Detecting Selfish Behavior in a Cooperative Commons

Kim, Hyun Jin; Peha, Jon M.

doi:10.1109/dyspan.2008.22

Cited by 12 publications

(5 citation statements)

References 26 publications

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“…As with the cooperative commons discussed in Section III-A, the problem is compounded by the fact that devices may be amply rewarded for providing misinformation to neighbors [26], perhaps convincing those neighbors to switch to another band by falsely claiming that the primary system is active. If it is necessary that all devices must follow the same cooperative algorithms, then someone must define those algorithms, enforce them on all secondary devices deployed in the band, and handle violations.…”

Section: Sharing Among Equal Secondaries Devicesmentioning

confidence: 99%

“…When devices delay their own transmissions for another, or carry each other's traffic, some altruism is required, e.g., one device might increase delays for its own traffic and drain its own battery by transmitting a stranger's packet. For example, we have shown that devices can manipulate today's routing protocols to avoid carrying traffic for other devices, thereby improving their own performance, and it is only possible to detect such behavior with nonstandard protocol modifications [26]. Even worse, a malicious node may take deliberate steps to disrupt the network, and in some proposed cooperative schemes, the impact of malicious behavior could be great.…”

Section: A Sharing Among Equal Primary Devicesmentioning

confidence: 99%

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Sharing Spectrum Through Spectrum Policy Reform and Cognitive Radio

2009

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| Traditionally, interference protection is guaranteed through a policy of spectrum licensing, whereby wireless systems get exclusive access to spectrum. This is an effective way to prevent interference, but it leads to highly inefficient use of spectrum. Cognitive radio along with software radio, spectrum sensors, mesh networks, and other emerging technologies can facilitate new forms of spectrum sharing that greatly improve spectral efficiency and alleviate scarcity, if policies are in place that support these forms of sharing. On the other hand, new technology that is inconsistent with spectrum policy will have little impact. This paper discusses policies that can enable or facilitate use of many spectrum-sharing arrangements, where the arrangements are categorized as being based on coexistence or cooperation and as sharing among equals or primary-secondary sharing. A shared spectrum band may be managed directly by the regulator, or this responsibility may be delegated in large part to a license-holder. The type of sharing arrangement and the entity that manages it have a great impact on which technical approaches are viable and effective. The most efficient and cost-effective form of spectrum sharing will depend on the type of systems involved, where systems under current consideration are as diverse as television broadcasters, cellular carriers, public safety systems, point-to-point links, and personal and local-area networks. In addition, while cognitive radio offers policy-makers the opportunity to improve spectral efficiency, cognitive radio also provides new challenges for policy enforcement. A responsible regulator will not allow a device into the marketplace that might harm other systems. Thus, designers must seek innovative ways to assure regulators that new devices will comply with policy requirements and will not cause harmful interference.

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Section: Sharing Among Equal Secondaries Devicesmentioning

confidence: 99%

Section: A Sharing Among Equal Primary Devicesmentioning

confidence: 99%

Sharing Spectrum Through Spectrum Policy Reform and Cognitive Radio

2009

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“…In the RREP header, in addition to these two, another field called next_to_destination is added to indicate the node to which the packet is to be forwarded in the reverse path. With these additional fields, it is possible to detect every instance of selfish behavior in a wireless network, if the following conditions are satisfied: (i) no packet is lost due to interference, (ii) links are bi-directional, (iii) the nodes are stationary, and (iv) queuing delays are bounded [13]. The robust clustering and monitoring with additional fields substantially increase the detection as evident from the results.…”

Section: The Detection Algorithmmentioning

confidence: 92%

A Trust-Based Detection Algorithm of Selfish Packet Dropping Nodes in a Peer-to-Peer Wireless Mesh Network

Sen

2010

Recent Trends in Network Security and Applications

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Abstract. Wireless mesh networks (WMNs) are evolving as a key technology for next-generation wireless networks showing raid progress and numerous applications. These networks have the potential to provide robust and highthroughput data delivery to wireless users. In a WMN, high speed routers equipped with advanced antennas, communicate with each other in a multi-hop fashion over wireless channels and form a broadband backhaul. However, the throughput of a WMN may be severely degraded due to presence of some selfish routers that avoid forwarding packets for other nodes even as they send their own traffic through the network. This paper presents an algorithm for detection of selfish nodes in a WMN that uses statistical theory of inference for reliable clustering of the nodes based on local observations. Simulation results show that the algorithm has a high detection rate and a low false positive rate.

