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: "enhanced position verification for vanets using subjective logic"
  Abstract: The integrity of messages in vehicular ad-hoc networks has been extensively studied by the research community, resulting in the IEEE&#126;1609.2 standard, which provides typical integrity guarantees. However, the correctness of message contents is still one of the main challenges of applying dependable and secure vehicular ad-hoc networks. One important use case is the validity of position information contained in messages: position verification mechanisms have been proposed in the literature to provide this functionality. A more general approach to validate such information is by applying misbehavior detection mechanisms. In this paper, we consider misbehavior detection by enhancing two position verification mechanisms and fusing their results in a generalized framework using subjective logic. We conduct extensive simulations using VEINS to study the impact of traffic density, as well as several types of attackers and fractions of attackers on our mechanisms. The obtained results show the proposed framework can validate position information as effectively as existing approaches in the literature, without tailoring the framework specifically for this use case.

Connected through hyperedge HE-1 (induced by source paper "securing vehicle to everything v2x communication platforms"):
  with members:
    - "survey on misbehavior detection in cooperative intelligent transportation systems"
    - "a security credential management system for v2x communications"
    - "security in automotive networks lightweight authentication and authorization"
    - "analyzing attacks on cooperative adaptive cruise control cacc"
    - "cyber physical systems security a survey"
    - "efficient detection of sybil attack based on cryptography in vanet"
    - "secure vehicular communication systems implementation performance and research challenges"

Connected through hyperedge HE-2 (induced by source paper "survey on misbehavior detection in cooperative intelligent transportation systems"):
  with members:
    - "a security credential management system for v2x communications"
    - "veremi a dataset for comparable evaluation of misbehavior detection in vanets"
    - "analyzing attacks on cooperative adaptive cruise control cacc"
    - "secmace scalable and robust identity and credential management infrastructure in vehicular communication systems"
    - "survey of important issues in uav communication networks"
    - "data centric misbehavior detection in vanets"
    - "secure vehicular communication systems implementation performance and research challenges"
    - "secure vehicular communication systems design and architecture"

Connected through hyperedge HE-3 (induced by source paper "context aware misbehavior detection scheme for vehicular ad hoc networks using sequential analysis of the temporal and spatial correlation of the cooperative awareness messages"):
  with members:
    - "survey on misbehavior detection in cooperative intelligent transportation systems"

Connected through hyperedge HE-4 (induced by source paper "veremi a dataset for comparable evaluation of misbehavior detection in vanets"):
  with members:
    - "survey on misbehavior detection in cooperative intelligent transportation systems"
    - "analyzing attacks on cooperative adaptive cruise control cacc"

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)