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: "an efficient privacy preserving algorithm based on randomized response in iot based smart grid"
  Abstract: Among existing privacy-preserving approaches, Differential Privacy (DP) is a powerful tool that can provide privacy-preserving noisy query answers over statistical databases and has been widely adopted in many practical fields. In particular, as a privacy machine of DP, Randomized Aggregable Privacy-Preserving Ordinal Response (RAPPOR) enables strong privacy, efficient, and high-utility guarantees for each client string in data crowdsourcing. However, as for Internet of Things(IoT), such as smart gird, data are often processed in batches. Therefore, developing a new random response algorithm that can support batch-processing tend to make it more efficient and suitable for IoT applications than existing random response algorithms. In this paper, we propose a new randomized response algorithm that can achieve differential-privacy and utility guar-antees for consumer's behaviors, and process a batch of data at each time. Firstly, by applying sparse coding in this algorithm, a behavior signature dictionary is created from the aggregated energy consumption data in fog. Then, we add noise into the behavior signature dictionary by classical randomized response techniques and achieve the differential privacy after data re-aggregation. Through the security analysis with the principle of differential privacy and experimental results verification, we find that our Algorithm can preserve consumer's privacy with-out comprising utility.

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.CR(Cryptography and Security)