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“…In the header of an RREQ packet, in addition to the above two fields, another field called next_to_destination is added to indicate the address of the node to which the packet must be forwarded in the reverse path. It has been shown in (Kim et al, 2008), with the above extra fields, it is possible to detect every instance of selfish behavior in a wireless network with 100% detection accuracy, if the following conditions are satisfied: (i) no packet loss lost due to interference, (ii) links are bi-directional, (iii) the nodes are stationary, and (iv) the queuing delays are bounded. Since all these conditions cannot be guaranteed in a realworld deployment, there will be always some detection inaccuracy.…”

Section: A Trust-based Protocol For Selfish Nodes Detection In Wmnsmentioning

confidence: 99%

Secure Routing in Wireless Mesh Networks

Sen¹

2011

Wireless Mesh Networks

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Physical layer attacksThe physical layer is responsible for frequency selection, carrier frequency generation, signal detection, modulation, and data encryption. As with any radio-based medium, the possibility of jamming attacks in this layer of WMNs is always there. Jamming is a type of attack which interferes with the radio frequencies that the nodes use in a WMN for communication (Shi et al., 2004). A jamming source may be powerful enough to disrupt communication in the entire network. Even with less powerful jamming sources, an adversary can potentially disrupt communication in the entire network by strategically distributing the jamming sources. An intermittent jamming source may also prove detrimental as some communications in WMNs may be time-sensitive. More complex forms of radio jamming attacks have been studied in (Xu et al., 2005), where the attacking devices do not obey the MAC layer protocols. MAC layer attacksDifferent types of attacks are possible in the MAC layer of a WMN. Some of the major attacks at this layer are: passive eavesdropping, jamming, MAC address spoofing, replay, unfairness in allocation, pre-computation and partial matching etc. These attacks are briefly described in this subsection. i. Passive eavesdropping: the broadcast nature of transmission of the wireless networks makes these networks prone to passive eavesdropping by the external attackers within the transmission range of the communicating nodes. Multi-hop wireless networks like WMNs are also prone to internal eavesdropping by the intermediate hops, whereby a malicious intermediate node may keep the copy of all the data that it forwards without the knowledge of any other nodes in the network. Although passive eavesdropping does not affect the network functionality directly, it leads to the compromise in data confidentiality and data integrity. Data encryption is generally employed using strong encryption keys to protect the confidentiality and integrity of data. ii. Link layer jamming attack: link layer attacks are more complex compared to blind physical layer jamming attacks. Rather than transmitting random bits constantly, the attacker may transmit regular MAC frame headers (no payload) on the transmission channel which conforms to the MAC protocol being used in the victim network (Law et al., 2005). Consequently, the legitimate nodes always find the channel busy and back off for a random period of time before sensing the channel again. This leads to the denialof-service for the legitimate nodes and also enables the jamming node to conserve its energy. In addition to the MAC layer, jamming can also be used to exploit the network and transport layer protocols (Brown et al., 2006). Intelligent jamming is not a purely transmit activity. Sophisticated sensors are deployed, which detect and identify victim network activity, with a particular focus on the semantics of higher-layer protocols (e.g., AODV and TCP). Based on the observations of the sensors, the attackers can exploit the predictable timing behavior exhibited by highe...

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Detecting Selfish Behavior in a Cooperative Commons

Cited by 12 publications

References 26 publications

Sharing Spectrum Through Spectrum Policy Reform and Cognitive Radio

Sharing Spectrum Through Spectrum Policy Reform and Cognitive Radio

A Trust-Based Detection Algorithm of Selfish Packet Dropping Nodes in a Peer-to-Peer Wireless Mesh Network

Secure Routing in Wireless Mesh Networks

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