Open Access

Minimizing Detection Probability Routing in Ad Hoc Networks Using Directional Antennas

  • Xiaofeng Lu1Email author,
  • Don Towsley2,
  • Pietro Lio'3,
  • Fletcher Wicker4 and
  • Zhang Xiong1
EURASIP Journal on Wireless Communications and Networking20092009:256714

https://doi.org/10.1155/2009/256714

Received: 31 January 2009

Accepted: 3 May 2009

Published: 8 June 2009

Abstract

In a hostile environment, it is important for a transmitter to make its wireless transmission invisible to adversaries because an adversary can detect the transmitter if the received power at its antennas is strong enough. This paper defines a detection probability model to compute the level of a transmitter being detected by a detection system at arbitrary location around the transmitter. Our study proves that the probability of detecting a directional antenna is much lower than that of detecting an omnidirectional antenna if both the directional and omnidirectional antennas provide the same Effective Isotropic Radiated Power (EIRP) in the direction of the receiver. We propose a Minimizing Detection Probability (MinDP) routing algorithm to find a secure routing path in ad hoc networks where nodes employ directional antennas to transmit data to decrease the probability of being detected by adversaries. Our study shows that the MinDP routing algorithm can reduce the total detection probability of deliveries from the source to the destination by over 74%.

1. Introduction

In a wireless network, nodes communicate with others through shared wireless medium, which makes the communications more susceptible to passive eavesdropping and malicious traffic analysis [1]. An adversary may eavesdrop network in order to discover the location of the transmitter. These adversaries are referred as detection systems. If the power received by a detection system is strong enough, the detection system can distinguish the transmission signals from the electromagnetic noise, and it becomes aware of the existence of a transmitter. If more than two detection systems detect a transmitter in a synchronous manner, they are able to compute the transmitter's position with localization algorithms and go to find the transmitter and catch it. Hence, transmission with low detection probability is very important in an untrustworthy network.

Typically, the assumption for ad hoc networks is that nodes are equipped with omnidirectional antennas, which can transmit and receive signals in all horizontal directions [2, 3]. However, a directional antenna can get antenna gain in the main lobe direction, thus transmitters can use the directional antenna to transmit signals farther away than omnidirectional antennas with the same transmit power, or transmit signals to a receiver while using less transmit power [2, 4].

The work in [58] mentioned that directional antennas can reduce the detection probability, but no study has been conducted to compare the detection probability of directional and omnidirectional antennas. On the other hand, using directional antennas to achieve secure routing has not been studied yet.

Researchers in the past have done much fundamental research on directional antennas in wireless networks that focused on medium-access control, spatial reuse, efficient power consumption, network capacity, and so forth. The work in [913] proposed adaptive Medium-Access Control (MAC) protocols to improve IEEE 802.11. These adaptive MAC protocols attempted to limit the disadvantages of IEEE 802.11 in spatial use. Power is another constrained source in some ad hoc network scenarios because in these cases the power for the antenna comes from batteries, which are energy-constrained. Sometimes, nodes equipped with batteries-powered antennas cannot recharge frequently. This is another reason for using directional antennas. Authors of [14, 15] described the advantages of using directional antennas to reduce power consumption in ad hoc networks. As directional antennas can increase spatial use [16], more than one directional antenna can send data at the same time. Directional antennas can also increase network capacity [17, 18].

In this paper, we address the work we have done on routing path selection to reduce the transmitter's probability of being detected by adversaries in ad hoc networks. This paper is organized as follows. Section 2 introduces the antenna model. We introduce the detection probability model in Section 3 and our minimizing detection probability routing algorithm in Section 4. In Section 5, we review some related work about anonymous routing and secure routing protocols. Finally, we conclude our work in Section 6.

2. Antenna Model

Antennas are either omnidirectional mode or directional mode [2, 3]. Omnidirectional antennas cover 360 degrees and send data in all directions. All nodes in the radiation region can receive the communication signals [2, 3]. Omnidirectional antennas spread the electromagnetic energy over a large region, while only small portion is received by the desired receivers, so the omnidirectional transmissions waste a large portion of the transmit power and the network capacity.

Directional transmission can overcome this disadvantage. A directional antenna can form a directional beam pointing at the receiver by concentrating its transmit power into that direction. By pointing the main lobe at the receiver, a directional antenna can get more antenna gain in the direction of the receiver. Directional antennas strongly reduce signal interference in unnecessary directions.

