Nadav Voloch

Affiliations:
  • Ben-Gurion University of the Negev, Beersheba, Israel


According to our database1, Nadav Voloch authored at least 12 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Multiple Subset Problem as an encryption scheme for communication.
CoRR, 2024

2022
Handling Exit Node Vulnerability in Onion Routing with a Zero-Knowledge Proof.
Proceedings of the Information Integration and Web Intelligence, 2022

Fake News Detection in Social Networks Using Machine Learning and Trust.
Proceedings of the Cyber Security, Cryptology, and Machine Learning, 2022

2021
A Trust based Privacy Providing Model for Online Social Networks.
Online Soc. Networks Media, 2021

Preventing Fake News Propagation in Social Networks Using a Context Trust-Based Security Model.
Proceedings of the Network and System Security - 15th International Conference, 2021

Implementing GDPR in Social Networks Using Trust and Context.
Proceedings of the Cyber Security Cryptography and Machine Learning, 2021

2020
Analyzing the Robustness of a Comprehensive Trust-Based Model for Online Social Networks Against Privacy Attacks.
Proceedings of the Complex Networks & Their Applications IX, 2020

2019
Managing large distributed dynamic graphs for smart city network applications.
Appl. Netw. Sci., 2019

A Role and Trust Access Control Model for Preserving Privacy and Image Anonymization in Social Networks.
Proceedings of the Trust Management XIII - 13th IFIP WG 11.11 International Conference, 2019

An MST-based information flow model for security in Online Social Networks.
Proceedings of the Eleventh International Conference on Ubiquitous and Future Networks, 2019

An Access Control Model for Data Security in Online Social Networks Based on Role and User Credibility.
Proceedings of the Cyber Security Cryptography and Machine Learning, 2019

2018
An Information-Flow Control Model for Online Social Networks Based on User-Attribute Credibility and Connection-Strength Factors.
Proceedings of the Cyber Security Cryptography and Machine Learning, 2018


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