeeda, An Architecture for Secure
Wireless Networking, IEEE Workshop on Reliable and Secure
Application in Mobile Environment, 2001
W. Wang, Y. Lu, B. Bharagav, “On vulnerability and protection of
AODV”, in proceedings of ICT 2003.
W. Wang, Y. Lu, B. Bhargava, “On security study of two distance
vector routing protocols for two mobile ad hoc networks”, in
proceedings of PerCOm 2003.
105
Selected References
•
•
•
•
•
•
•
•
[1] C. Perkins and E. Royer, “Ad-hoc on-demand distance vector routing,” in
Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and
Applications, 1999.
[2] C. Perkins, “Highly dynamic destination-sequenced distancevector routing
(DSDV) for mobile computers,” in Proceedings of SIGCOMM, 1994.
[3] Z. Haas and M. Pearlman, “The zone routing protocol (ZRP) for ad hoc
networks,” IETF Internet Draft, Version 4, July, 2002.
[4] T. Camp, J. Boleng, B. Williams, L. Wilcox, and W. Navidi, “Performance
comparison of two location based routing protocols for ad hoc networks,” in
Proceedings of the IEEE INFOCOM, 2002.
[5] Z. Haas, J. Halpern, and L. Li, “Gossip-based ad hoc routing,” in
Proceedings of the IEEE INFOCOM, 2002.
[6] C. Perkins, E. Royer, and S. Das, “Performance comparison of two ondemand routing protocols for ad hoc networks,” in Proceedings of IEEE
INFOCOM, 2000.
[7] S. Das and R. Sengupta, “Comparative performance evaluation of routing
protocol for mobile, ad hoc networks,” in Proceedings of IEEE the Seventh
International Conference on Computer Communications and Networks, 1998.
[8] L. Venkatraman and D. Agrawal, “Authentication in ad hoc networks,” in
Proceedings of the 2nd IEEE Wireless Communications and Networking
Conference, 2000.
106
Selected References
•
•
•
•
•
•
•
[9] Y. Zhang and W. Lee, “Intrusion detection in wireless ad-hoc networks,” in
Proceedings of ACM MobiCom, 2000.
[10] Z. Zhou and Z. Haas, “Secure ad hoc networks,” IEEE Networks, vol. 13,
no. 6, pp. 24–30, 1999.
[11] V. Bharghavan, “Secure wireless LANs,” in Proceedings of the ACM
Conference on Computers and Communications Security, 1994.
[12] P. Sinha, R. Sivakumar, and V. Bharghavan, “Enhancing ad-hoc routing
with dynamic virtual infrastructures.,” in Proceedings of IEEE INFOCOM,
2001.
[13] S. Bhargava and D. Agrawal, “Security enhancements in AODV protocol
for wireless ad hoc networks,” in Proceedings of Vehicular Technology
Conference, 2001.
[14] P. Papadimitratos and Z. Haas, “Secure routing for mobile ad hoc
networks,” in Proceedings of SCS Communication Networks and Distributed
Systems Modeling and Simulation Conference (CNDS), 2002.
[15] P. Albers and O. Camp, “Security in ad hoc network: A general id
architecture enhancing trust based approaches,” in Proceedings of
International Conference on Enterprise Information Systems (ICEIS), 2002.
107