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: "automated inference of past action instances in digital investigations"
  Abstract: As the amount of digital devices suspected of containing digital evidence increases, case backlogs for digital investigations are also increasing in many organizations. To ensure timely investigation of requests, this work proposes the use of signature-based methods for automated action instance approximation to automatically reconstruct past user activities within a compromised or suspect system. This work specifically explores how multiple instances of a user action may be detected using signature-based methods during a postmortem digital forensic analysis. A system is formally defined as a set of objects, where a subset of objects may be altered on the occurrence of an action. A novel action-trace update time threshold is proposed that enables objects to be categorized by their respective update patterns over time. By integrating time into event reconstruction, the most recent action instance approximation as well as limited past instances of the action may be differentiated and their time values approximated. After the formal theory if signature-based event reconstruction is defined, a case study is given to evaluate the practicality of the proposed method.

Connected through hyperedge HE-1 (induced by source paper "hierarchical bloom filter trees for approximate matching"):
  with members:
    - "battling the digital forensic backlog through data deduplication"

Connected through hyperedge HE-2 (induced by source paper "update thresholds of more accurate time stamp for event reconstruction"):
  with members:
    - "signature based detection of user events for post mortem forensic analysis"

Connected through hyperedge HE-3 (induced by source paper "battling the digital forensic backlog through data deduplication"):
  with members:
    - "increasing digital investigator availability through efficient workflow management and automation"
    - "current challenges and future research areas for digital forensic investigation"
    - "tiered forensic methodology model for digital field triage by non digital evidence specialists"
    - "leveraging decentralization to extend the digital evidence acquisition window case study on bittorrent sync"

Connected through hyperedge HE-4 (induced by source paper "tiered forensic methodology model for digital field triage by non digital evidence specialists"):
  with members:
    - "forensics in industrial control system a case study"
    - "towards the forensic identification and investigation of cloud hosted servers through non invasive wiretaps"

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)