In our antenna model, we assume that an antenna can work in two modes: omnidirectional mode and directional mode. It can send and receive data in both these two modes [2]. If nodes have nothing to transmit, their antennas work in omnidirectional mode to detect signals. A receiver and a transmitter can communicate over a larger distance when both antennas are in directional mode than just one of them is in directional mode while another is in omnidirectional mode.

Effective Isotropic Radiated Power (EIRP) is the gain of a transmitting antenna multiplied by the net power accepted by the antenna from the connected transmitter in a given direction [19]. As the gain and received power are measured in dB, EIRP can be calculated as
(1)

where is the transmit power in dBW, and is the antenna gain in dBi ( ).

Antenna gain refers to an antenna's ability to direct its radiated power in a desired direction, or to receive energy preferentially from a desired direction [4]. It is defined as the ratio of the radiation intensity of an antenna in a given direction to the intensity of the same antenna as it radiates in all directions (isotropically) and has no losses [20]. Antenna gain is expressed in dBi.

For an omnidirectional antenna, because the ratio of the radiation intensity is 1, the antenna gain is . As a directional antenna concentrates the transmit power into the main lobe direction, the radiation intensity in the main lobe direction is larger than that in other directions and its in that direction is much larger than zero. Therefore, the directional antenna can provide the same EIRP in the main lobe direction as that an omnidirectional antenna provides while using much less transmit power than that the omni-direction antennas uses.

No directional antenna is able to radiate all of its energy in one preferred direction. Some is inevitably radiated in other directions. These smaller peaks in Figure 1(b) are referred to as side lobes, commonly specified in dBi down from the main lobe. Figure 2 shows a case directional antenna gain in main lobe, side lobes, and back lobe.
Figure 1

Transmission region of omnidirectional antenna and directional antenna.

Figure 2

A directional antenna gain function.

As different antennas have different antenna structures and physical characteristic, their antenna gain functions are different. We use an approximate gain function to fit the directional antenna gain function. This approximate gain function is showed in Figure 3.
Figure 3

An approximate directional antenna gain function.

3. Detection Probability Model

3.1. Link Budget Equation

If the power received by a detection system is strong enough, the detection system can distinguish the transmission signals from electromagnetic noise. The ratio of the total received signal power to the total noise which includes thermal and system noise plus total interference is denoted as SNIR [21]. Hence, the detection event occurs if and only if the SNIR is larger than a threshold at a detection system.

The equation to compute the total received signal level at the receiver antenna is the following [22]:

(2)

where is the transmitter's power level, is the transmitter's antenna gain in the direction towards the receiver, is the receiver's antenna gain in the direction of the transmitter, is the transmitter's cable attenuation, is the receiver's cable attenuation, and is adaptive transmission path loss, which we will discuss carefully later. and are assumed to be zero here.

The total noise level at the receiving unit is

(3)

where is Boltzmann constant equal to −228.6 dB(Watts/ (Hertz * Degree Kelvin). is noise temperature at the receiver's antenna and is environment noise temperature at the receiver's antenna [22]. The receiving bandwidth is of course matched to communication signal's bandwidth BW. The final term is the total interference power level. The impact of interference is assumed to be zero in our study.

Free-space path loss (FSPL) is the loss in signal strength of an electromagnetic wave that would result from a line of sight path through free space, with no obstacles nearby to cause reflection or diffraction [23]. This loss is calculated using the following formula:

(4)
where is the distance from the transmitter to the receiver, the radio frequency is , and is a constant that depends of the units of measure for and . With the units of measure for and listed in Table 1, .
Table 1

Variable definitions for link budget equations.

Symbol

Meaning

Value

Units

Transmitter power level

dBW

Transmit antenna gain in the direction of the hostile antenna

Figure 3

dB

Radio frequency

2500

MHz

Distance between the transmitter and hostile node

Calculated

M

Receiver antenna gain in the direction of the transmit antenna

0

dB

Total received signal level after receive antenna

Equation (2)

dBW

BW

Hostile receiver's Bandwidth

1000000

Hertz

Noise temperature of hostile antenna

500

Degrees Kelvin

Environment noise temperature at hostile antenna

300

Degrees Kelvin

Total system noise temperature at hostile antenna

Degrees Kelvin

Total noise level in signal bandwidth at hostile antenna

Equation (3)

dB Watts

Past line of sight, communications is still possible, but there is additional attenuation due to shadowing. Additionally it is well know that the average receive power level, measured in dBW, around a circle at a constant distance from the transmitter and beyond the line of sight is a lognormally distributed random variable. Let be the path loss when the distance from the receiver to the transmitter is larger than the line of sight distance. We modify the FSPL formula and propose an adaptive path loss formula:
(5)

where is determined by the terrain type.

