IJIRST –International Journal for Innovative Research in Science & Technology| Volume 3 | Issue 02 | July 2016 ISSN (online): 2349-6010
Performance Evaluation of AODV, DSDV and DSR or Avoiding Selective Jamming Attacks in WLAN Parikh D A PG Scholar Department of Computer Engineering L D College Of Engineering Ahmedabad(Guj) India
Dr. Wandra K. H. Principal Department of Computer Engineering C U Shah Engineering College, Wadhawan City (Guj)India
Abstract Jamming is always an issue in wireless network. An internal threat model of wireless network is vulnerable to the selective jamming attacks. In these attacks, the adversary node with internal knowledge of protocol specifications and network secrets can launch low-effort jamming attacks that are difficult to detect and counter. The adversary node is active only for short period of time and selectively targets specific packets of “high” importance by exploiting his knowledge on the implementation details of network that leads network performance degradation. To reduce this attack, we develop an algorithm that prevents real-time packet classification by combining cryptographic primitives with physical-layer attributes. In NS2 simulation environment, we analyze the effects of AODV, DSDV and DSR routing protocol on selective jamming attacks and prevention of these attacks in wireless network by our proposed algorithm. The performance of network analyzed in terms of various performance parameters like packet delivery ratio (PDR), packet loss ratio (PLR), end to end delay (E2E). Keywords: Selective Jamming, Internal Threat Model, Routing Protocol, PDR, PLR _______________________________________________________________________________________________________ I.
INTRODUCTION
In Wireless Network, Anyone with a transceiver can eavesdrop on wireless transmissions, inject spurious messages, or jam legitimate ones. A Wireless communication standard such as IEEE802.11 and Bluetooth are easy targets of DoS attacks .Other wireless data standards that make use of error-correction codes are also not secured. Jamming attacks have been considered under an external threat model, in which the jammer is not part of the network. At present, anti-jamming systems rely on an extensive use of spread-spectrum techniques. These techniques separately protect bits against jammers. They are used in voice communication where the jammer has to keep jamming the channel to prevent a communication. Our work aims at building antijamming techniques, used at the bit level to protect data packets from jamming. In the context of internal threat model, a small number of smart jammers located across a geographical area can last for a long period of time with limited energy. The adversary node sends the continuous or random transmission of high- power interference signals. In these attacks, the adversary is active only for a short period of time, selectively targeting messages of high importance. The adversary nodes can stay in sleep mode most of the time and be triggered to jam some communication between specific nodes. In this case, the attackers would only wake-up to detect some MAC/IP address and, if needed, jam only few bits of the packet to destroy. The attacking nodes receivers can be designed to consume very little energy even if anti-jamming techniques, such as spread-spectrum, are used, the substantial gain achieved by having to jam only few bits out of 1500 bytes IP packets can be invested in a higher signal power (for DSSS) or multi-channel jamming (for FHSS) [5]. II. TYPES OF JAMMING Following two techniques are discussed as per our work scenarios [4]. Physical Jamming (Physical Layer) Physical or Radio jamming in a wireless network is done by either continuous emission of radio signals or by sending random bits onto the channel. The jammers causing these attacks can refuse complete access to the channel by monopolizing the wireless medium. This has an adverse propagating effect as the nodes enter into large exponential back-off periods [4]. Virtual Jamming (MAC Layer) In IEEE 802.11 based MAC protocols, Jamming can be launched at the MAC layer through attacks on the RTS/CTSframes or DATA frames. A significant advantage of MAC layer jamming is that the adversary node consumes less power in targeting these attacks as compared to the physical radio jamming [4].
