Related papers: SybilControl: Practical Sybil Defense with Computa…
Sybil attacks are a fundamental threat to the security of distributed systems. Recently, there has been a growing interest in leveraging social networks to mitigate Sybil attacks. However, the existing approaches suffer from one or more…
Any decentralised distributed network is particularly vulnerable to the Sybil attack wherein a malicious node masquerades as several different nodes, called Sybil nodes, simultaneously in an attempt to disrupt the proper functioning of the…
Sybil attacks are becoming increasingly widespread and pose a significant threat to online social systems; a single adversary can inject multiple colluding identities in the system to compromise security and privacy. Recent works have…
This paper reviews the Sybil attack in social networks, which has the potential to compromise the whole distributed network. In the Sybil attack, the malicious user claims multiple identities to compromise the network. Sybil attacks can be…
Sybil attacks are becoming increasingly widespread, and pose a significant threat to online social systems; a single adversary can inject multiple colluding identities in the system to compromise security and privacy. Recent works have…
The Sybil attack plagues all peer-to-peer systems, and modern open distributed ledgers employ a number of tactics to prevent it from proof of work, or other resources such as space, stake or memory, to traditional admission control in…
Federated learning is a privacy-enforcing machine learning technology but suffers from limited scalability. This limitation mostly originates from the internet connection and memory capacity of the central parameter server, and the…
In federated learning, machine learning and deep learning models are trained globally on distributed devices. The state-of-the-art privacy-preserving technique in the context of federated learning is user-level differential privacy.…
Distributed hash tables suffer from several security and privacy vulnerabilities, including the problem of Sybil attacks. Existing social network-based solutions to mitigate the Sybil attacks in DHT routing have a high state requirement and…
Detecting fake users (also called Sybils) in online social networks is a basic security research problem. State-of-the-art approaches rely on a large amount of manually labeled users as a training set. These approaches suffer from three key…
Detecting and suspending fake accounts (Sybils) in online social networking (OSN) services protects both OSN operators and OSN users from illegal exploitation. Existing social-graph-based defense schemes effectively bound the accepted…
This paper presents SYBILGAT, a novel approach to Sybil detection in social networks using Graph Attention Networks (GATs). Traditional methods for Sybil detection primarily leverage structural properties of networks; however, they tend to…
We investigate the problem of sybil (fake account) detection in social networks from a graph algorithms perspective, where graph structural information is used to classify users as sybil and benign. We introduce the novel notion of user…
Restaking protocols expand validator responsibilities beyond consensus, but their security depends on resistance to Sybil attacks. We introduce a formal framework for Sybil-proofness in restaking networks, distinguishing between two types…
Internet of things (IoT) connects all items to the Internet through information-sensing devices to exchange information for intelligent identification and management. Sybil attack is a famous and crippling attack in IoT. Most of the…
P2P systems are highly susceptible to Sybil attacks, in which an attacker creates a large number of identities and uses them to control a substantial fraction of the system. Persea is the most recent approach towards designing a social…
This paper describes a simulation study on security attacks over Distributed Ledger Technologies (DLTs). We specifically focus on attacks at the underlying peer-to-peer layer of these systems, that is in charge of disseminating messages…
Machine learning (ML) over distributed multi-party data is required for a variety of domains. Existing approaches, such as federated learning, collect the outputs computed by a group of devices at a central aggregator and run iterative…
As popular tools for spreading spam and malware, Sybils (or fake accounts) pose a serious threat to online communities such as Online Social Networks (OSNs). Today, sophisticated attackers are creating realistic Sybils that effectively…
The InterPlanetary File System (IPFS) is a decentralized peer-to-peer (P2P) storage built on Kademlia, a Distributed Hash Table (DHT) structure commonly used in P2P systems and known for its proved scalability. However, DHTs susceptible to…