FileLinker: Simple Peer-to-Peer File Sharing Using Wi-Fi Direct and NFC

Kwan, Keith; Greaves, Brian

doi:10.23919/istafrica.2019.8764840

Cited by 5 publications

(4 citation statements)

References 16 publications

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“…The Near Field Communication (NFC) technology, which enables two NFC-enabled devices to converse and exchange information in an ad hoc manner [28], is another model of WPANs applications. This contactless technology enables devices to connect with a simple tap or touch, allowing them to perform various functions such as cashless payment, peer-to-peer data transfer, loyalty and membership identification, and other real-time applications.…”

Section: Wireless Personal Area Network (Wpan)mentioning

confidence: 99%

Exploring Manet Security Aspects: Analysis of Attacks and Node Misbehaviour Issues

Khan

Anwar²,

Rahman³

et al. 2022

MJCS

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Mobile ad hoc networks are susceptible to various security threats due to their open media nature and mobility, making them a top priority for security measures. This paper provides an in-depth examination of MANET security issues. Some of the most critical aspects of mobile ad hoc networks, including their applications, have been discussed. This is followed by a discussion of MANETs' design vulnerability to external and internal security threats caused by inherent network characteristics such as limited battery power, mobility, dynamic topology, open media, and so on. Numerous MANET-related attacks have been classified based on their sources, behaviour, participating nodes, processing capability, and layering. The many different types of misbehaviour a node can exhibit and the various ways a node can behave were investigated. Two major types of MANETs misbehaviour have been evaluated, classified and analysed. Notably, mitigating node misbehaviour in MANET is a critical issue that must be addressed to ensure network node functionality and availability. Strategies for detecting network nodes that misroute packets are also examined. Finally, the paper emphasises the need for effective solutions to secure MANETs.

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Section: Wireless Personal Area Network (Wpan)mentioning

confidence: 99%

Exploring Manet Security Aspects: Analysis of Attacks and Node Misbehaviour Issues

Khan

Anwar²,

Rahman³

et al. 2022

MJCS

View full text Add to dashboard Cite

show abstract

“…Given the user's permission, we access the user's 50 most recently played tracks using OAuth 2.0. 43 Retrieving these recently played tracks regularly yields implicit ratings by the user -based on the assumption that the more a user listened to a track, the more he/she likes it. From the user's side, authorizing our app to access Spotify is the only action he/she must take.…”

Section: ) Automatic Data Trackingmentioning

confidence: 99%

MobRec: Mobile Platform for Decentralized Recommender Systems

Beierle¹

2021

T-Labs Series in Telecommunication Services

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“…The WiFi Alliance developed another WiFi mode for device-to-device communication, WiFi Direct, which is supported on Android devices with version 4.0 and higher [39]. 8 There are several related papers dealing with WiFi Direct for device-to-device communication [18], [37], [40]- [43]. While the Talk2Me prototype was developed utilizing WiFi Direct, Shu et al describe how it is not mature enough and wasn't used for the evaluation [18].…”

Section: B Wifimentioning

confidence: 99%

“…Spotify has by far the most subscribers in the market of music streaming services (36% market share 42 ). Given the user's permission, we access the user's 50 most recently played tracks using OAuth 2.0 43 . Retrieving these recently played tracks regularly yields implicit ratings by the user -based on the assumption that the more a user listened to a track, the more he/she likes it.…”

Section: ) Automatic Data Trackingmentioning

confidence: 99%

MobRec — Mobile Platform for Decentralized Recommender Systems

Beierle

Egger

2020

IEEE Access

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Recommender systems recommend new movies, music, restaurants, etc. Typically, service providers organize such systems in a centralized way, holding all the data. Biases in the recommender systems are not transparent to the user and lock-in effects might make it inconvenient for the user to switch providers. In this paper, we present the concept, design, and implementation of MobRec, a mobile platform that decentralizes the data collection, data storage, and recommendation process. MobRec's architecture does not need any backend and solely consists of the users' smartphones, which already contain the users' preferences and ratings. Being in proximity in public places or public transportation, data is exchanged in a device-to-device manner, building local databases that can recommend new items. One of biggest challenges of such a system is the implementation of unobtrusive device-to-device data exchange on off-the-shelf Android devices and iPhones. MobRec facilitates such data exchange, building on Google Nearby Messages with Bluetooth Low Energy. We achieve the successful exchange of data within 3 to 4 minutes, making it suitable for the described scenario. We demonstrate the feasibility of decentralized recommender systems and provide blueprints for the development of seamless multi-platform device-to-device communication.

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FileLinker: Simple Peer-to-Peer File Sharing Using Wi-Fi Direct and NFC

Cited by 5 publications

References 16 publications

Exploring Manet Security Aspects: Analysis of Attacks and Node Misbehaviour Issues

Exploring Manet Security Aspects: Analysis of Attacks and Node Misbehaviour Issues

MobRec: Mobile Platform for Decentralized Recommender Systems

MobRec — Mobile Platform for Decentralized Recommender Systems

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