All rights reserved by www.ijirst.org
165
Performance Evaluation of AODV, DSDV and DSR or Avoiding Selective Jamming Attacks in WLAN (IJIRST/ Volume 3 / Issue 02/ 030)
III. DETECTION & PREVENTION OF JAMMING The network implements a monitoring mechanism for detecting potential malicious activity by a jammer. The monitoring mechanism [4], [5] consists of the following: (i) determination of a subset of nodes m that will act as network monitors, and (ii) employment of a detection algorithm at each monitor node. The assignment of the role of monitor to a node can be affected by energy limitations and detection performance specifications. In this work, we fix m and formulate optimization problems for one or more monitor nodes. We now check detection at one monitor node. First, we define the quantity to be observed at each monitor node. In our case, available metric is probability of collision that node experiences, namely the percentage of packets that are erroneously received. .A detection algorithm takes observation sample so obtained at the monitor node (i.e, collision or not collision) and decides whether there exists an attack. On one hand, the observation window should be small enough, such that the attack is detected on time and appropriate countermeasures are initiated. On the other hand, this window should be sufficiently large, such that the chance of a false alarm notification is minimized. A Mapping to Commitment Scheme [4],[5] for Selective Jamming attack prevention for countering selective jamming, the goal of this scheme is to transform a selective jammer to a random one. This can be achieved by overwhelming the adversary’s computational ability to perform real-time packet classification. Commitment schemes are fundamental cryptographic primitives that allow a committer P, commit to a value m to a verifier V while keeping m hidden. Initially, P provides V with a commitment C = commit(m, r), where commit is some commitment operation, and r is a random number. At a later stage, P can release additional information that reveals m. A scheme that does not allow the computation of m from C without additional information from P is called perfect or hiding, while a scheme that does not allow P to change m to a value m_ once C is released, is called binding. The role of the committer is assumed by the transmitting node S. The role of the verifier V is assumed by any receiver R within the communication range of S, including the jammer J. We now provide a scheme that prevents packet classification based on the idea of commitments. IV. PROPOSED ALGORITHM Algorithm for prevention of selective jamming attack by selecting packets at physical layer is using SHCS and add hiding layer between PHY and MAC layer.
Fig. 1: Header with various encryption algorithms on different layers
A Strong Hiding Commitment Scheme (SHCS) A strong hiding commitment scheme (SHCS) consider PHY and MAC layer [5], which is based on symmetric cryptography. Assume that the sender has a packet for Receiver. First, S constructs commit ( message ) C the commitment function is an offthe-shelf symmetric encryption algorithm is a publicly known permutation, and k is a randomly selected key of some desired key length s (the length of k is a security parameter). Upon reception of d, any receiver R computes. Hiding sublayer is inserted between PHY and MAC layer and storing key k with C || pad(C).The functions of hiding sublayer is shown in Fig.1. The hiding sublayer also perform permutation Π1 and Π2 at different processing stages[5].
All rights reserved by www.ijirst.org
166
Performance Evaluation of AODV, DSDV and DSR or Avoiding Selective Jamming Attacks in WLAN (IJIRST/ Volume 3 / Issue 02/ 030)
Steps of Proposed Anti-Jamming Algorithm Identification of Neighbor node Step 1: Create Topology for wireless network for node N. Step 2: Select center node as an access point- AP. Step 3: Set Range r1 as neighbor distance between AP and other node. Set Range r2 as a neighbor distance between node to node. Step 4: Calculate Euclidian distance-E1between neighboring node and create a list –L1of node based on E1. Step 5: Arrange L1 ascending order. Step 6: Identify Jammer node (Random method) Step 7: Assign Traffic Agent to Jammer node. Identify Peripheral Node with its neighbor Identify Mapper node for intermediate node to pass the massage. Anti-jamming method (To detect the Jammer node) Identify the Jammer and transmit the message to alternate route(Applying SHCS) Apply Encryption1 C=Ek1 (m) Apply permutation