In our analysis, the coefficient is a random variable that depends of the type of terrain, that is, how rugged the terrain is to radio frequency waves. Typical terrain types include open rural, rural trees and rolling hills, suburban, and urban. For each of the terrain types there is an average distance to the edge of the unobstructed line of sight given. Beyond this limit, the value of is drawn uniformly random between the values listed in Table 2 with the possibility that there are locations that have direct line of sight beyond this average.
Table 2

Terrain type parameters.

Terrain type

Distance to horizon ( )

Range of

Rural-open

1000

2 to 2.5

Rural-trees

300

2 to 4.0

Suburban

200

2 to 5.0

Urban

100

2 to 6.0

3.2. Detection Probability Model

Now we study the issue of the probability that a detection system detects a transmitter. Let the direction of the directional antenna's peak radiation intensity lie on the positive axis and the star node be a detection system in Figure 4. The distance from the transmitter to the detection system is and the angle between the direction of the detection system and the direction of the positive axis is . We will use and in the following sections of this paper with the same meanings defined here. We assume that the detection system's antenna works in omnidirectional mode.
Figure 4

Illustration of and .

The detection event occurs at a detection system if and only if the SNIR is larger than the threshold :

,

(6)

Substitute (2), (3), and (5) into (6).

(7)
where is the transmitter's antenna gain function as Figure 3 shows, and . As , , , and are constants, let
(8)

Substitute (8) into the definition of the SNIR, the probability of the detection event occuring is

(9)

Now we discuss the value of , for each of the terrain types listed in Table 1, there is an average distance to the edge of the unobstructed line of sight given, which we defined as . When the distance is smaller than , we set equal to 2. If the distance to the transmitter is greater than , the value of is a random variable between the values listed in Table 1:

(10)

where is given by (8).

3.3. Model Analysis

Assume both the directional and omnidirectional antennas provide the same EIRP in the direction of the receiver. Assume that the omnidirectional antenna's transmit power is 3 watt and the directional antenna's gain function is as Figure 3 shows, so the directional antenna's transmit power is 0.03 watt. We assume that the operational area is a finite area 100 kilometers 100 kilometers and the terrain is rural-open. We place the transmitter at the center of the operational area.

Figure 5 shows the detection probability map of an omnidirectional antenna in the operational area. In this figure, different colors mean different probability values. As omnidirectional antennas radiate signals in all directions equally, the contour lines are almost circles in Figure 5. The detection probability becomes lower and lower with the increase of the distance . Figure 6 shows the detection probability map of a directional antenna. Only locations in the main lobe direction of the directional antenna have high probabilities to detect the transmitter, the detection probabilities at other directions are very low.
Figure 5

An omnidirectional antenna's detection probability map.

Figure 6

A directional antenna's detection probability map.

Let be a partition of the operational area . Assume that there is only one detection system that is in one of . According to the total probability theorem, the probability of detecting the transmitter is

(11)
where is the probability of the detection system being in region . We assume that the probability of the detection system being in are even, . Then the probability of detecting the transmitter is
(12)

Here we assume that each is which is a small region for directional transmissions. Normally, if two locations are very near, the detection probabilities at these two locations should be almost equal, so we can assume to be the detection probability at the center of . Using equation (10), we can calculate the probability of detecting a transmitter at the center of .

The dp of Figure 5 is 0.36 and dp of Figure 6 is 0.012. This indicates that directional antennas can reduce the detection probability by over 96.7%. Comparing these two figures, we can find that the area where the detection probability being zero in Figure 6 is much larger than that in Figure 5 and the colorful area where the detection probabilities being larger than 0.1 in Figure 6 is much less than that area in Figure 5. This can explain why a directional antenna has the lower detection probability than an omnidirectional antenna if they provide the same EIRP in the direction of receiver.

4. Minimizing Detection Probability Routing Algorithm

4.1. Definition

We model adversaries as passive. Adversaries in this model are assumed to be able to receive any transmitter's signals but are not able to modify these signals. If a set of adversaries detect a transmitter in a synchronous manner, they may be able to compute the transmitter's position with localization algorithms. It is dangerous to reveal the position information to adversaries, because adversaries may find the transmitter and catch it according to its position.

