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 "real time index authentication for event oriented surveillance video query using blockchain"):
  Abstract: Information from surveillance video is essential for situational awareness (SAW). Nowadays, a prohibitively large amount of surveillance data is being generated continuously by ubiquitously distributed video sensors. It is very challenging to immediately identify the objects of interest or zoom in suspicious actions from thousands of video frames. Making the big data indexable is critical to tackle this problem. It is ideal to generate pattern indexes in a real-time, on-site manner on the video streaming instead of depending on the batch processing at the cloud centers. The modern edge-fog-cloud computing paradigm allows implementation of time sensitive tasks at the edge of the network. The on-site edge devices collect the information sensed in format of frames and extracts useful features. The near-site fog nodes conduct the contextualization and classification of the features. The remote cloud center is in charge of more data intensive and computing intensive tasks. However, exchanging the index information among devices in different layers raises security concerns where an adversary can capture or tamper with features to mislead the surveillance system. In this paper, a blockchain enabled scheme is proposed to protect the index data through an encrypted secure channel between the edge and fog nodes. It reduces the chance of attacks on the small edge and fog devices. The feasibility of the proposal is validated through intensive experimental analysis.

Includes members:
  Member "fog computing a taxonomy survey and future directions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "efficient 3d road map data exchange for intelligent vehicles in vehicular fog networks")
  Member "smart surveillance as an edge network service from harr cascade svm to a lightweight cnn":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "machine learning at the network edge a survey")
  Member "smart contract based access control for the internet of things":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "scaling blockchains to support electronic health records for hospital systems")
  Member "real time human detection as an edge service enabled by a lightweight cnn":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "i safe instant suspicious activity identification at the edge using fuzzy decision making")
  Member "an edge fog cloud platform for anticipatory learning process designed for internet of mobile things":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "decentralized smart surveillance through microservices platform")
  Member "mobilenets efficient convolutional neural networks for mobile vision applications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "discrimination aware network pruning for deep model compression")
  Member "fully convolutional siamese networks for object tracking":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "siamese attentional keypoint network for high performance visual tracking")
  Member "learning to track at 100 fps with deep regression networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "object adaptive lstm network for real time visual tracking with adversarial data augmentation")

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.DC(Distributed, Parallel, and Cluster Computing)