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: "highly secure physically unclonable cryptographic primitives using nonlinear conductance and analog state tuning in memristive crossbar arrays"
  Abstract: The rapidly expanding hardware-intrinsic security primitives are aimed at addressing significant security challenges of a massively interconnected world in the age of information technology. The main idea of such primitives is to employ instance-specific process-induced variations in electronic hardware as a source of cryptographic data. Among the emergent technologies, memristive devices provide unique opportunities for security applications due to the underlying stochasticity in their operation. Herein, we report a prototype of a robust, dense, and reconfigurable physical unclonable function primitives based on the three-dimensional passive metal-oxide memristive crossbar circuits, by making positive use of process-induced variations in the devices' nonlinear I-Vs and their analog tuning. We first characterize security metrics for a basic building block of the security primitives based on a two layer stack with monolithically integrated 10x10 250-nm half-pitch memristive crossbar circuits. The experimental results show that the average uniformity and diffusivity, measured on a random sample of 6,000 64-bit responses, out of ~697,000 total, is close to ideal 50% with 5% standard deviation for both metrics. The uniqueness, which was evaluated on a smaller sample by readjusting conductances of crosspoint devices within the same crossbar, is also close to the ideal 50% +/- 1%, while the smallest bit error rate, i.e. reciprocal of reliability, measured over 30-day window under +/-20% power supply variations, was ~ 1.5% +/- 1%. We then utilize multiple instances of the basic block to demonstrate physically unclonable functional primitive with 10-bit hidden challenge generation that encodes more than 10^19 challenge response pairs and has comparable uniformity, diffusiveness, and bit error rate.

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.ET(Emerging Technologies)