As directional antennas can transmit signals towards a specific direction, we can employ several directional antennas as relays to bypass a detection system. In Figure 7, node , , and are three network nodes and the black node is a detection system. Assume that node wants to send data to node . If node transmits data to node directly using directional antenna, as the detection system happens to lie in main lobe direction of node , it can detect node with 100% probability. Or, node can send data to node via node as Figure 7(b) shows. As the detection system is not in the main lobe direction of these two directional antennas, the probability of detecting the transmissions at the detection system is very low as Figure 6 indicates.
Figure 7

An illustration of using directional antennas to bypass a detection system.

Figure 8

An illustration of anonymous routing using directional antennas.

Assume detection systems and network nodes are scattered within the operational area. To make the relay transmission from the source to the destination more secure, the strategy of our routing algorithm is to Minimize Detection Probability (MinDP) by selecting a routing path with the lowest detection probability rather than the shortest distance or the least power consumption. In Figure (8), the relay transmission path ( ) is more secure than the path ( ). If network nodes know the locations of detection systems, they can use equation (10) to calculate the detection probability. If network nodes do not know the locations of detection systems, they can use equation (12) to calculate the detection probability.

The goal of our routing protocol is to find a secure routing path which has the lowest detection probability throughout the whole delivery process from the source to the destination. Assume that a packet would be delivered from the source to the destination through hops. If any of these hops deliveries is detected by a detection system, the detection event occurs. Let TDP be the total detection probability from the source to the destination

(13)

where is the probability of the hop delivery being detected by all detection systems.

Some assumptions for this routing algorithm are as follows.
  1. (1)

    Assume that there are network nodes and all of them employ directional antennas to transmit data.

     
  2. (2)

    The transmit power of a transmitter varies based on the distance from the transmitter to the receiver and the transmit rate.

     

The formal definition of MinDP routing algorithm is shown in Algorithm 1.

Algorithm 1:

Let note the selected path and save all possible routing paths

for to

for to

if

Calculate

end if

end for

end for

/*Generate all available routing paths and save routing paths to A is nodes

sequence like */

GeneratePath

while

/*Calculate the total detection probability (TDP) of */

if then

end if

DeletePath(AvailablePath,path)

/*delete path from AvailablePath*/

end while

PATH is the selected routing path

4.2. Evaluation

Assume the experimental area is 100 km 100 km and detection systems and network nodes are scattered within the operational area randomly. We compare the total detection probability of MinDP routing algorithm using directional antennas with that of shortest path rouging using omnidirectional antennas. We randomly select two nodes as the source and the destination of each routing.

Figure 9 shows the TDP function of hops. In this figure, the TDP of Shortest path routing using omni-direction antennas increases rapidly, while the TDP of MinDP routing algorithm increases adagio. In a scenario where the number of detection systems is given, the TDP of Shortest path routing is much higher than that of MinDP routing algorithm. It is reasonable that the more detection systems are within the experiment area, the higher total detection probability is. We can know from this figure that the transmission from the source to the destination using omni-directional antennas will be detected by detection systems definitely when the number of detection systems is larger than 3 and the number of hops is larger than 2. The average TDP of Shortest path routing is 0.953 and the average TDP of MinDP routing algorithm is 0.244. Hence, the MinDP routing algorithm using directional antennas can reduce the total detection probability by over 74%.
Figure 9

Total detection probability function of hops.

5. Related Work

Many protocols have been proposed to provide anonymity in Internet, such as Crowds [24], Onion [25]. For ad hoc networks, although a number of papers about secure routing have been proposed, such as SEAD [26], ARAN [27], AODV-S [28], only a few papers are about anonymous routing issue and few of them talk about directional antennas and locations .

Zhu et al. proposed a secure routing protocol ASR for MANET [29] to realize anonymous data transmission. ASR makes sure that adversaries are not able to know the source and the destination from data packets. ASR considers the anonymity of addresses of the source and the destination in a packet but not the physical location of the source. In ASR, their solution make use of the shared secrets between any two consecutive nodes. The goal of ASR is to hide the source and destination information from data packets but not to protect the transmission from being detected by hostile detection systems.

ANODR is an secure protocol for mobile Ad hoc networks to provide route anonymity and location privacy [30]. For route anonymity, ANODR prevents strong adversaries from tracing a packet flow back to its source or destination; for location privacy, ANODR ensures that adversaries cannot discover the real identities of local transmitters. However, the location privacy ANODR provides is the identity of sender, not the physical location privacy.

