DDoS Attack and Defense Scheme in Wireless Ad hoc Networks

International Journal of Network Security & Its Applications (IJNSA), Vol.3, No.3, May 2011
DOI : 10.5121/ijnsa.2011.3312 182
DDoS Attack and Defense Scheme in Wireless
Ad hoc Networks
S.A.Arunmozhi1
, Y.Venkataramani2
1.
Associate Professor,Dept. of ECE, Saranathan College of Engineering,India
2
.Principal, Saranathan College of Engineering, India
Abstract. The wireless ad hoc networks are highly vulnerable to distributed denial of service(DDoS)
attacks because of its unique characteristics such as open network architecture, shared wireless medium
and stringent resource constraints. These attacks throttle the tcp throughput heavily and reduce the
quality of service(QoS) to end systems gradually rather than refusing the clients from the services
completely. In this paper, we discussed the DDoS attacks and proposed a defense scheme to improve the
performance of the ad hoc networks. Our proposed defense mechanism uses the medium access control
(MAC) layer information to detect the attackers. The status values from MAC layer that can be used for
detection are Frequency of receiving RTS/CTS packets, Frequency of sensing a busy channel and the
number of RTS/DATA retransmissions. Once the attackers are identified, all the packets from those
nodes will be blocked. The network resources are made available to the legitimate users. We perform the
simulation with Network Simulator NS2 and we proved that our proposed system improves the network
performance.
Key words: distributed denial-of-service (DDoS), wireless ad hoc networks, medium access
control, bandwidth reservation, distributed rate control.
1 Introduction
Wireless networks are inherently susceptible to security problems. The intrusion on the
transmission medium is easier than for wired networks and it is possible to conduct denial of
service attacks by scrambling the used frequency bands. The ad hoc context increases the
number of potential security vulnerabilities. Ad hoc networks can not benefit from the security
services offered by dedicated equipment such as firewalls, authentication servers and so on.
The security services must be distributed, cooperative and consistent with the available
bandwidth.
One of the serious attacks to be considered in ad hoc network is DDoS attack. A DDoS
attack is a large-scale, coordinated attack on the availability of services at a victim system or
network resource. The DDoS attack is launched by sending an extremely large volume of
packets to a target machine through the simultaneous cooperation of a large number of hosts
that are distributed throughout the network. The attack traffic consumes the bandwidth
resources of the network or the computing resource at the target host, so that legitimate requests
will be discarded.
A bandwidth depletion attack is designed to flood the victim network with unwanted
traffic that prevents legitimate traffic from reaching the victim system. A resource depletion
attack is an attack that is designed to tie up the resources of a victim system. This type of attack
targets a server or process at the victim making it unable to legitimate requests for service. Any
amount of resources can be exhausted with a sufficiently strong attack. The only viable
approach is to design defense mechanism that will detect the attack and respond to it by
dropping the excess traffic.
The DoS attacks that target resources can be grouped into three broad scenarios. The
first attack scenario targets Storage and Processing Resources. This is an attack that mainly
targets the memory, storage space, or CPU of the service provider. Consider the case where a
node continuously sends an executable flooding packet to its neighborhoods and to overload the

