human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "conditional adjacency anonymity in social graphs under active attacks"):
  Abstract: Social network data is typically made available in a graph format, where users and their relations are represented by vertices and edges, respectively. In doing so, social graphs need to be anonymised to resist various privacy attacks. Among these, the so-called active attacks, where an adversary has the ability to enrol sybil accounts in the social network, have proven difficult to counteract. In this article, we provide an anonymisation technique that successfully thwarts active attacks while causing low structural perturbation. We achieve this goal by introducing #N#                  #N#                    #N#                  #N#                  $$(k, \Gamma _{G,\ell })$$#N#                  #N#                    #N#                  #N#                -adjacency anonymity: a privacy property based on #N#                  #N#                    #N#                  #N#                  $$(k,\ell )$$#N#                  #N#                    #N#                  #N#                -anonymity that alleviates the computational burden suffered by anonymisation algorithms based on #N#                  #N#                    #N#                  #N#                  $$(k,\ell )$$#N#                  #N#                    #N#                  #N#                -anonymity and relaxes some of its assumptions on the adversary capabilities. We show that the proposed method is efficient and establish tight bounds on the number of modifications that it performs on the original graph. Experimental results on real-life and randomly generated graphs show that when compared to methods based on #N#                  #N#                    #N#                  #N#                  $$(k,\ell )$$#N#                  #N#                    #N#                  #N#                -anonymity, the new method continues to provide protection from equally capable active attackers while introducing a much smaller number of changes in the graph structure.

Includes members:
  Member "on the computational complexities of three privacy measures for large networks under active attack":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on analyzing and evaluating privacy measures for social networks under active attack")
  Member "discovering social circles in ego networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "relational thematic clustering with mutually preferred neighbors")
  Member "preserving link privacy in social network based systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "target privacy preserving for social networks")
  Member "de anonymizing social networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "knowledge graphs")
  Member "anonymity and information hiding in multiagent systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards logical specification of statistical machine learning")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SI(Social and Information Networks)