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 "a friendship privacy attack on friends and 2 distant neighbors in social networks"):
  Abstract: In an undirected social graph, a friendship link involves two users and the friendship is visible in both the users' friend lists. Such a dual visibility of the friendship may raise privacy threats. This is because both users can separately control the visibility of a friendship link to other users and their privacy policies for the link may not be consistent. Even if one of them conceals the link from a third user, the third user may find such a friendship link from another user's friend list. In addition, as most users allow their friends to see their friend lists in most social network systems, an adversary can exploit the inconsistent policies to launch privacy attacks to identify and infer many of a targeted user's friends. In this paper, we propose, analyze and evaluate such an attack which is called Friendship Identification and Inference (FII) attack. In a FII attack scenario, we assume that an adversary can only see his friend list and the friend lists of his friends who do not hide the friend lists from him. Then, a FII attack contains two attack steps: 1) friend identification and 2) friend inference. In the friend identification step, the adversary tries to identify a target's friends based on his friend list and those of his friends. In the friend inference step, the adversary attempts to infer the target's friends by using the proposed random walk with restart approach. We present experimental results using three real social network datasets and show that FII attacks are generally efficient and effective when adversaries and targets are friends or 2-distant neighbors. We also comprehensively analyze the attack results in order to find what values of parameters and network features could promote FII attacks. Currently, most popular social network systems with an undirected friendship graph, such as Facebook, LinkedIn and Foursquare, are susceptible to FII attacks.

Includes members:
  Member "risks of friendships on social networks":
    also connected through other hyperedges:
      (none)
  Member "predicting links and inferring attributes using a social attribute network san":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "clustering attributed graphs models measures and methods")
  Member "all liaisons are dangerous when all your friends are known to us":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "privacy in social media identification mitigation and applications")

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)