183
storage space and deplete the memory of that node. This prevents the node from sending or
receiving packets from other legitimate nodes. The second attack scenario targets energy
resources, specifically the battery power of the service provider. A malicious node may
continuously send a bogus packet to a node with the intention of consuming the victim’s battery
energy and preventing other nodes from communicating with the node. The use of localized
monitoring can help in detecting such nodes and preventing their consequences. The third
attack scenario targets bandwidth. Consider the case where an attacker located between
multiple communicating nodes wants to waste the network bandwidth and disrupt connectivity.
This consumes the resources of all neighbors that communicate, overloads the network, and
results in performance degradations. Such attacks can be prevented based on our proposed
congestion based defense scheme.
2 Related Work
Xiapu Luo et al [1] have presented the important problem of detecting pulsing denial of service
(PDoS) attacks which send a sequence of attack pulses to reduce TCP throughput. Wei-Shen
Lai et al [3] have proposed a scheme to monitor the traffic pattern in order to alleviate
distributed denial of service attacks. Shabana Mehfuz1 et al [4] have proposed a new secure
power-aware ant routing algorithm (SPA-ARA) for mobile ad hoc networks that is inspired
from ant colony optimization (ACO) algorithms such as swarm intelligent technique. Xiaoxin
Wu et al [6] proposed a DoS mitigation technique that uses digital signatures to verify
legitimate packets, and drop packets that do not pass the verification Ping Yi, Zhoulin Dai,
Shiyong Zhang and Yiping Zhong [8] have presented a new DOS attack and its defense in ad
hoc networks. The new DOS attack, called Ad Hoc Flooding Attack(AHFA), can result in
denial of service when used against on-demand routing protocols for mobile ad hoc networks,
such as AODV & DSR. John Haggerty, Qi Shi and Madjid Merabti [9] have proposed a new
approach that utilizes statistical signatures at the router to provide early detection of flooding
denial-of-service attacks. Wei Ren, Dit-Yan Yeung, Hai Jin, Mei Yang [11] have proposed a
defense scheme that includes both the detection and response mechanisms. In this paper the
detection scheme that monitors MAC layer signals and a response scheme based on Explicit
Congestion Notification (ECN) marking are discussed. But, the method of monitoring the
sending rates of the nodes is not discussed. Hence identifying the attacking nodes becomes a
problem. It may also result in increase of false positives and false negatives. Gahng-Seop Ahn
et al [12] have proposed SWAN, a stateless network model which uses distributed control
algorithms to deliver service differentiation in mobile wireless ad hoc networks in a simple,
scalable and robust manner. Giriraj Chauhan and Sukumar Nandi [13] proposed a QoS aware
on demand routing protocol that uses signal stability as the routing criteria along with other
QoS metrics.
3 Proposed Defense Technique
In this paper, we propose a new defense mechanism which consists of a flow monitoring table
(FMT) at each node. It contains flow id, source id, packet sending rate and destination id.
Sending rates are estimated for each flow in the intermediate nodes. The updated FMT is sent
to the destination along with each flow. After monitoring the MAC layer signals the destination
sends the Explicit Congestion Notification (ECN) bit to notify the sender nodes about the
congestion. The sender nodes, upon seeing these packets with ECN marking, will then reduce
their sending rate. If the channel continues to be congested because some sender nodes do not
reduce their sending rate, it can be found by the destination using the updated FMT. It checks
the previous sending rate of a flow with its current sending rate. When both the rates are same,
the corresponding sender of the flow is considered as an attacker. Once the DDoS attackers are
identified, all the packets from those nodes will be discarded.

184
The two phases of the proposed scheme are Bandwidth querying phase and Data
transmission phase. In bandwidth querying phase the control messages sent are Bandwidth
query request and Bandwidth query reply. The request packet includes the source IP address,
destination IP address, type of the message, flow ID, and requested data rate which is stored in
the bottleneck bandwidth (BnBW) field. In Bandwidth querying phase of the proposed scheme,
the node’s FMT information along a path is computed. An intermediate node updates its FMT
using the BnBW value stored in the reply packet after receiving a REPLY message on the
reverse path, and then forwards the REPLY to the next node. The available bandwidth ABWj is
checked first. The reservation of bandwidth for the flow can be made if the value of ABWj is
greater than or equal to the BnBW value in the REPLY packet. Else, the BnBW value in the
REPLY packet is overwritten with the smaller value of ABWj. Next, the current BnBW value in
the REPLY packet is added to the reserved rate RRij, associated with the in-out stream. A FMT
entry is created with an assigned rate value ARij, set equal to the BnBW value of the REPLY
packet, if the stream (i, j) was previously inactive. Subsequently, the REPLY packet is
forwarded to the next node on the reverse path. Finally, based on the value of the BnBW field,
the source establishes the real-time flow when the REPLY packet reaches the source node.
Distributed Rate Control
The actual rate ACRij is given by
ACRij=W*ARij (1)
Where,
W =








∑ ARij
Lc
where Lc is the link capacity of each link.
If the source receives the congestion bit (CB), then the assigned rate ARij can be written as
ARij=ACRij–δ (2)
Where δ is the rate reduction factor.
The rate monitoring function measures the traffic rate of a given in-out stream over a time
interval T.
MRij=Cij/T (3)
If the measured rate MRij is greater than actual rate ACRij for the next time interval then the
flow is considered to be an attack flow. Then its status is marked as REJECTED and the
corresponding source IP address is recorded from the FMT.
4 Experimental Results
The network simulator NS2 is used to simulate our proposed algorithm. In our simulation, the
channel capacity of mobile hosts is set to the same value: 2 Mbps. The distributed coordination
function (DCF) of IEEE 802.11 is used for wireless LANs as the MAC layer protocol. It has the
functionality to notify the network layer about link breakage. The simulated traffic is Constant
Bit Rate (CBR).
Our simulation settings and parameters are summarized in table 1.
Table1: Simulation Parameters
No. of Nodes 80
Area Size 1200 X 1200
Mac 802.11
Radio Range 250m
Simulation Time 60 sec
Traffic Source CBR
Packet Size 512
Routing Protocol AODV

