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: "quality of information in mobile crowdsensing survey and research challenges"
  Abstract: Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.

Connected through hyperedge HE-1 (induced by source paper "a novel methodology for designing policies in mobile crowdsensing systems"):
  with members:
    - "incentme effective mechanism design to stimulate crowdsensing participants with uncertain mobility"
    - "a socially aware incentive mechanism for mobile crowdsensing service market"
    - "incentive mechanisms for participatory sensing survey and research challenges"

Connected through hyperedge HE-2 (induced by source paper "fridges on the highway road traffic poisoning of navigation apps"):
  with members:
    - "vulnerability analysis of smart grids to gps spoofing"

Connected through hyperedge HE-3 (induced by source paper "blockchain for the internet of things present and future"):
  with members:
    - "machine learning for wireless communications in the internet of things a comprehensive survey"
    - "block4forensic an integrated lightweight blockchain framework for forensics applications of connected vehicles"
    - "securing the internet of things in the age of machine learning and software defined networking"
    - "smart contract based access control for the internet of things"
    - "lsb a lightweight scalable blockchain for iot security and privacy"
    - "learning to detect and mitigate cross layer attacks in wireless networks framework and applications"
    - "blockchain a distributed solution to automotive security and privacy"
    - "providing privacy safety and security in iot based transactive energy systems using distributed ledgers"

Connected through hyperedge HE-4 (induced by source paper "trust evaluation mechanism for user recruitment in mobile crowd sensing in the internet of things"):
  with members:
    - "social network assisted worker recruitment in mobile crowd sensing"
    - "when crowdsourcing meets mobile sensing a social network perspective"
    - "mobile crowd sensing and computing when participatory sensing meets participatory social media"
    - "from participatory sensing to mobile crowd sensing"
    - "sensing as a service model for smart cities supported by internet of things"
    - "internet of things iot a vision architectural elements and future directions"
    - "pagerank standing on the shoulders of giants"
    - "supervised random walks predicting and recommending links in social networks"

Connected through hyperedge HE-5 (induced by source paper "securing the internet of things in the age of machine learning and software defined networking"):
  with members:
    - "learning to detect and mitigate cross layer attacks in wireless networks framework and applications"
    - "iot sentinel demo automated device type identification for security enforcement in iot"
    - "low power wide area networks an overview"
    - "a survey on wireless security technical challenges recent advances and future trends"
    - "understanding modern banking ledgers through blockchain technologies future of transaction processing and smart contracts on the internet of money"
    - "device fingerprinting in wireless networks challenges and opportunities"
    - "incentive mechanisms for participatory sensing survey and research challenges"
    - "a survey on truth discovery"

Connected through hyperedge HE-6 (induced by source paper "hytasker hybrid task allocation in mobile crowd sensing"):
  with members:
    - "task allocation in mobile crowd sensing state of the art and future opportunities"
    - "prediction based task assignment in spatial crowdsourcing"
    - "taskme multi task allocation in mobile crowd sensing"
    - "reliable diversity based spatial crowdsourcing by moving workers"
    - "lazier than lazy greedy"
    - "data for development the d4d challenge on mobile phone data"

Connected through hyperedge HE-7 (induced by source paper "incentme effective mechanism design to stimulate crowdsensing participants with uncertain mobility"):
  with members:
    - "securing the internet of things in the age of machine learning and software defined networking"
    - "taskme multi task allocation in mobile crowd sensing"
    - "incentive mechanisms for participatory sensing survey and research challenges"
    - "mining users significant driving routes with low power sensors"
    - "on the approximability of budget feasible mechanisms"
    - "budget feasible mechanisms"

Connected through hyperedge HE-8 (induced by source paper "first a framework for optimizing information quality in mobile crowdsensing systems"):
  with members:
    - "taskme multi task allocation in mobile crowd sensing"
    - "ear phone a context aware noise mapping using smart phones"

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)