π2 (C||pad(C)||k) Apply Encryption2 Ek2 (π2(C||pad(C)||k)) And create hiding layer This will prevent Jammer node to jam network. V. PROPOSED SOLUTION A solution to selective jamming would be the encryption of transmitted packets (including headers) with a static key. However, for broadcast communications, this static decryption key must be known to all intended receivers and hence, is susceptible to compromise[5]. Moreover, even if the encryption key of a hiding scheme were to remain secret, the static portions of a transmitted packet could potentially lead to packet classification. TCP header is a most common part of the data packet. In a TCP header there are six reserved bits which remains always unused. In this paper we propose a new approach to enhance the security by using the six reserved bits of a TCP header. Real Time Packet Classification At the Physical layer, a packet m is encoded, interleaved, and modulated before it is transmitted over the wireless channel [5]. At the receiver, the signal is demodulated, de-interleaved and decoded to recover the original packet m. Nodes A and B communicate via a wireless link. Within the communication range of both A and B there is a jamming node J. When A transmits a packet m to B, node J classifies m by receiving only the first few bytes of m. J then corrupts m beyond recovery by interfering with its reception at B. In our proposed system we have proved that the open nature of the wireless medium leaves it vulnerable to intentional interference attacks, typically referred to as jamming. And also this intentional interference with wireless transmissions can be used as a launch pad for mounting Denial-of-Service attacks on wireless networks. We addressed the problem of selective jamming in wireless networks. We illustrated the effectiveness of selective jamming attacks by implementing such attacks against the TCP protocol. We showed that an adversary can exploit its knowledge of the protocol implementation to increase the impact of his attack at a significantly lower energy cost. We illustrated the feasibility of selective jamming attacks by performing real time packet classification. To mitigate selective jamming, we proposed several methods that combine cryptographic primitives such as commitment schemes, cryptographic puzzles, all-or-nothing transformations and MD5 algorithm with physical layer attributes as in Fig.1. VI. SIMULATION RESULT In NS2 Simulator [13], we tested various scenarios for 10,20,30,40 and 50 no of node with area of 1000 X 1000 m2 topology with fix locations of nodes. Route discovery protocol AODV, DSDV and DSR are used for communication between nodes. First without our proposed algorithm, selective jamming is applied and result is taken for 40 ms duration in NS2 simulator. In second scenario, our proposed algorithm for anti-jamming is applied to mitigate selective jamming and results are taken by analyzing packet delivery ratio in Fig.2 and Fig.3, packet delivery ratio in Fig.4 and Fig. 5, and end to end delay in Fig.6 and Fig.7 for 5,25 and 35 no of nodes by using xgraph. By seeing this results, we also check results for 55 no of nodes and get comparison for packet loss ration in Fig.8, packet delivery ratio in Fig.9 and end to end delay in Fig. 10. By seeing result we see the improvement in all matrices in terms of performance.
All rights reserved by www.ijirst.org
167
Performance Evaluation of AODV, DSDV and DSR or Avoiding Selective Jamming Attacks in WLAN (IJIRST/ Volume 3 / Issue 02/ 030)
Fig. 2: Packet Delivery Ratio by Proposed Anti-jamming algo for 50 nodes (AODV)
Fig. 3: Packet Delivery Ratio by Proposed Anti-jamming algo for 50 nodes (DSDV)
All rights reserved by www.ijirst.org
168
Performance Evaluation of AODV, DSDV and DSR or Avoiding Selective Jamming Attacks in WLAN (IJIRST/ Volume 3 / Issue 02/ 030)
Fig. 4: Packet Delivery Ratio by Proposed Anti-jamming algo for 50 nodes (DSR)
Fig. 5: Packet Loss Ratio by Proposed Anti-jamming algo for 50 nodes (AODV)
All rights reserved by www.ijirst.org
169
Performance Evaluation of AODV, DSDV and DSR or Avoiding Selective Jamming Attacks in WLAN (IJIRST/ Volume 3 / Issue 02/ 030)
Fig. 6: Packet Loss Ratio by Proposed Anti-jamming algo for 50 nodes (AODV)
Fig. 7: Packet Loss Ratio by Proposed Anti-jamming algo for 50 nodes (DSR)
All rights reserved by www.ijirst.org
170
Performance Evaluation of AODV, DSDV and DSR or Avoiding Selective Jamming Attacks in WLAN (IJIRST/ Volume 3 / Issue 02/ 030)
Fig. 8: Packet Loss Ratio by jamming algo for 50 nodes (AODV, DSDV, DSR)
