Bayesian mechanisms for wireless network security

Chorppath, Anil Kumar; Alpcan, Tansu; Boche, Holger

doi:10.1109/icc.2014.6883428

Cited by 5 publications

(5 citation statements)

References 14 publications

(22 reference statements)

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“…The model in [5] is similar to that in [85]. The users as bidders submit bids including their optimal power requests to the base station as the seller.…”

Section: B Distributed Dos (Ddos) Attackmentioning

confidence: 99%

“…To learn private types of users, the authors in [85] assumed that the base station can observe the users in a sufficient time to get probabilistic information of their behaviors. The base station's problem is to find the resource allocation that maximizes the users' social welfare, i.e., the sum of utilities, while preventing the maliciousness of users.…”

Section: Major Approachesmentioning

confidence: 99%

“…It can be seen that the pricing strategy in [85] is a type of the Bayesian pricing [86] in which prices for users are set based on the probabilistic assumptions on their behaviors. This pricing strategy is also similar to the differential pricing scheme [87] which sets different prices for different users according to their behaviors.…”

Section: Major Approachesmentioning

confidence: 99%

“…The users as bidders submit bids including their optimal power requests to the base station as the seller. The optimal power requests of users are determined similar to those in [85]. Upon receiving the bids, the base station allocates power to users according to the share auction, i.e., the proportional allocation, as presented in [46].…”

Section: Major Approachesmentioning

confidence: 99%

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Applications of Economic and Pricing Models for Wireless Network Security: A Survey

Luong

Hoang

Wang

et al. 2017

IEEE Commun. Surv. Tutorials

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Abstract-This paper provides a comprehensive literature review on applications of economic and pricing theory to security issues in wireless networks. Unlike wireline networks, the broadcast nature and the highly dynamic change of network environments pose a number of nontrivial challenges to security design in wireless networks. While the security issues have not been completely solved by traditional or system-based solutions, economic and pricing models recently were employed as one efficient solution to discourage attackers and prevent attacks to be performed. In this paper, we review economic and pricing approaches proposed to address major security issues in wireless networks including eavesdropping attack, Denial-of-Service (DoS) attack such as jamming and Distributed DoS (DDoS), and illegitimate behaviors of malicious users. Additionally, we discuss integrating economic and pricing models with cryptography methods to reduce information privacy leakage as well as to guarantee the confidentiality and integrity of information in wireless networks. Finally, we highlight important challenges, open issues and future research directions of applying economic and pricing models to wireless security issues.

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“…The model in [5] is similar to that in [85]. The users as bidders submit bids including their optimal power requests to the base station as the seller.…”

Section: B Distributed Dos (Ddos) Attackmentioning

confidence: 99%

Section: Major Approachesmentioning

confidence: 99%

Section: Major Approachesmentioning

confidence: 99%

Section: Major Approachesmentioning

confidence: 99%

See 2 more Smart Citations

Applications of Economic and Pricing Models for Wireless Network Security: A Survey

Luong

Hoang

Wang

et al. 2017

IEEE Commun. Surv. Tutorials

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“…A Bayesian network origin encoding technique is established on dynamic and overlapped arithmetic coding that solves the network issues [14]. The Bayesian mechanism contains pricing and auctions and receives the Nash Equilibrium points of the fundamental Bayesian games [15]. The prices and allocations are adapted by applying the Bayesian information.…”

Section: Introductionmentioning

confidence: 99%

Bayesian decision model based reliable route formation in internet of things

Kumar,

Mishra,

Reddy

et al. 2024

IJEECS

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Security provisioning has become an important issue in wireless multimedia networks because of their crucial task of supporting several services. This paper presents Bayesian decision model based reliable route formation in internet of things (BDMI). The main objective of the BDMI approach is to distinguish unreliable sensor nodes and transmit the data efficiently. Active and passive attack recognition methods identify unreliable node sensor nodes. Remaining energy, node degree, and packet transmission rate parameters to observe their node possibilities for recognizing the passive unreliable nodes. In active recognition, the base station (BS) confirms every sensor node identity, remaining energy, supportive node rate, node location, and link efficiency parameters to detect active unreliable sensor nodes. The Bayesian decision model (BDM) efficiently isolates an unreliable sensor node in the multimedia network. Simulation outcomes illustrate that the BDMI approach can efficiently enhance unreliable node detection and minimize the packet loss ratio in the network.

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