A brief survey on anonymization techniques for privacy preserving publishing of social network data

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Private analysis of graph structure (2011, background): “See [13] for a survey of techniques for anonymizing social networks that work along the lines of k -anonymity (and do not carry the strong semantics of diﬀerential privacy).”
Collective Data-Sanitization for Preventing Sensitive Information Inference Attacks in Social Networks (2018, background): “The work in [11] presents a systematic survey for the anonymization techniques for social network data.”
Audience selection for on-line brand advertising: privacy-friendly social network targeting (2009, background): “This is important not only from a base-level privacy standpoint, but also as a deterrent to reidentiﬁcation [27].”
Privacy-Preserving Visual Learning Using Doubly Permuted Homomorphic Encryption (2017, background): “More practical tasks include privacy-preserving data mining [3, 4], ubiquitous computing [36], and social network analysis [64].”
Trustworthy AI: From Principles to Practices (2021, background): “For example, private information in the form of graph data for social networks can be potentially contained in properties of the vertices of the graph, its link relationships, weights, or other graph metrics [390].”