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 "hiding communications in awgn channels and thz band with interference uncertainty"):
  Abstract: Covert communication can prevent an adversary from knowing that a wireless transmission has occurred. In additive white Gaussian noise (AWGN) channels, a square root law is found that Alice can reliably and covertly transmit $\mathcal{O}(\sqrt{n})$ bits to Bob in $n$ channel uses. In this paper, we consider covert communications in noisy wireless networks, where the receivers not only experience the background noise, but also the aggregate interference from other transmitters. Our results show that uncertainty in interference experienced by the adversary Willie is beneficial to Alice. In AWGN channels, when the distance between Alice and Willie $d_{a,w}=\omega(n^{1/(2\alpha)})$ ($\alpha$ is the path loss exponent), Alice can reliably and covertly transmit $\mathcal{O}(\log_2\sqrt{n})$ bits to Bob in $n$ channel uses. Although the covert throughput is lower than the square root law, the spatial throughput is higher. In THz (Terahertz) Band networks,covert communication is more difficult because Willie can simply place a receiver in the narrow beam between Alice and Bob to detect or block their LOS (Line-of-Sight) communications. We then present a covert communication scheme that utilizes the reflection or diffuse scattering from a rough surface to prevent being detected by Willie. From the network perspective, the communications are hidden in the interference of noisy wireless networks, and what Willie sees is merely a "shadow" wireless network.

Includes members:
  Member "covert wireless communication with artificial noise generation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "finite blocklength analysis of gaussian random coding in awgn channels under covert constraints ii a viewpoint of total variation distance")
  Member "on covert communication with noise uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "finite blocklength analysis of gaussian random coding in awgn channels under covert constraints ii a viewpoint of total variation distance")
  Member "fundamental limits of communication with low probability of detection":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "keyless covert communication via channel state information")
  Member "covert communication in the presence of an uninformed jammer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi antenna jamming in covert communication")
  Member "covert communication over noisy channels a resolvability perspective":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "keyless covert communication via channel state information")
  Member "covert single hop communication in a wireless network with distributed artificial noise generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "challenges in covert wireless communications with active warden on awgn channels")
  Member "limits of reliable communication with low probability of detection on awgn channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "keyless covert communication via channel state information")
  Member "applications of stochastic ordering to wireless communications":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "transmit power policy and ergodic multicast rate analysis of cognitive radio networks in generalized fading")

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)