human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "end to end privacy for open big data markets"
  Abstract: Establishing an open data market would require the creation of a data trading model to facilitate exchange of data between different parties in the Internet of Things (IoT) domain. The data collected by IoT products and solutions are expected to be traded in these markets. Data owners will collect data using IoT products and solutions. Data consumers who are interested will negotiate with the data owners to get access to such data. Data captured by IoT products will allow data consumers to further understand the preferences and behaviors of data owners and to generate additional business value using techniques ranging from waste reduction to personalized service offerings. In open data markets, data consumers will be able to give back part of the additional value generated to the data owners. However, privacy becomes a significant issue when data that can be used to derive extremely personal information is being traded. This article discusses why privacy matters in the IoT domain in general and especially in open data markets, and then surveys existing privacy-preserving strategies and design techniques that can be used to facilitate end-to-end privacy for open data markets. It also highlights some of the major research challenges that must be addressed to make the vision of open data markets a reality through ensuring the privacy of stakeholders.

Connected through hyperedge HE-1 (induced by source paper "emerging privacy issues and solutions in cyber enabled sharing services from multiple perspectives"):
  with members:
    - "regulating highly automated robot ecologies insights from three user studies"
    - "information design in crowdfunding under thresholding policies"
    - "an online mechanism for ridesharing in autonomous mobility on demand systems"
    - "managing autonomous mobility on demand systems for better passenger experience"
    - "the hidden cost of accommodating crowdfunder privacy preferences a randomized field experiment"
    - "reliable crowdsourcing for multi class labeling using coding theory"
    - "a clustering based location privacy protection scheme for pervasive computing"

Connected through hyperedge HE-2 (induced by source paper "emerging privacy issues and solutions in cyber enabled sharing services from multiple perspectives"):
  with members:
    - "regulating highly automated robot ecologies insights from three user studies"
    - "information design in crowdfunding under thresholding policies"
    - "an online mechanism for ridesharing in autonomous mobility on demand systems"
    - "managing autonomous mobility on demand systems for better passenger experience"
    - "the hidden cost of accommodating crowdfunder privacy preferences a randomized field experiment"
    - "reliable crowdsourcing for multi class labeling using coding theory"
    - "a clustering based location privacy protection scheme for pervasive computing"

Connected through hyperedge HE-3 (induced by source paper "valorising the iot databox creating value for everyone"):
  with members:
    - "big data privacy in the internet of things era"
    - "the emerging internet of things marketplace from an industrial perspective a survey"
    - "a survey on internet of things from industrial market perspective"
    - "improve the sustainability of internet of things through trading based value creation"
    - "human data interaction the human face of the data driven society"
    - "sensing as a service model for smart cities supported by internet of things"
    - "a market for unbiased private data paying individuals according to their privacy attitudes"
    - "your browsing behavior for a big mac economics of personal information online"

Connected through hyperedge HE-4 (induced by source paper "privacy knowledge modelling for internet of things a look back"):
  with members:
    - "context aware computing for the internet of things a survey"

Question: Please tell me which class the center node 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.CY(Computers and Society)