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 multi dimensional approach towards intrusion detection system"
  Abstract: In this paper, we suggest a multi-dimensional approach towards intrusion detection. Network and system usage parameters like source and destination IP addresses; source and destination ports; incoming and outgoing network traffic data rate and number of CPU cycles per request are divided into multiple dimensions. Rather than analyzing raw bytes of data corresponding to the values of the network parameters, a mature function is inferred during the training phase for each dimension. This mature function takes a dimension value as an input and returns a value that represents the level of abnormality in the system usage with respect to that dimension. This mature function is referred to as Individual Anomaly Indicator. Individual Anomaly Indicators recorded for each of the dimensions are then used to generate a Global Anomaly Indicator, a function with n variables (n is the number of dimensions) that provides the Global Anomaly Factor, an indicator of anomaly in the system usage based on all the dimensions considered together. The Global Anomaly Indicator inferred during the training phase is then used to detect anomaly in the network traffic during the detection phase. Network traffic data encountered during the detection phase is fed back to the system to improve the maturity of the Individual Anomaly Indicators and hence the Global Anomaly Indicator.

Connected through hyperedge HE-1 (induced by source paper "secure management of logs in internet of things"):
  with members:
    - "survey of operating systems for the iot environment"
    - "authentication systems in internet of things"
    - "rism reputation based intrusion detection system for mobile ad hoc networks"
    - "inter cloud data security strategies"
    - "detection and prevention of botnets and malware in an enterprise network"
    - "cloud computing an approach with modern cryptography"
    - "a hybrid approach towards intrusion detection based on artificial immune system and soft computing"
    - "a semi distributed reputation based intrusion detection system for mobile adhoc networks"

Connected through hyperedge HE-2 (induced by source paper "application of multi factor authentication in internet of things domain"):
  with members:
    - "detection and prevention of botnets and malware in an enterprise network"
    - "a multi factor security protocol for wireless payment secure web authentication using mobile devices"
    - "embedding secret data in html web page"
    - "data hiding techniques using prime and natural numbers"
    - "voice recognition algorithms using mel frequency cepstral coefficient mfcc and dynamic time warping dtw techniques"
    - "a semi distributed reputation based intrusion detection system for mobile adhoc networks"

Connected through hyperedge HE-3 (induced by source paper "monitoring in iot enabled devices"):
  with members:
    - "survey of operating systems for the iot environment"
    - "authentication systems in internet of things"
    - "rism reputation based intrusion detection system for mobile ad hoc networks"
    - "a hybrid approach towards intrusion detection based on artificial immune system and soft computing"
    - "a semi distributed reputation based intrusion detection system for mobile adhoc networks"

Connected through hyperedge HE-4 (induced by source paper "increasing security in cloud environment"):
  with members:
    - "rism reputation based intrusion detection system for mobile ad hoc networks"
    - "detection and prevention of botnets and malware in an enterprise network"
    - "a paxos based state machine replication system for anomaly detection"
    - "a hybrid approach towards intrusion detection based on artificial immune system and soft computing"
    - "a survey on security issues in cloud computing"
    - "a new trusted and collaborative agent based approach for ensuring cloud security"
    - "grid security and integration with minimal performance degradation"
    - "embedding secret data in html web page"

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)