Zhang et al. proposed an anonymous on-demand routing protocol, MASK, for MANET [31]. In MASK, nodes authenticate their neighboring nodes without revealing their identities to establish pairwise secret keys. By utilizing the secret keys, MASK achieves routing and forwarding task without disclosing the identities of participating nodes.

Most secure routing protocols and anonymous routing protocols employ authentication and secret key approaches to ensure the security. In a real wireless network, there is no clear transmission range, hostile detection systems can detect the transmitter's signals even if it is very far away from the transmitter. In this scenario, the detection system does not need to pass the authentication, they just detect signals. Hence, authentication cannot thwart hostile detection.

6. Conclusions

In an untrustworthy network, it is very important for the transmitter to avoid being detected by adversaries. In this paper, we propose a detection probability model to calculate the probability of detecting a transmitter at any location around the transmitter. Since signals from omnidirectional antennas are radiated in all directions, hostile nodes at any location can receive these electromagnetic waves, they have probabilities to tell signals from noises. A directional antenna could form a directional beam pointing to the receiver, and only nodes in the main lobe beam region can receive signals well. If a directional antenna employs less transmit power than an omnidirectional antenna but provides the same EIRP to the receiver, the directional antenna can reduce the detection probability by over 96.7%. Therefore, we prefer to employ directional antennas to relay data from the source to the destination. Minimizing Detection Probability (MinDP) routing algorithm we proposed can select a routing path that has the lowest total detection probability. The simulation results show that the MinDP routing algorithm can reduce the TDP by over 74% so as to provide high security and concealment for transmitters.

Declarations

Acknowledgments

We would like to gratefully acknowledge ITA Project. Our research was sponsored by the US Army Research Laboratory and the U.K. Ministry of Defence.

Authors’ Affiliations

(1)
School of Computer Science, Beijing University of Aeronautics and Astronautics
(2)
Department of Computer Science, University of Massachusetts at Amherst
(3)
Computer Laboratory, University of Cambridge
(4)
Communication Network Architectures Subdivision, The Aerospace Corporation

