Trust and reputation management for opportunistic dissemination

Ciobanu, Radu-Ioan; Marin, Radu-Corneliu; Dobre, Ciprian; Cristea, Valentin

doi:10.1016/j.pmcj.2016.09.016

Cited by 20 publications

(13 citation statements)

References 7 publications

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“…Under the model, each entity should communicate with as many entities as possible to obtain more accurate verification and reputation calculation. By considering majority opinions from others, Ciobanu et al [27] investigate the security aspects of employing intermediate nodes on the delay-tolerant network (DTN). They propose opportunistic trust and reputation management called SAROS in order to detect and avoid malicious nodes by comparing several contents coming from various nodes within an interest-space.…”

Section: B Evaluation Of Reputationmentioning

confidence: 99%

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BPT Scheme: Establishing Trusted Vehicular Fog Computing Service for Rural Area Based on Blockchain Approach

Dewanta

Mambo

2021

IEEE Trans. Veh. Technol.

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Passing through a rural area with a limited network infrastructure may disrupt fog computing support for vehicles. As a result, some applications on vehicles may turn off and bother the performance of the vehicular systems. In order to escape from this kind of situation, vehicular fog computing is discussed in recent times as an alternative of fog computing support while passing through a blank spot of network infrastructure. However, it is not feasible to establish a trusted vehicular fog computing service among vehicles without mutual trust. To deal with this situation, this paper proposes a method called Bidding-Price-based Transaction (BPT) for vehicular fog computing service in rural areas. This method is composed of bidding-price-based mutual trust establishment between client vehicle and server vehicle and also payoff assignment based on transaction evaluation. By applying this method, trusted fog computing service transactions between two vehicles can be achieved without the direct assistance of any trusted third party as a validating entity. The simulation results and feasibility analysis then validate the performance of the BPT scheme in rural areas. Based on feasibility analysis, we claim that the BPT scheme can be realized by adjusting vehicle speed and transmission range with respect to the size of offloaded data.

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Section: B Evaluation Of Reputationmentioning

confidence: 99%

“…However, intuitively trust computation that relies on the number of participants is vulnerable to collusion attacks. Moreover, without verifying entities, e.g., identity, location, etc., the previous trust evaluations in [27] and [28] will be useless in case of adversaries launching Sybil attacks.…”

Section: B Evaluation Of Reputationmentioning

confidence: 99%

BPT Scheme: Establishing Trusted Vehicular Fog Computing Service for Rural Area Based on Blockchain Approach

Dewanta

Mambo

2021

IEEE Trans. Veh. Technol.

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“…The resilience of this protocol against other attacks such as bad or good mouthing, black hole attack, has not been studied. Ciobanu et al [18] proposed a trust and reputation management mechanism (called SAROS) for OppNets. Trust is computed as local and global and a quorum-based algorithm is used for deciding the correctness of the received messages.…”

Section: Trust-based Approachesmentioning

confidence: 99%

T_CAFE: A Trust based Security approach for Opportunistic IoT

2019

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“…Beyond mobile crowdsensing, the notion of computational trust has been employed to solve many research problems related to the QoI, including e-commerce [93,124]. Among the fields closely related to mobile crowdsensing, we include sensor networks [9,83,84,137,163], opportunistic networks [32,99,153,198], and social networks [59,197], to name a few. However, establishing trust in mobile crowdsensing poses some unique challenges that cannot be addressed solely with existing trust frameworks.…”

Section: Related Workmentioning

confidence: 99%

Quality of Information in Mobile Crowdsensing

Restuccia

Ghosh

Bhattacharjee

et al. 2017

ACM Trans. Sen. Netw.

152

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Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work. F. Restuccia et al.Not only are today's smartphones ubiquitous devices, they are also equipped with a plethora of embedded multi-modal sensors; integrate wireless communication technologies such as 4G/WiFi Internet connectivity, and possess complex processing capabilities. For example, the cameras on smartphones can be used as video and image sensors [29], the microphone can be used as an acoustic sensor [39,154,206], and the embedded global positioning system (GPS) receiver can be used to gather accurate location information, while gyroscopes, accelerometers, and proximity sensors can be used to extract contextual information about the users, such as driving or walking states [75,122]. Further, additional sensors can be easily interfaced with smartphones via Bluetooth or wired connections, such as temperature, air quality, and humidity [69,168].These technological features, combined with the advanced sensing capability of humans, has spurred a significant amount of research from both academia and industry, which together have proposed over the last 10 years a myriad of applications based on the emerging mobile crowdsensing paradigm 1 . Mobile crowdsensing empowers ordinary citizens (or users 2 ) with the capability to actively monitor various phenomena pertaining to themselves (e.g., health, social connections) or their community (e.g., environment). This rich information or inference about themselves or the community may also be sent back to the participating or other concerned users to improve their life experiences, thus influencing their choices. Real-life applications, which can take advantage of both low-level sensor data and high-level user activities, range from real-time traffic monitoring applications, to environmental pollution monitoring, crime monitoring, and social networking, just to name a few. For a survey on mobile crowdsensin...

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Trust and reputation management for opportunistic dissemination

Cited by 20 publications

References 7 publications

BPT Scheme: Establishing Trusted Vehicular Fog Computing Service for Rural Area Based on Blockchain Approach

BPT Scheme: Establishing Trusted Vehicular Fog Computing Service for Rural Area Based on Blockchain Approach

T_CAFE: A Trust based Security approach for Opportunistic IoT

Quality of Information in Mobile Crowdsensing

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