Defending against Sybil Nodes in BitTorrent

Abstract

Abstract. BitTorrent and its derivatives contribute a major portion of Internet traffic due to their simple and scalable operation. However, the lack of security mechanisms makes them vulnerable to attacks such as file piece pollution, connection slot consumption, and bandwidth exhaustion. These effects are made worse by the ability of attackers to manufacture new identities, or Sybil nodes, at will. The net effect of Sybil nodes and weak security leads to inefficient BitTorrent operation, or collapse. In this paper, we present defenses against threats from Sybil attackers in BitTorrent. A simple, direct reputation scheme called GOLF fosters peer cooperation to exclude potential attackers. Locality filtering tentatively identifies Sybil nodes based on patterns in IP addresses. Under the proposed scheme, Sybil attackers may still continue malicious behaviors, but their effect sharply decreases. Comparison to existing reputation models shows GOLF effectively detects and blocks potential attackers, despite false accusation.

Exploring Sybil and Double-Spending Risks in Blockchain Systems

“…In traditional P2P systems, the Sybil attack imposes various threats and subverts the reputation of a P2P network. For example, the attacker uses Sybil identities to pollute the BitTorrent distributed hash table (DHT) routing to trigger delays, connection slot consumption, invalid file contents downloads, and bandwidth exhaustion [19]. Similarly, the attacker can use the clone node attack to target static wireless sensor networks (WSNs) [124] by taking control of node n and replicating it throughout the network.…”

“…Sybil attacks are hard to prevent [7], however, there exist preventive measures to increase protection against Sybil attack. The authors [19] present a reputation-based scheme 'GOLF' to identify Sybil nodes on BitTorrent DHT based on patterns in IP addresses. Numan et al [124] perform a litera-This work is licensed under a Creative Commons Attribution 4.0 License.…”

Slowing down to speed up: Protecting users against massive attacks in content distribution systems

“…The aforementioned "rotation" algorithm may also be applied to tackle Eclipse attacks (LEHMANN et al, 2012). So and Reeves (SO;REEVES, 2011) propose a solution using locality filters to restrict the neighborhood of a user and mitigate the effect of massive attacks. In another work, Singh et al (SINGH et al, 2006) design a solution to detect colluding users by monitoring their list of neighbors.…”

“…This attack consists on malicious users connecting to a victim and uploading junk data (DHUNGEL et al, 2008;YANG et al, 2008). Solutions based on hash functions were proposed to verify the integrity of pieces (HARIDASAN; RENESSE, 2006;MEIER;WATTENHOFER, 2008;SO;REEVES, 2011). In another work, Lehmann et al (LEHMANN et al, 2012) propose an additional reputation mechanism to isolate users who send corrupt pieces.…”