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: "the circle game scalable private membership test using trusted hardware"
  Abstract: Malware checking is changing from being a local service to a cloud-assisted one where users' devices query a cloud server, which hosts a dictionary of malware signatures, to check if particular applications are potentially malware. Whilst such an architecture gains all the benefits of cloud-based services, it opens up a major privacy concern since the cloud service can infer personal traits of the users based on the lists of applications queried by their devices. Private membership test (PMT) schemes can remove this privacy concern. However, known PMT schemes do not scale well to a large number of simultaneous users and high query arrival rates. We propose a simple PMT approach using a carousel: circling the entire dictionary through trusted hardware on the cloud server. Users communicate with the trusted hardware via secure channels. We show how the carousel approach, using different data structures to represent the dictionary, can be realized on two different commercial hardware security architectures (ARM TrustZone and Intel SGX). We highlight subtle aspects of securely implementing seemingly simple PMT schemes on these architectures. Through extensive experimental analysis, we show that for the malware checking scenario our carousel approach surprisingly outperforms Path ORAM on the same hardware by supporting a much higher query arrival rate while guaranteeing acceptable response latency for individual queries.

Connected through hyperedge HE-1 (induced by source paper "sgxpectre stealing intel secrets from sgx enclaves via speculative execution"):
  with members:
    - "netspectre read arbitrary memory over network"
    - "spectre returns speculation attacks using the return stack buffer"
    - "ret2spec speculative execution using return stack buffers"
    - "software grand exposure sgx cache attacks are practical"
    - "sgxio generic trusted i o path for intel sgx"
    - "malware guard extension using sgx to conceal cache attacks"
    - "a software approach to defeating side channels in last level caches"
    - "inferring fine grained control flow inside sgx enclaves with branch shadowing"

Connected through hyperedge HE-2 (induced by source paper "pdot private dns over tls with tee support"):
  with members:
    - "s faas trustworthy and accountable function as a service using intel sgx"
    - "integrating remote attestation with transport layer security"
    - "the pyramid scheme oblivious ram for trusted processors"
    - "lightbox full stack protected stateful middlebox at lightning speed"
    - "towards plugging privacy leaks in domain name system"

Connected through hyperedge HE-3 (induced by source paper "detecting stuffing of a user s credentials at her own accounts"):
  with members:
    - "protocols for checking compromised credentials"

Connected through hyperedge HE-4 (induced by source paper "securing input data of deep learning inference systems via partitioned enclave execution"):
  with members:
    - "grad cam visual explanations from deep networks via gradient based localization"
    - "privynet a flexible framework for privacy preserving deep neural network training"
    - "chiron privacy preserving machine learning as a service"
    - "mlcapsule guarded offline deployment of machine learning as a service"
    - "efficient deep learning on multi source private data"
    - "opening the black box of deep neural networks via information"
    - "squeezenet alexnet level accuracy with 50x fewer parameters and 0 5mb model size"
    - "software grand exposure sgx cache attacks are practical"

Connected through hyperedge HE-5 (induced by source paper "reaching data confidentiality and model accountability on the caltrain"):
  with members:
    - "contamination attacks and mitigation in multi party machine learning"
    - "exploiting unintended feature leakage in collaborative learning"
    - "chiron privacy preserving machine learning as a service"
    - "how to backdoor federated learning"
    - "efficient deep learning on multi source private data"
    - "mitigating sybils in federated learning poisoning"
    - "securing input data of deep learning inference systems via partitioned enclave execution"
    - "badnets identifying vulnerabilities in the machine learning model supply chain"

Connected through hyperedge HE-6 (induced by source paper "yerbabuena securing deep learning inference data via enclave based ternary model partitioning"):
  with members:
    - "grad cam visual explanations from deep networks via gradient based localization"
    - "chiron privacy preserving machine learning as a service"
    - "mlcapsule guarded offline deployment of machine learning as a service"
    - "efficient deep learning on multi source private data"
    - "opening the black box of deep neural networks via information"
    - "hardidx practical and secure index with sgx"
    - "stealing machine learning models via prediction apis"
    - "communication efficient learning of deep networks from decentralized data"

Connected through hyperedge HE-7 (induced by source paper "keys in the clouds auditable multi device access to cryptographic credentials"):
  with members:
    - "safekeeper protecting web passwords using trusted execution environments"
    - "intel sgx enabled key manager service with openstack barbican"
    - "inferring fine grained control flow inside sgx enclaves with branch shadowing"

Connected through hyperedge HE-8 (induced by source paper "migrating sgx enclaves with persistent state"):
  with members:
    - "inferring fine grained control flow inside sgx enclaves with branch shadowing"
    - "teechan payment channels using trusted execution environments"

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)