human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "vehicle security risk assessment in transportation"):
  Abstract: Intelligent Transportation Systems (ITS) are critical infrastructure that are not immune to both physical and cyber threats. Vehicles are cyber/physical systems which are a core component of ITS, will be either a target or a launching point for an attack on the ITS network. Unknown vehicle security vulnerabilities trigger a race among adversaries to exploit the weaknesses and security experts to mitigate the vulnerability. In this study we identified opportunities for adversaries to take control of the in-vehicle network which can compromise the safety, privacy, reliability, efficiency and security of the transportation system. We contribute to the knowledge in vehicular security by investigating the impact of hacking the in-vehicle network through a risk-based approach. For this purpose, we employ a risk-based model to conduct a qualitative vulnerability-oriented risk assessment.

Includes members:
  Member "inferring transportation modes from gps trajectories using a convolutional neural network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "how to eliminate detour behaviors in e hailing real time detecting and time dependent pricing")
  Member "viden attacker identification on in vehicle networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "tacan transmitter authentication through covert channels in controller area networks")
  Member "identifying ecus using inimitable characteristics of signals in controller area networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "network intrusion detection systems for in vehicle network technical report")

Question: Please tell me which class the source paper 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)