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: "cloudme forensics a case of big data forensic investigation"
  Abstract: The significant increase in the volume, variety and velocity of data complicates cloud forensic efforts, as such big data will, at some point, become computationally expensive to be fully extracted and analyzed in a timely manner. Thus, it is important for a digital forensic practitioner to have a well-rounded knowledge about the most relevant data artefacts that could be forensically recovered from the cloud product under investigation. In this paper, CloudMe, a popular cloud storage service, is studied. The types and locations of the artefacts relating to the installation and uninstallation of the client application, logging in and out, and file synchronization events from the computer desktop and mobile clients are described. Findings from this research will pave the way towards the development of tools and techniques (e.g. data mining techniques) for cloud-enabled big data endpoint forensics investigation.

Connected through hyperedge HE-1 (induced by source paper "enabling trust in deep learning models a digital forensics case study"):
  with members:
    - "threat of adversarial attacks on deep learning in computer vision a survey"
    - "large scale jpeg image steganalysis using hybrid deep learning framework"
    - "autoencoder with recurrent neural networks for video forgery detection"
    - "attacking automatic video analysis algorithms a case study of google cloud video intelligence api"
    - "axiomatic attribution for deep networks"
    - "unsupervised machine learning for networking techniques applications and research challenges"
    - "transferability in machine learning from phenomena to black box attacks using adversarial samples"
    - "tiered forensic methodology model for digital field triage by non digital evidence specialists"

Connected through hyperedge HE-2 (induced by source paper "leveraging machine learning techniques for windows ransomware network traffic detection"):
  with members:
    - "greening cloud enabled big data storage forensics syncany as a case study"
    - "a cyber kill chain based taxonomy of banking trojans for evolutionary computational intelligence"
    - "know abnormal find evil frequent pattern mining for ransomware threat hunting and intelligence"
    - "exploit kits the production line of the cybercrime economy"
    - "automated dynamic analysis of ransomware benefits limitations and use for detection"
    - "automated detection and classification of cryptographic algorithms in binary programs through machine learning"

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)