Fig. 9: Packet Delivery Ratio by jamming algo for 50 nodes (AODV, DSDV, DSR)
All rights reserved by www.ijirst.org
171
Performance Evaluation of AODV, DSDV and DSR or Avoiding Selective Jamming Attacks in WLAN (IJIRST/ Volume 3 / Issue 02/ 030)
Fig. 10: Packet Loss Ratio by Proposed Anti-Jamming algo for 50 nodes (AODV,DSDV,DSR)
Fig. 11: End to End Delay by jamming algo for 50 nodes (AODV, DSDV, DSR)
All rights reserved by www.ijirst.org
172
Performance Evaluation of AODV, DSDV and DSR or Avoiding Selective Jamming Attacks in WLAN (IJIRST/ Volume 3 / Issue 02/ 030)
Fig. 12: End to End Delay by Proposed anti-jamming algo for 50 nodes (AODV, DSDV, DSR)
Fig. 13: Packet Delivery Ratio by Proposed Anti Jamming Algo for 50 nodes (AODV, DSDV, DSR)
All rights reserved by www.ijirst.org
173
Performance Evaluation of AODV, DSDV and DSR or Avoiding Selective Jamming Attacks in WLAN (IJIRST/ Volume 3 / Issue 02/ 030)
VII. CONCLUSION We analyze the problem of selective jamming attacks in wireless networks with different routing protocols AODV, DSDV and DSR. We tested the effectiveness of selective jamming attacks against the TCP protocol. We showed that an adversary can exploit its knowledge of the protocol implementation to increase the impact of the attack at a significantly lower energy cost. We illustrated the feasibility of selective jamming attacks by performing real time packet classification. To mitigate selective jamming, we proposed a method that combine cryptographic primitives such as commitment schemes (SHCS) and analyzes various parameters like PDR, PLR and End to End Delay for all three routing protocols AODV, DSDV and DSR and conclude that it improves performance in all three protocols. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18]
P.Rameshkumar, G.Nageshwarrao,P.Rambabbu, “Packet Classification Methods to counte r Jamming attacks in Adhoc Networks,” IJDCST, vol. 1, pp. 3136, Aug. 2013. Sisi Liu, Loukas Lazos, Marwan Krunz, “Thwarting Inside Jamming Attacks on Wireless Broadcast Communication,” ACM Trans. 978-4503-0693 ,2006 Jue hans, Fanggang wang, Tony Q.S. Qzek, “Jamming-Aided Secure Communication in Massive MIMO Rician Channels,” Proc. IEEE ITRANSACTIONS ON WIRELESS Communications, pp. 1-15, 2015. Pushphas Chaturvedi, Kunas Gupta, “Detection and Prevention of various types of Jamming Attacks in Wireless Networks” IRACST, vol. 3, no. 2, pp.7579, Aug. 2013. Alejandro Proan ̃o, Loukas Lazos, “Packet-Hiding Methods for Preventing Selective Jamming Attacks,”IEEE Transactions on Dependable And Secure Computing, VOL. 9, NO. 1,pp.101-114 ,Feb. 2012. Nand Dhandhukia, Dr. Kiran Parmar , “Effects of Jamming Attacks on Wireless Communication Systems, IJSRD, ,Vol 3,No.7,pp. 1-6, 212 O. Goldreich, Foundations of Cryptography: Basic Applications. Cambridge Univ. Press, 2004. IEEE, IEEE 802.11 Standard, http://standards.ieee.org/ getieee802/download/802.11-2007.pdf, 2007. Y.W. Law, M. Palaniswami, L.V. Hoesel, J. Doumen, P. Hartel, and P. Havinga, “Energy-Efficient Link-Layer Jamming Attacks against WSN MAC Protocols,” ACM Trans. Sensor Networks, vol. 5, no. 1, pp. 1-38, 2009. L. Lazos, S. Liu, and M. Krunz, “Mitigating Control-Channel Jamming Attacks in Multi-Channel Ad Hoc Networks,” Proc. Second ACM Conf. Wireless Network Security, pp. 169-180,2009. G. Lin and G. Noubir, “On Link Layer Denial of Service in Data Wireless LANs,” Wireless Comm. and Mobile Computing, vol. 5, no. 3, pp. 273-284, May 2004. Y. Liu, P. Ning, H. Dai, and A. Liu, “Randomized Differential DSSS: Jamming-Resistant Wireless Broadcast Communication,” Proc. IEEE INFOCOM, 2010. Ns2 Simulator http://www.isi.edu/nsnam/ns/ C. Perkins, E. Belding-Royer, and S. Das, “RFC 3561: Ad Hoc On-Demand Distance Vector (AODV) Routing,” Internet RFCs, 2003. D. Stinson, “Something about All or Nothing (Transforms),” Designs, Codes and Cryptography, vol. 22, no. 2, pp. 133-138, 2001. M. Strasser, C. Po¨pper, and S. _Capkun, “Efficient Uncoordinated fhss Anti-Jamming Communication,” Proc. ACM Int’l Symp. Mobile Ad Hoc Networking and Computing (MobiHoc), pp. 207-218, 2009. P. Tague, M. Li, and R. Poovendran, “Mitigation of Control Channel Jamming under Node Capture Attacks,” IEEE Trans. Mobile Computing, vol. 8, no. 9, pp. 1221-1234, Sept. 2009. B. Thapa, G. Noubir, R. Rajaramanand, and B. Sheng, “On the Robustness of IEEE802.11 Rate Adaptation Algorithms against Smart Jamming,” Proc. ACM Conf. Wireless Network Security (WiSec), 2011.
All rights reserved by www.ijirst.org
174