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 "on analyzing and evaluating privacy measures for social networks under active attack"):
  Abstract: Abstract   Widespread usage of complex interconnected social networks such as  Facebook, Twitter  and  LinkedIn in modern internet era has also unfortunately opened the door for privacy violation of users of such networks by malicious entities. In this article we investigate, both theoretically and empirically, privacy violation measures of large networks under active attacks that was recently introduced in Trujillo-Rasua and Yero (2016). Our theoretical result indicates that the network manager responsible for prevention of privacy violation must be very careful in designing the network  if its topology does not contain a cycle . Our empirical results shed light on privacy violation properties of eight real social networks as well as a large number of synthetic networks generated by both the classical Erdos–Renyi model and the scale-free random networks generated by the Barabasi–Albert preferential-attachment model.

Includes members:
  Member "privacy preserving machine learning through data obfuscation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "predicting performance of asynchronous differentially private learning")
  Member "ml leaks model and data independent membership inference attacks and defenses on machine learning models":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic backdoor attacks against machine learning models")
  Member "motifs in temporal networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hypergraph motifs concepts algorithms and discoveries")
  Member "on optimal approximability results for computing the strong metric dimension":
    also connected through other hyperedges:
      (none)
  Member "on the computational complexities of three privacy measures for large networks under active attack":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "conditional adjacency anonymity in social graphs under active attacks")
  Member "computing the diameter polynomially faster than apsp":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "approximation algorithms for min distance problems")

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)