Source anonymity in WSNs against global adversary based on low rate fake injections

Bushang, Anas; Abuzneid, Abdelshakour; Mahmood, Ausif

doi:10.1109/ropaces.2016.7465306

Cited by 5 publications

(9 citation statements)

References 4 publications

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“…DUD [55,56] divides the time into intervals that have the exact duration, and it uses the same transmission rate for both real and dummy packets. A random number is thrown between 0 and 1.…”

Section: Dummy Uniform Distribution (Dud)mentioning

confidence: 99%

“…It is solved by increasing the transmitting rate, but this causes higher overhead as the network transmits more dummy packets. This relationship is considered as a trade-off between overhead and latency [55,56].…”

Section: Dummy Uniform Distribution (Dud)mentioning

confidence: 99%

“…DAD [55,56] technique is based on DUD. However, it gives the nodes that have real packets an advantage over other nodes in the network by increasing their transmuting rate by a specific value x.…”

Section: Dummy Adaptive Distribution (Dad)mentioning

confidence: 99%

“…However, increasing the transmitting rate could lead the adversary to be notified that a real event is being transmitted by implementing a time correlation attack. Therefore, nodes that have real packets need to decrease their original transmitting rate by the same specific value x after sending all real packets in their buffers to balance the transmitting rate and make its average equal to other nodes [55,56].…”

Section: Dummy Adaptive Distribution (Dad)mentioning

confidence: 99%

“…CAD [55,56] is based on DAD and DUD. It is developed to guarantee the maximum delay of a real event.…”

Section: Controlled Dummy Adaptive Distribution (Cad)mentioning

confidence: 99%

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Source Anonymity against Global Adversary in WSNs Using Dummy Packet Injections: A Survey

2018

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Source anonymity in wireless sensor networks (WSNs) becomes a real concern in several applications such as tracking and monitoring. A global adversary that has sophisticated resources, high computation and full view of the network is an obvious threat to such applications. The network and applications need to be protected and secured to provide the expected outcome. Source anonymity is one of the fundamental WSNs security issues. It is all about preventing the adversary from reaching the origin by analyzing the traffic of the network. There are many methods to provide source anonymity, which is also known as Source Location Privacy (SLP). One of these methods is based on dummy packets. The basic notion is to inject the network with dummy packets to confuse the adversary about the location of the transmitting source node. This paper provides a survey of protocols for anonymity that use dummy packet injections. We discuss each technique from the point of their advantages and disadvantages. Further, We provide a comparison for the most promising techniques provided in the literature which use dummy packet injections. A comparison for the adversary assumptions and capabilities will be provided as well.

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Section: Dummy Uniform Distribution (Dud)mentioning

confidence: 99%

Section: Dummy Uniform Distribution (Dud)mentioning

confidence: 99%

Section: Dummy Adaptive Distribution (Dad)mentioning

confidence: 99%

Section: Dummy Adaptive Distribution (Dad)mentioning

confidence: 99%

“…CAD [55,56] is based on DAD and DUD. It is developed to guarantee the maximum delay of a real event.…”

Section: Controlled Dummy Adaptive Distribution (Cad)mentioning

confidence: 99%