On Security Study of Two Distance Vector Routing Protocols for Ad Hoc Networks
Weichao Wang, Yi Lu, Bharat Bhargava
CERIAS and Department of Computer Sciences
Purdue University
March 24th, 2003*The research is supported by CERIAS, CISCO URP and NSF
CCR-0001788
2
Index
Research motivation Introduction to protocols Security observations and simulation results Detecting false sequence attacks Intruder identification and reverse labeling
restriction (RLR) Experimental studies Conclusion
3
Research motivation
The hybrid of Internet, cellular system and mobile ad hoc networks introduces vulnerabilities. [S. Bush, GE Research ’99]
Security is a central requirement for mobile ad hoc networks. [Hubaux et al, MobiCom ’01]
More than ten routing protocols. Security and robustness will impact the design of the standard for ad hoc networks. [Corson & Macker, IETF MANET WG ’02]
4
Destination sequenced distance vector (DSDV) Proposed by Perkins in [SigCOMM ’94]; The nodes periodically broadcast the routing tables and
proactively construct the routes; Using destination sequence numbers to avoid routing loop
and identify the freshness of the information; Advantages:
Short delay brought by the proactive feature Difficult for the attackers to control the propagation of false
information Disadvantages:
Difficult to scale to large networks Computation and communication resources wasted on
unused routes
Introduction to DSDV
5
Ad hoc on-demand distance vector (AODV) Proposed by Perkins and Royer [Mobile Computing and
Applications ’99]; The routes are detected only when they are needed
by the applications; Broadcast routing request (RREQ) and unicast routing
reply (RREP) Using destination sequence numbers to avoid routing
loop and identify the freshness of the information; Advantages:
Low overhead and smaller routing tables Disadvantages:
On-demand feature brings a longer delay for the first packet Malicious nodes have more flexibility on conducting attacks
Introduction to AODV
6
Attacks on ad hoc routing procedure
Attacks on routing
Active attacks Passive attacks
Packet silent discard
Routing information hiding
Routing procedure
Flood network
False reply Wormhole attacks
Route request
Route broken message
False distance vector
False destination sequence
7
Example attacks on AODV and DSDV
Silent packet discard False distance vector attacks False destination sequence attacks Routing request flood False route error packets
8
AODV: the malicious node can immediately form a false route reply when it receives the route request.
DSDV: the malicious node must send false routes in advance. So the attacks require a longer duration.
AODV: the malicious node can make flexible choices on the type of attacks and timing of attacks when it sends false reply to a request.
AODV: the routing reply is unicast to the source, it is more difficult to trace back to the malicious node.
Security observations
9
DSDV: the routing packets are broadcast. It is easier for the intrusion detection system to detect the attacks.
DSDV: the malicious node can carry multiple false routes in its routing broadcast packets. So the communication overhead for the attacker is stable when it attacks multiple routes.
Security observations (con’d)
10
Two kinds of attacks: false distance vector (hop) false destination sequence attacks
Two conditions for route discovery: one common destination hybrid connection (random selection of source and destination
in multiple routes) Input parameters:
maximum speed of nodes number of connections;
Output parameters: packet delivery ratio communication overhead for the attacker (number of false route
reply) number of good nodes cheated by the false routes
Simulation of attacks
11
Parameters in Simulation
Simulator ns-2
Protocols AODV and DSDV
Simulation duration 1000 seconds
Simulation area 1000 m x 1000 m
Number of nodes 30
Transmission range 250 m
Movement model Random waypoint
Maximum speed 5 – 20 m/s
Traffic type CBR (UDP)
Data payload 512 bytes/packet
Packet rate 2 packets/sec
Number of malicious node 1
Node pause time 10 seconds
Number of connections 5 – 29
13
Simulation results of one destination
Figure 2: Cheated (affected) nodes versus number of connections
14
Simulation results of one destination
Figure 3: Communication overhead versus number of connections
15
Simulation results combining figure 2 and 3
Figure 4: cheated nodes versus number of false route packets
18
The attackers must choose a large number as the false sequence to show its “freshness”. If this number can be detected by the destination node, the attack will be detected.
Detecting false destination sequence attacks
D
S S1
S2 M
S3
S4
RREQ(D, 3, ?)
RREP(D, 5)
RREP(D, 20)RREP(D, 20)X
RREQ(D, 20, ?)
!! If local DS is only 5, how can other host get 20 ??
19
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.
Intruder identification in AODVFor more details, refer to the tech report at
www.cs.purdue.edu/people/bb
20
Intruder identification
Objectives: locate the source of attackscombine the information from multiple
nodes and enable each node to make independent decision
achieve consistency among the conclusions of a group of nodes
21
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
22
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.
23
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.
24
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.
25
Example to illustrate RLR
D
S S1
S2 M
S3
S4
BL {}
BL {S2}
BL {}BL {M}
BL {S1}
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.
INVALID ( D, 5, 21, {}, SIGN )
26
RLR creates suspicion trees. If a host is the root of a quorum of suspicion trees, it is labeled as the attacker.
27
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
28
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
29
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.
30
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.
31
Simulation parameter
Simulation duration 1000 seconds
Simulation area 1000 * 1000 m
Number of mobile hosts 30
Transmission range 250 m
Pause time between the host reaches current target and moves to next target
0 – 60 seconds
Maximum speed 5 m/s
Number of CBR connection 25/50
Packet rate 2 pkt / sec
32
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)
33
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.
34
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.
Reverse Labeling Restriction (con’d)
35
Reverse Labeling Restriction (con’d)
30 hosts, 25 connections 30 hosts, 50 connections
Host Pause time (sec)
# of normal hosts identify the attacker
# of normal hosts marked as malicious
# 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
36
Reverse Labeling Restriction (con’d)
30 hosts, 25 connections 30 hosts, 50 connections
# of attackers # of normal hosts identify all attackers
# of normal hosts marked as malicious
# of normal hosts identify all attackers
# of normal hosts marked as 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
37
X-axis is host pause time, which evaluates the mobility of host. Y-axis is normalized overhead (# of control packet / # of delivered data packet). 25 connections and 50 connections are considered. RLR increases the overhead slightly.
Reverse Labeling Restriction (con’d)
38
Reverse Labeling Restriction (con’d)
X-axis is host pause time, which evaluates the mobility of host. Y-axis 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.
39
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.
40
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.
41
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.
42
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.
43
The malicious nodes in on-demand protocols can cause real time attacks
The malicious nodes in proactive protocols can send multiple false routes in the same round
False destination sequence attacks cause a more severe impact on network performance than false distance vector attacks
The destination node in proactive protocols has a higher probability to detect attacks because the false routes are broadcast throughout the network
Using RLR, the good nodes in AODV can efficiently locate the attackers
Observations & Conclusions
44
Study the relationship between the average detection delay and the mobility of the nodes
Study more types of attacks (include gang attacks) and ascertain their relations to the vulnerabilities of the protocols
Study the joint responses to detect attacks and identify intruders
The results will lead to a secure routing protocol for mobile ad hoc networks
A complete system to implement intruder identification
Future work