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: "the group element of cybercrime types dynamics and criminal operations"
  Abstract: While cybercrime can often be an individual activity pursued by lone hackers, it has increasingly grown into a group activity, with networks across the world. This chapter critically examines the group element of cybercrime from several perspectives. It identifies the platforms that online groups - cybercriminal and otherwise - use to interact, and considers groups as both perpetrators and victims of cybercrime. A key novelty is the discovery of new types of online groups whose collective actions border on criminality. The chapter also analyzes how online cybercrime groups form, organize, and operate. It explores issues such as trust, motives, and means, and draws on several poignant examples, from Anonymous to LulzSec, to illustrate the arguments.

Connected through hyperedge HE-1 (induced by source paper "the social and psychological impact of cyber attacks"):
  with members:
    - "cyber security awareness campaigns why do they fail to change behaviour"
    - "cybercrime and you how criminals attack and the human factors that they seek to exploit"
    - "privacy is the boring bit user perceptions and behaviour in the internet of things"
    - "security risk assessment in internet of things systems"

Connected through hyperedge HE-2 (induced by source paper "cybercrime investigators are users too understanding the socio technical challenges faced by law enforcement"):
  with members:
    - "cybercrime and you how criminals attack and the human factors that they seek to exploit"
    - "current challenges and future research areas for digital forensic investigation"

Connected through hyperedge HE-3 (induced by source paper "cybercrime and you how criminals attack and the human factors that they seek to exploit"):
  with members:
    - "privacy is the boring bit user perceptions and behaviour in the internet of things"
    - "stealing pins via mobile sensors actual risk versus user perception"

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.CR(Cryptography and Security)