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: "a forensically sound adversary model for mobile devices"
  Abstract: In this paper, we propose an adversary model to facilitate forensic investigations of mobile devices (e.g. Android, iOS and Windows smartphones) that can be readily adapted to the latest mobile device technologies. This is essential given the ongoing and rapidly changing nature of mobile device technologies. An integral principle and significant constraint upon forensic practitioners is that of forensic soundness. Our adversary model specifically considers and integrates the constraints of forensic soundness on the adversary, in our case, a forensic practitioner. One construction of the adversary model is an evidence collection and analysis methodology for Android devices. Using the methodology with six popular cloud apps, we were successful in extracting various information of forensic interest in both the external and internal storage of the mobile device.

Connected through hyperedge HE-1 (induced by source paper "greening cloud enabled big data storage forensics syncany as a case study"):
  with members:
    - "digital forensic investigation of cloud storage services"
    - "network traffic forensics on firefox mobile os facebook twitter and telegram as case studies"
    - "windows instant messaging app forensics facebook and skype as case studies"
    - "cloud storage forensic hubic as a case study"
    - "leveraging decentralization to extend the digital evidence acquisition window case study on bittorrent sync"
    - "bittorrent sync first impressions and digital forensic implications"
    - "bittorrent sync network investigation methodology"

Connected through hyperedge HE-2 (induced by source paper "cloudme forensics a case of big data forensic investigation"):
  with members:
    - "greening cloud enabled big data storage forensics syncany as a case study"
    - "forensic investigation of p2p cloud storage bittorrent sync as a case study"
    - "cloud storage forensics analysis of data remnants on spideroak justcloud and pcloud"
    - "digital forensic investigation of cloud storage services"
    - "windows instant messaging app forensics facebook and skype as case studies"
    - "cloud storage forensic hubic as a case study"
    - "leveraging decentralization to extend the digital evidence acquisition window case study on bittorrent sync"
    - "bittorrent sync first impressions and digital forensic implications"

Connected through hyperedge HE-3 (induced by source paper "forensics analysis of android mobile voip apps"):
  with members:
    - "windows instant messaging app forensics facebook and skype as case studies"
    - "on the feasibility of attribute based encryption on smartphone devices"
    - "forensic taxonomy of popular android mhealth apps"
    - "mobile cloud forensics an analysis of seven popular android apps"
    - "conceptual evidence collection and analysis methodology for android devices"
    - "privacy risks in mobile dating apps"
    - "forensic analysis of whatsapp messenger on android smartphones"
    - "can t you hear me knocking identification of user actions on android apps via traffic analysis"

Connected through hyperedge HE-4 (induced by source paper "investigating america online instant messaging application data remnants on windows 8 1 client machine"):
  with members:
    - "forensic taxonomy of popular android mhealth apps"
    - "privacy risks in mobile dating apps"

Connected through hyperedge HE-5 (induced by source paper "mobile phone forensics an investigative framework based on user impulsivity and secure collaboration errors"):
  with members:
    - "windows instant messaging app forensics facebook and skype as case studies"

Connected through hyperedge HE-6 (induced by source paper "windows instant messaging app forensics facebook and skype as case studies"):
  with members:
    - "forensics acquisition and analysis of instant messaging and voip applications"
    - "forensic taxonomy of popular android mhealth apps"
    - "privacy risks in mobile dating apps"
    - "an analysis of the skype peer to peer internet telephony protocol"

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)