A Community Detection Method for Large-Scale Networks Against Sybil Attacks

Abstract

The invention discloses a community detection method for large-scale networks against witch attacks. Given a social network G=(V, E), V is a node set, and E is a social link or edge set; given a community Link strength threshold t, initialize the community link or edge set C=null; calculate the similarity index for the nodes at both ends of the edge (u, v) in each set E, denoted as s uv ; for each edge (u, v) in the set E, if s uv If not less than t, add the edge (u, v) to the set C; calculate all the connected subgraphs in the set C, and each connected subgraph is a community. The present invention can realize community detection of different granularities in a large-scale network, can effectively resist witch attacks, and improve community security.

Description

technical field [0001] The invention belongs to the technical field of cyberspace security community security, and in particular relates to a community detection method for large-scale networks against witch attacks. Background technique [0002] Society is an important feature of social networks, and it is inherent in most social networks. Community detection detects the communities existing in the network by observing and analyzing the social behavior and feature similarity between individuals. However, in reality, the community relationship of some networks is private information, and community detection will violate user privacy and cause security problems. For example, an AIDS patient often has more social relationships with his friends, encouraging and helping each other, but he does not want to be exposed to the AIDS community because of social interaction, that is, community exposure. In addition, a patient's friends may also have more social relationships (care an...

AI Technical Summary

Problems solved by technology

Therefore, the cost of data perturbation is often high, or difficult to achieve;

[0006] 2. Cause new security issues

After the disturbance, the division of associations becomes chaotic, which is often used by illegal elements to deceive the associations, causing unpredictable security risks;

[0007] 3. Cannot resist Sybil attacks

Once an attacker establishes a social relationship with certain individuals, it is easy to fool the community detection method

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