LibreSocial: A peer‐to‐peer framework for online social networks

Graffi, Kálmán; Masinde, Newton

doi:10.1002/cpe.6150

Cited by 12 publications

(3 citation statements)

References 63 publications

(113 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For privacyminded applications, it would be desirable to have an OSNAC-like system, where permissions are enforced without a service provider. Peer-to-peer networks such as Peer-SoN [28], Glycos [29], or LibreSocial [30] all provide private and secure SNSs. Their access control mechanisms are relatively simple, in the sense that every user that should have access is listed with the protected data item.…”

Section: Datalog and Rebacmentioning

confidence: 99%

Circuitree: A Datalog Reasoner in Zero-Knowledge

Godden

Smet

Debruyne³

et al. 2022

IEEE Access

View full text Add to dashboard Cite

show abstract

Section: Datalog and Rebacmentioning

confidence: 99%

Circuitree: A Datalog Reasoner in Zero-Knowledge

Godden

Smet

Debruyne³

et al. 2022

IEEE Access

View full text Add to dashboard Cite

show abstract

“…When the amount of data is large, the communication link of the traditional social network method is easily interrupted, and a stable end-to-end path cannot be maintained, which significantly affects the success rate of information delivery [6]. Opportunistic social networks are intermittently connected mobile ad hoc networks, which usually implement communication between nodes in a "storagecarry-forward" routing mode, which can provide strong support for the effective transmission of data [7,8]. This transmission mechanism relies on node movement to achieve, and human mobility can be used to carry messages between separate parts of the network physically.…”

Section: Introductionmentioning

confidence: 99%

Effective Data Optimization and Evaluation Based on Social Communication with AI-Assisted in Opportunistic Social Networks

Gou

Long

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Billions of people around the world send and receive data over online networks daily. Sufficient and redundant data are transmitted over social platforms with AI-assisted in 5G networks. In opportunistic social networks, the main challenge faced by traditional methods is that numerous user nodes participate in data transmission, causing a lot of message copy redundancy and node cache consumption. As a result, the transmission delay of the algorithm is high, the node energy consumption is too large, and even information is lost. To solve these problems, this study establishes an artificial intelligence-based optimization multiple evaluation method. The main purpose of this method is to avoid information loss caused by data loss when reducing data noise, reasonably select communication nodes in opportunistic social network scenarios, optimize data transmission performance, and avoid network congestion. Moreover, our method can effectively identify and exclude potential malicious nodes, reducing the situation that packets are intercepted and discarded. The experiment confirms that the optimized transmission evaluation scheme can effectively reduce routing overheads and energy consumption of a user node, improve the delivery ratio of node data transmission, and ensure the reliability and security of data transmission.

show abstract

“…In order to achieve a decentralized social media platform, a p2p solution is required. A number of decentralized solutions have been proposed, such as [2], [4], that do address the base for achieving the goals towards having a decentralized solutions (and in some cases taking into account privacy aspects at some level), but they do lack the solution of achieving un-tractability in the networks.…”

Section: Introductionmentioning

confidence: 99%

Privacy-Preserving Peer Discovery for Group Management in p2p Networks

Meskanen

Niemi

Kuusijaarvi

2020

2020 27th Conference of Open Innovations Association (FRUCT)

View full text Add to dashboard Cite

The necessity for peer-to-peer (p2p) communications is obvious; current centralized solutions are capturing and storing too much information from the individual people communicating with each other. Privacy concerns with a centralized solution in possession of all the users data are a difficult matter. HELIOS platform introduces a new social-media platform that is not in control of any central operator, but brings the power of possession of the data back to the users. It does not have centralized servers that store and handle receiving/sending of the messages. Instead, it relies on the current open-source solutions available in the p2p communities to propagate the messages to the wanted recipients of the data and/or messages. The p2p communications also introduce new problems in terms of privacy and tracking of the user, as the nodes part of a p2p network can see what data the other nodes provide and ask for. How the sharing of data in a p2p network can be achieved securely, taking into account the user's privacy is a question that has not been fully answered so far. We do not claim we answer this question fully in this paper either, but we propose a set of protocols to help answer one specific problem. Especially, this paper proposes how to privately share data (end-point address or other) of the user between other users, provided that they have previously connected with each other securely, either offline or online.

show abstract

LibreSocial: A peer‐to‐peer framework for online social networks

Cited by 12 publications

References 63 publications

Circuitree: A Datalog Reasoner in Zero-Knowledge

Circuitree: A Datalog Reasoner in Zero-Knowledge

Effective Data Optimization and Evaluation Based on Social Communication with AI-Assisted in Opportunistic Social Networks

Privacy-Preserving Peer Discovery for Group Management in p2p Networks

Contact Info

Product

Resources

About