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 "physical layer authentication in mission critical mtc networks a security and delay performance analysis"):
  Abstract: We study the detection and delay performance impacts of a feature-based physical layer authentication (PLA) protocol in mission-critical machine-type communication (MTC) networks. The PLA protocol uses generalized likelihood-ratio testing based on the line-of-sight (LOS), single-input multiple-output channel-state information in order to mitigate impersonation attempts from an adversary node. We study the detection performance, develop a queueing model that captures the delay impacts of erroneous decisions in the PLA (i.e., the false alarms and missed detections), and model three different adversary strategies: data injection, disassociation, and Sybil attacks. Our main contribution is the derivation of analytical delay performance bounds that allow us to quantify the delay introduced by PLA that potentially can degrade the performance in mission-critical MTC networks. For the delay analysis, we utilize tools from stochastic network calculus. Our results show that with a sufficient number of receive antennas (approx. 4-8) and sufficiently strong LOS components from legitimate devices, PLA is a viable option for securing mission-critical MTC systems, despite the low latency requirements associated to corresponding use cases. Furthermore, we find that PLA can be very effective in detecting the considered attacks, and in particular, it can significantly reduce the delay impacts of disassociation and Sybil attacks.

Includes members:
  Member "application of machine learning for channel based message authentication in mission critical machine type communication":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "performance of statistical and machine learning techniques for physical layer authentication")
  Member "channel impulse response based distributed physical layer authentication":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the effective capacity of an underwater acoustic channel under impersonation attack")
  Member "physical layer authentication for mission critical machine type communication using gaussian mixture model based clustering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "putting things in context securing industrial authentication with context information")
  Member "secure transmission of delay sensitive data over wireless fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "effective capacity in wireless networks a comprehensive survey")
  Member "fingerprints in the ether using the physical layer for wireless authentication":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning aided physical layer attacks against multicarrier communications in iot")
  Member "using the physical layer for wireless authentication in time variant channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the effective capacity of an underwater acoustic channel under impersonation attack")

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)