185
The experiment is carried out with five different normal flow of traffic with the data rate of 50
kbps and an attacking flow with the data rate of 500 kbps. The received bandwidth at the
destination node over a period of time is obtained using the simulation and the results are
shown in Fig. 1. The proposed system is compared with SWAN [2] and it is observed that the
bandwidth received for the proposed system is greater compared to the other scheme. The
bandwidth reservation technique and the distributed rate control technique of our proposed
method make to achieve more bandwidth received for the legitimate users. Hence we are able
to obtain greater bandwidth received for our proposed scheme than the SWAN.
Fig. 1 Bandwidth Received Vs Time
The number of lost packets at the destination node over the period of time is shown in Fig. 2.
From the graph, it is known that the number of packets lost for the proposed system is less
compared to the SWAN. Since the attacking flows are rejected effectively in our proposed
scheme, the network resources are made available to the legitimate users. This makes the
dropping rate of legitimate packets low compared to the other scheme.
Fig. 2 Lost Packets Vs Time
The simulation is also carried with the variable number of attacking flows. Since the attacker
are effectively identified and blocked in our scheme, it is again seen that the proposed scheme
achieves greater received bandwidth. It is also observed that as the number of attackers is
increased, the bandwidth received gets increased due to greater amount of traffic. The
simulation results are shown in Fig. 3.
Bandwidth Received Vs Time
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0 5 10 15 20 25 30 35 40 45 50 55
Time(secs)
BandwidthReceived(Mbps)
PROPOED
SWAN
Lost packets Vs Time
0
2000
4000
6000
8000
10000
0 5 10 15 20 25 30 35 40 45 50 55
Time(secs)
Lostpackets
PROPOSED
SWAN

186
Fig. 3 Bandwidth Received Vs Attackers
The packet delivery ratio is the ratio of the number of packets received successfully and the
total number of packets sent. Since the proposed scheme is congestion based scheme, the
distributed rate control is applied when there is a heavy traffic due to the attacking flows.
Hence the number of dropped packets is well reduced. As the dropped packets are reduced,
more number of packets is delivered to the destination. Hence greater packet delivery ratio is
achieved for the proposed scheme. The simulation results are shown in Fig. 4.
Fig. 4 Packet Delivery Ratio Vs Attackers
Fig. 5 Dropped Packets Vs Attackers
The number of dropped packets at the destination node with varying number of attackers is
shown in Fig. 5. From the graph, it is known that the number of dropped packets for the
proposed system is less compared to the SWAN. Since the attacking flows are rejected
effectively, the dropping rate of legitimate packets low compared to the other scheme.
5 Conclusion
In this paper, we discussed the DDoS attacks and proposed a defense scheme to mitigate the
attack in wireless ad hoc networks. Our approach can accurately identify DDoS attack flows
and consequently apply rate-limiting to the malicious network flows. Our proposed defense
mechanism identifies the attackers effectively. Once the attackers are identified, the attack
traffic is discarded. This makes the network resources available to the legitimate users. We
Bandwidth Received Vs Attackers
0
0.5
1
1.5
2
2.5
2 4 6 8
AttackersBandwidthReceived(Mbps)
PROPOSED
SWAN
Packet Delivery Ratio Vs Attackers
0
10
20
30
40
50
60
70
2 4 6 8
Attackers
PacketDeliveryRatio
PROPOSED
SWAN
Dropped Packets Vs Attackers
0
20000
40000
60000
80000
100000
120000
2 4 6 8
Attackers
DroppedPackets
PROPOSED
SWAN

