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 "internet of things enabled policing processes"):
  Abstract: The Internet of Things (IoT) has the potential to transform many industries. This includes harnessing real-time intelligence to improve risk-based decision making and supporting adaptive processes from core to edge. For example, modern police investigation processes are often extremely complex, data-driven and knowledge-intensive. In such processes, it is not sufficient to focus on data storage and data analysis; as the knowledge workers (e.g., police investigators) will need to collect, understand and relate the big data (scattered across various systems) to process analysis. In this thesis, we analyze the state of the art in knowledge-intensive and data-driven processes. We present a scalable and extensible IoT-enabled process data analytics pipeline to enable analysts ingest data from IoT devices, extract knowledge from this data and link them to process execution data. We focus on a motivating scenario in policing, where a criminal investigator will be augmented by smart devices to collect data and to identify devices around the investigation location, to communicate with them to understand and analyze evidence. We design and implement a system (namely iCOP, IoT-enabled COP) to assist investigators collect large amounts of evidence and dig for the facts in an easy way.

Includes members:
  Member "data curation apis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "social influence and radicalization a social data analytics study")
  Member "big data and cross document coreference resolution current state and future opportunities":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "curating social media data")
  Member "temporal provenance model tpm model and query language":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "curating social media data")
  Member "internet of things applications and challenges in technology and standardization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "machine learning for resource management in cellular and iot networks potentials current solutions and open challenges")

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.CR(Cryptography and Security)