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: "greening cloud enabled big data storage forensics syncany as a case study"
  Abstract: The pervasive nature of cloud-enabled big data storage solutions introduces new challenges in the identification, collection, analysis, preservation, and archiving of digital evidences. Investigation of such complex platforms to locate and recover traces of criminal activities is a time-consuming process. Hence, cyber forensics researchers are moving towards streamlining the investigation process by locating and documenting residual artefacts (evidences) of forensic value of users’ activities on cloud-enabled big data platforms in order to reduce the investigation time and resources involved in a real-world investigation. In this paper, we seek to determine the data remnants of forensic value from Syncany private cloud storage service, a popular storage engine for big data platforms. We demonstrate the types and the locations of the artifacts that can be forensically recovered. Findings from this research contribute to an in-depth understanding of cloud-enabled big data storage forensics, which can result in reduced time and resources spent in real-world investigations involving Syncany-based cloud platforms.

Connected through hyperedge HE-1 (induced by source paper "cloudme forensics a case of big data forensic investigation"):
  with members:
    - "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"
    - "a forensically sound adversary model for mobile devices"
    - "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-2 (induced by source paper "emerging from the cloud a bibliometric analysis of cloud forensics studies"):
  with members:
    - "internet of things security and forensics challenges and opportunities"
    - "forensic investigation of p2p cloud storage bittorrent sync as a case study"
    - "cloud storage forensics analysis of data remnants on spideroak justcloud and pcloud"
    - "a cyber kill chain based taxonomy of banking trojans for evolutionary computational intelligence"
    - "investigating storage as a service cloud platform pcloud as a case study"
    - "know abnormal find evil frequent pattern mining for ransomware threat hunting and intelligence"
    - "cloud storage forensic hubic as a case study"
    - "calm before the storm the challenges of cloud computing in digital forensics"

Connected through hyperedge HE-3 (induced by source paper "a model for android and ios applications risk calculation cvss analysis and enhancement using case control studies"):
  with members:
    - "internet of things security and forensics challenges and opportunities"
    - "mobile phone forensics an investigative framework based on user impulsivity and secure collaboration errors"
    - "a cyber kill chain based taxonomy of banking trojans for evolutionary computational intelligence"
    - "forensics analysis of android mobile voip apps"
    - "an android cloud storage apps forensic taxonomy"
    - "know abnormal find evil frequent pattern mining for ransomware threat hunting and intelligence"
    - "forensic investigation of social media and instant messaging services in firefox os facebook twitter google telegram openwapp and line as case studies"

Connected through hyperedge HE-4 (induced by source paper "leveraging machine learning techniques for windows ransomware network traffic detection"):
  with members:
    - "cloudme forensics a case of big data forensic investigation"
    - "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)