Trust Evaluation for Light Weight Security in Sensor Enabled Internet of Things: Game Theory Oriented Approach

Rani, Rinki; Kumar, Sushil; Dohare, Upasana

doi:10.1109/jiot.2019.2917763

Cited by 55 publications

(40 citation statements)

References 40 publications

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“…In this section, we briefly describe our research work from three aspects: The application of game theory, the application of trust, and the application of joint game theory and trust; and give some examples in the literature. Through the investigation of literature, we have concluded that most researchers use the following types of games: Dynamic game [32][33][34][35][36][37][38][39][40][41][42][43][44][45], static game [46], non-cooperative game [47][48][49][50][51], cooperative game [52][53][54][55][56][57][58][59], security game [60][61][62][63][64], and trust game [65][66][67][68][69].…”

Section: Relate Summarized Workmentioning

confidence: 99%

“…In this literature, researchers use trust relationships, trustworthiness, and other factors for decision-making. Based on trust, the researchers proposed some trust models [34,40,49,52,53,58,59,64,69,75,79], trust mechanisms [32,42,43,78,82], and trust frameworks [57]. They provide a better selection scheme for players in the network/system through trust evaluation.…”

Section: Relate Summarized Workmentioning

confidence: 99%

“…They establish a strategic trust mechanism in the internet of things and cyber-physical systems and use game theory to capture the adversarial and strategic nature of cyber-physical systems security [37,43]. In sensor networks, cooperative game and trust model are also combined, improving network security and enhancing the accuracy of data transmission [52,58,59]. Through the analysis of these literature, we can conclude that there are three main types of application scenarios: Centralized networks, distributed networks, and social networks.…”

Section: Relate Summarized Workmentioning

confidence: 99%

“…In [19], the problem of efficiently coordinating price-responsive appliances operating in the electricity market is tackled within a game theoretical framework. Cho [34] Al-Talabani et al [35] Muthukumar and Sahai [36] Pawlick and Zhu [37] Yang et al [38] Li et al [39] Wang et al [40] Gao et al [41] Xu et al [42] Pawlick et al [43] Niu et al [44] Pawlick et al [45] Shi et al [31] Maharjan et al [18] Zonouz et al [29] Tian et al [46] De Paola et al [19] Zhu et al [47] Anand et al [48] Xu et al [49] Ahn et al [50] Xu et al [51] Borjigin et al [24] De Paola et al [20] Gong et al [22] Basilico et al [30] Duan et al [52] Chen et al [53] Cao et al [54] Cho et al [55] Waqas et al [56] Wahab et al [57] Abdalzaher et al [58] Rani et al [59]…”

Section: Game Theory In Networkmentioning

confidence: 99%

“…In [24], a resource scheduling method for guaranteeing resource utilization and service performance is presented, maximizing the profits of players. The cooperative game is introduced into the network, which enables the network to maintain high security against malicious attacks and reduce malicious services [52,[57][58][59]. In device-to-device communication, game theory is combined with social ties or social trust.…”

Section: Security Game Trust Game Othersmentioning

confidence: 99%

See 4 more Smart Citations

Towards Security Joint Trust and Game Theory for Maximizing Utility: Challenges and Countermeasures

Huang

Jia

Fang

et al. 2019

Sensors

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The widespread application of networks is providing a better platform for the development of society and technology. With the expansion of the scope of network applications, many issues need to be solved. Among them, the maximization of utility and the improvement of security have attracted much attention. Many existing attacks mean the network faces security challenges. The concept of trust should be considered to address these security issues. Meanwhile, the utility of the network, including efficiency, profit, welfare, etc., are concerns that should be maximized. Over the past decade, the concepts of game and trust have been introduced to various types of networks. However, there is a lack of research effort on several key points in distributed networks, which are critical to the information transmission of distributed networks, such as expelling malicious nodes quickly and accurately and finding equilibrium between energy assumption and high transmission rate. The purpose of this paper is to give a holistic overview of existing research on trust and game theory in networks. We analyzed that network utility can be maximized in terms of effectiveness, profits, and security. Moreover, a possible research agenda is proposed to promote the application and development of game theory and trust for improving security and maximizing utility.

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Section: Relate Summarized Workmentioning

confidence: 99%

Section: Relate Summarized Workmentioning

confidence: 99%

Section: Relate Summarized Workmentioning

confidence: 99%

Section: Game Theory In Networkmentioning

confidence: 99%

Section: Security Game Trust Game Othersmentioning

confidence: 99%

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Towards Security Joint Trust and Game Theory for Maximizing Utility: Challenges and Countermeasures

Huang

Jia

Fang

et al. 2019

Sensors

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A game‐theoretic approach for ensuring trustworthiness in cyber‐physical systems with applications to multiloop UAV control

Jithish

Sankaran

2020

Trans Emerging Tel Tech

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Advancements in computing and communication technologies, coupled with the ubiquitous availability of low‐cost embedded devices, have enabled the vision of cyber‐physical systems (CPSs). With the advent of advanced persistent threats, CPSs are more vulnerable to sophisticated cyber‐attacks that cause catastrophic damages, thereby necessitating the development of novel defence architectures for CPS security. This work presents an analytical framework based on noncooperative game theory to evaluate the trustworthiness of individual nodes that constitute CPSs. The proposed approach uses the Nash equilibrium solution to derive a minimum trust threshold score for the CPS nodes. The game‐theoretic framework is evaluated on a supervisory control and data acquisition system prototype to model the evolution of the trust scores its sensors. Furthermore, we apply the model on a simulated unmanned aerial vehicle (UAV) system and derive the trust threshold. The trust threshold represents the minimum trust score required to be maintained by individual UAV nodes. Nodes with trust scores below the threshold are potentially malicious and may be removed or isolated to ensure the secure operation of the system. The proposed approach is successfully implemented to detect malicious behavior in a simulated multiloop UAV control system with a fewer number of false‐positives, achieving a maximum accuracy of 98.85% across different scenarios.

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ABBDIoT: Anomaly-Based Botnet Detection Using Machine Learning Model in the Internet of Things Network

Sudhakar¹,

Kumar²

2023

Lecture Notes in Electrical Engineering

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Trust Evaluation for Light Weight Security in Sensor Enabled Internet of Things: Game Theory Oriented Approach

Cited by 55 publications

References 40 publications

Towards Security Joint Trust and Game Theory for Maximizing Utility: Challenges and Countermeasures

Towards Security Joint Trust and Game Theory for Maximizing Utility: Challenges and Countermeasures

A game‐theoretic approach for ensuring trustworthiness in cyber‐physical systems with applications to multiloop UAV control

ABBDIoT: Anomaly-Based Botnet Detection Using Machine Learning Model in the Internet of Things Network

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