References

  1. Raymond J-F: Traffic analysis: protocols, attacks, design issues, and open problems. In Designing Privacy Enhancing Technologies, Lecture Notes in Computer Science. Edited by: Federath H. Springer, Berlin, Germany; 2001.Google Scholar
  2. Stimson GW: Introduction to Airborne Radar. SciTech, Raleigh, NC, USA; 1998.View ArticleGoogle Scholar
  3. Rappaport TS: Wireless Communications: Principles and Practice. Prentice-Hall, Upper Saddle River, NJ, USA; 1996.Google Scholar
  4. Hill JE: Gain of Directional Antennas. Watkins-Johnson Company, Tech-notes,1976Google Scholar
  5. Huang Z, Shen C-C: A comparison study of omnidirectional and directional MAC protocols for ad hoc networks. Proceedings of the IEEE Global Telecommunications Conference (GLOBECOM '02), November 2002, Taipei, Taiwan 1: 57-61.Google Scholar
  6. Spyropoulos A, Raghavendra CS: Energy efficient communications in ad hoc networks using directional antennas. Proceedings of the 21st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '02), June 2002, New York, NY, USA 1: 220-228.Google Scholar
  7. Steenstrup ME: Neighbor discovery among mobile nodes equipped with smart antennas. Proceedings of the Swedish Workshop on Wireless Ad-Hoc Networks (ADHOC '03), 2003Google Scholar
  8. Zhang Z: Pure directional transmission and reception algorithms in wireless ad hoc networks with directional antennas. Proceedings of the IEEE International Conference on Communications (ICC '05), May 2005, Seoul, Korea 5: 3386-3390.Google Scholar
  9. Nasipuri A, Ye S, You J, Hiromoto RE: A MAC protocol for mobile ad hoc networks using directional antennas. Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC '00), September 2000, Chicago, Ill, USA 1214-1219.Google Scholar
  10. Ko Y-B, Shankarkumar V, Vaidya NH: Medium access control protocols using directional antennas in ad hoc networks. Proceedings of the 19th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '00), March 2000, Tel Aviv, Israel 1: 13-21.Google Scholar
  11. Takai M, Martin J, Ren A, Bagrodia R: Directional virtual carrier sensing for directional antennas in mobile ad hoc networks. Proceedings of the 3rd ACM International Symposium on Mobile Ad Hoc Networking & Computing (MobiHoc '02), June 2002, Lausanne, Switzerland 183-193.View ArticleGoogle Scholar
  12. Bao L, Garcia-Luna-Aceves JJ: Transmission scheduling in ad hoc networks with directional antennas. Proceedings of the 8th Annual International Conference on Mobile Computing and Networking (MOBICOM '02), September 2002, Atlanta, Ga, USA 48-58.View ArticleGoogle Scholar
  13. Choudhury RR, Yang X, Ramanathan R, Vaidya NH: Using directional antennas for medium access control in ad hoc networks. Proceedings of the 8th Annual International Conference on Mobile Computing and Networking (MOBICOM '02), September 2002, Atlanta, Ga, USA 59-70.View ArticleGoogle Scholar
  14. Spyropoulos A, Raghavendra CS: Energy efficient communications in ad hoc networks using directional antennas. Proceedings of the 21st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '02), June 2002, New York, NY, USA 1: 220-228.Google Scholar
  15. Nasipuri A, Li K, Sappidi UR: Power consumption and throughput in mobile ad hoc networks using directional antennas. Proceedings of the 11th International Conference on Computer Communications and Networks (IC3N '02), October 2002Google Scholar
  16. Ramanathan R, Redi J, Santivanez C, Wiggins D, Polit S: Ad hoc networking with directional antennas: a complete system solution. IEEE Journal on Selected Areas in Communications 2005, 23(3):496-506.View ArticleGoogle Scholar
  17. Yi S, Pei Y, Kalyanaraman S: On the capacity improvement of ad hoc wireless networks using directional antennas. Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc '03), June 2003, Annapolis, Md, USA 108-116.View ArticleGoogle Scholar
  18. Liu B, Liu Z, Towsley D: On the capacity of hybrid wireless networks. Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '03), March-April 2003, San Francisco, Calif, USA 2: 1543-1552.Google Scholar
  19. IEEE Std : 100 The Authoritative Dictionary of IEEE Standards Terms. 7th edition. The Institute of Electrical and Electronics Engineers, New York, NY, USA; 2000.Google Scholar
  20. Balanis C: Antenna Theory. 3rd edition. John Wiley & Sons, New York, NY, USA; 2005.Google Scholar
  21. Breed G: Bit error rate: fundamental concepts and measurement issues. High Frequency Electronics 2003, 2(1):46-47.Google Scholar
  22. Breeze Wireless Communications Ltd Radio Signal Propagation, http://www.breezecom.com
  23. Federal Standard 1037C : Telecommunications: Glossary of Telecommunication Terms. National Communication System Technology & Standards Division, 1991Google Scholar
  24. Reiter MK, Rubin AD: Crowds: anonymity for web transactions. Communications of the ACM 1999, 42(2):32-48. 10.1145/293411.293778View ArticleGoogle Scholar
  25. Reed MG, Syverson PF, Goldschlag DM: Anonymous connections and onion routing. IEEE Journal on Selected Areas in Communications 1998, 16(4):482-493. 10.1109/49.668972View ArticleGoogle Scholar
  26. Hu Y-C, Perrig A, Johnson DB: Ariadne: a secure on-demand routing protocol for ad hoc networks. Proceedings of the 8th Annual International Conference on Mobile Computing and Networking (MobiHoc '02), September 2002, Atlanta, Ga, USA 12-23.View ArticleGoogle Scholar
  27. Sanzgiri K, Dahill B, Levine BN, Shields C, Belding-Royer EM: A secure routing protocol for ad hoc networks. Proceedings of the 10th IEEE International Conference on Network Protocols (ICNP '02), November 2002, Paris, FranceGoogle Scholar
  28. Yang H, Meng X, Lu S: Self-organized network-layer security in mobile ad hoc networks. Proceedings of the ACM Workshop on Wireless Security, September 2002, Atlanta, Ga, USA 11-20.View ArticleGoogle Scholar
  29. Zhu B, Wan Z, Kankanhalli MS, Bao F, Deng RH: Anonymous secure routing in mobile ad-hoc networks. Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks (LCN '04), November 2004, Tampa, Fla, USA 102-108.View ArticleGoogle Scholar
  30. Kong J, Hong X: ANODR: anonymous on demand routing with untraceable routes for mobile ad-hoc networks. Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc '03), June 2003, Annapolis, Md, USA 291-302.View ArticleGoogle Scholar
  31. Zhang Y, Liu W, Lou W: Anonymous communications in mobile ad hoc networks. Proceedings of the 24th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '05), March 2005, Miami, Fla, USA 3: 1940-1951.View ArticleGoogle Scholar

Copyright

© Xiaofeng Lu et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.