187
compared the performance of our proposed scheme with the SWAN scheme and proved that
our proposed scheme assures better performance. By simulation results, we have shown that
our proposed scheme achieves higher bandwidth received and packet delivery ratio with
reduced packet drop for legitimate users.
References
1. Xiapu Luo, Edmond W.W.Chan,Rocky K.C.Chang: Detecting Pulsing
Denial-of-Service Attacks with Nondeterministic Attack Intervals, EURASIP Journal on
Advances in Signal Processing (2009)
2. Gahng-Seop Ahn, Andrew T. Campbell, Andras Veres, Li-Hsiang Sun:SWAN: Service
Differentiation in Stateless Wireless Ad Hoc Networks, in Proceedings of IEEE Twenty-First
Annual Joint Conference of the IEEE Computer and Communications Societies, INFOCOM, Vol. 2
(2002)
3. Wei-Shen Lai, Chu-Hsing Lin , Jung-Chun Liu , Hsun-Chi Huang, Tsung-Che Yang: Using
Adaptive Bandwidth Allocation Approach to Defend DDoS Attacks, International Journal of
Software Engineering and Its Applications, Vol. 2, No. 4, pp. 61-72 (2008)
4. ShabanaMehfuz, Doja,M.N.: Swarm Intelligent Power-Aware Detection of Unauthorized and
Compromised Nodes in MANETs”, Journal of Artificial Evolution and Applications (2008)
5. Nagesh,H.R.,Chandra Sekaran,K.: Design and Development of Proactive Models for Mitigating
Denial-of-Service and Distributed Denial-of-Service Attacks, International Journal of Computer
Science and Network Security, Vol. 7, No.7 (2007)
6. Xiaoxin Wu, David,K.Y.Yau, Mitigating Denial-of-Service Attacks in MANET by Distributed
Packet Filtering: A Game-theoretic Approach, in Proceedings of the 2nd
ACM symposium on
Information, computer and communication security, pp 365-367 (2006)
7. Sugata Sanyal, Ajith Abraham, Dhaval Gada, Rajat Gogri, Punit Rathod, Zalak Dedhia,Nirali Mody:
Security Scheme for Distributed DoS in Mobile Ad Hoc Networks, ACM, Newyork,USA (2004)
8. Ping Yi, Zhoulin Dai, Shiyong Zhang, Yiping Zhong: A New Routing Attack in Mobile Ad Hoc
Networks, International Journal of Information Technology, Vol. 11, No.2 (2005)
9. John Haggerty, Qi Shi, Madjid Merabti: Statistical Signatures for Early Detection of Flooding
Denial-Of service Attacks , Springer, 2005, Vol. 181, pp. 327-341 (2005)
10. Giovanni Vigna, Sumit Gwalani, Kavitha Srinivasan: An Intrusion Detection tool for AODV-based
Ad hoc Wireless Networks, in Proceedings of the Annual Computer Security Applications
Conference, pp.16-27 (2004)
11. Wei Ren, Dit-Yan Yeung, Hai Jin, Mei Yang: Pulsing RoQ DDoS Attack and Defense Scheme in
Mobile Ad Hoc Networks, International Journal of Network Security, Vol. 4, No.2, pp. 227-234
(2007)
12. Yang Xiang, Wanlei Zhou, Morshed Chowdhury: A Survey of Active and Passive Defense
Mechanisms against DDoS Attacks, Technical reports, Computing series, Deakin university,School
of Information Technology(2004)
13. Giriraj Chauhan,Sukumar Nandi: QoS Aware Stable path Routing (QASR) Protocol for MANETs,
in First International Conference on Emerging Trends in Engineering and Technology, pp. 202-207
(2008).
14. Amey Shevtekar, Nirwan Ansari: A router-based technique to mitigate reduction of quality (RoQ)
attacks, Computer Networks: The international Journal of Computer & Telecommunication
Networking, Vol. 52, No.5, pp. 957–970 (2008)
15. Rajaram,A., Palaniswami,S.: The Trust-Based MAC-Layer Security Protocol for Mobile Ad hoc
Networks, International Journal on Computer Science and Engineering, Vol. 2, No. 02, pp. 400-408
(2010)
16. L. Zhou and Z. Haas, Securing Ad Hoc Networks, IEEE Network Magazine Vol.13 No.6, pp. 24-
30, (1999).
17. Y. Hu, D. Johnson, and A. Perrig, SEAD: Secure Efficient Distance Vector Routing in Mobile
Wireless Ad-Hoc Networks. Proc. of the 4th IEEE Workshop on Mobile Computing Systems and
Applications (WMCSA’02), pp. 3-13, (2002).
18. Arunmozhi, S. A. and Venkataramani, Y. : A Flow Monitoring Scheme to Defend Reduction-of-
Quality (RoQ) Attacks in Mobile Ad-hoc Networks, Information Security Journal: A Global
Perspective, Vol.19, No.5, pp. 263 – 272, (2010).

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