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: "device fingerprinting in wireless networks challenges and opportunities"
  Abstract: Node forgery or impersonation, in which legitimate cryptographic credentials are captured by an adversary, constitutes one major security threat facing wireless networks. The fact that mobile devices are prone to be compromised and reverse engineered significantly increases the risk of such attacks in which adversaries can obtain secret keys on trusted nodes and impersonate the legitimate node. One promising approach toward thwarting these attacks is through the extraction of unique fingerprints that can provide a reliable and robust means for device identification. These fingerprints can be extracted from transmitted signal by analyzing information across the protocol stack. In this paper, the first unified and comprehensive tutorial in the area of wireless device fingerprinting for security applications is presented. In particular, we aim to provide a detailed treatment on developing novel wireless security solutions using device fingerprinting techniques. The objectives are three-fold: (i) to introduce a comprehensive taxonomy of wireless features that can be used in fingerprinting, (ii) to provide a systematic review on fingerprint algorithms including both white-list based and unsupervised learning approaches, and (iii) to identify key open research problems in the area of device fingerprinting and feature extraction, as applied to wireless security.

Connected through hyperedge HE-1 (induced by source paper "prifi low latency anonymity for organizational networks"):
  with members:
    - "taranet traffic analysis resistant anonymity at the network layer"
    - "i know what you saw last minute encrypted http adaptive video streaming title classification"
    - "the loopix anonymity system"
    - "atom horizontally scaling strong anonymity"
    - "riposte an anonymous messaging system handling millions of users"
    - "hornet high speed onion routing at the network layer"
    - "dovetail stronger anonymity in next generation internet routing"
    - "hang with your buddies to resist intersection attacks"

Connected through hyperedge HE-2 (induced by source paper "beyond the front page measuring third party dynamics in the field"):
  with members:
    - "missed by filter lists detecting unknown third party trackers with invisible pixels"
    - "un informed consent studying gdpr consent notices in the field"
    - "the chain of implicit trust an analysis of the web third party resources loading"
    - "tranco a research oriented top sites ranking hardened against manipulation"
    - "digging into browser based crypto mining"
    - "we value your privacy now take some cookies measuring the gdpr s impact on web privacy"
    - "http cookies standards privacy and politics"

Connected through hyperedge HE-3 (induced by source paper "handoff all your privacy a review of apple s bluetooth low energy continuity protocol"):
  with members:
    - "sundials in the shade an internet wide perspective on icmp timestamps"
    - "easy 4g lte imsi catchers for non programmers"
    - "a study of mac address randomization in mobile devices and when it fails"
    - "passive taxonomy of wifi clients using mlme frame contents"
    - "tracking human mobility using wifi signals"
    - "an empirical study of passive 802 11 device fingerprinting"

Connected through hyperedge HE-4 (induced by source paper "start making sense semantic plane filtering and control for post 5g connectivity"):
  with members:
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "federated learning via over the air computation"
    - "a very brief introduction to machine learning with applications to communication systems"
    - "towards an intelligent edge wireless communication meets machine learning"
    - "millimeter wave vehicular communication to support massive automotive sensing"
    - "compute and forward harnessing interference through structured codes"

Connected through hyperedge HE-5 (induced by source paper "semantic effectiveness filtering and control for post 5g wireless connectivity"):
  with members:
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "on unified vehicular communications and radar sensing in millimeter wave and low terahertz bands"
    - "a very brief introduction to machine learning with applications to communication systems"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "towards an intelligent edge wireless communication meets machine learning"
    - "federated optimization distributed machine learning for on device intelligence"

Connected through hyperedge HE-6 (induced by source paper "deepradioid real time channel resilient optimization of deep learning based radio fingerprinting algorithms"):
  with members:
    - "big data goes small real time spectrum driven embedded wireless networking through deep learning in the rf loop"
    - "machine learning for wireless communications in the internet of things a comprehensive survey"
    - "securing the internet of things in the age of machine learning and software defined networking"
    - "deep learning based dynamic watermarking for secure signal authentication in the internet of things"
    - "cudnn efficient primitives for deep learning"

Connected through hyperedge HE-7 (induced by source paper "a light weight authentication scheme for air force internet of things"):
  with members:
    - "internet of things security and forensics challenges and opportunities"
    - "usbee air gap covert channel via electromagnetic emission from usb"
    - "internet of things iot a vision architectural elements and future directions"
    - "using the physical layer for wireless authentication in time variant channels"

Connected through hyperedge HE-8 (induced by source paper "pinch an effective efficient and robust solution to drone detection via network traffic analysis"):
  with members:
    - "machine learning based delay aware uav detection and operation mode identification over encrypted wi fi traffic"
    - "key technologies and system trade offs for detection and localization of amateur drones"
    - "flight dynamics based recovery of a uav trajectory using ground cameras"

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.NI(Networking and Internet Architecture)