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: "hardidx practical and secure index with sgx"
  Abstract: Software-based approaches for search over encrypted data are still either challenged by lack of proper, low-leakage encryption or slow performance. Existing hardware-based approaches do not scale well due to hardware limitations and software designs that are not specifically tailored to the hardware architecture, and are rarely well analyzed for their security (e.g., the impact of side channels). Additionally, existing hardware-based solutions often have a large code footprint in the trusted environment susceptible to software compromises. In this paper we present HardIDX: a hardware-based approach, leveraging Intel's SGX, for search over encrypted data. It implements only the security critical core, i.e., the search functionality, in the trusted environment and resorts to untrusted software for the remainder. HardIDX is deployable as a highly performant encrypted database index: it is logarithmic in the size of the index and searches are performed within a few milliseconds rather than seconds. We formally model and prove the security of our scheme showing that its leakage is equivalent to the best known searchable encryption schemes. Our implementation has a very small code and memory footprint yet still scales to virtually unlimited search index sizes, i.e., size is limited only by the general - non-secure - hardware resources.

Connected through hyperedge HE-1 (induced by source paper "encdbdb searchable encrypted fast compressed in memory database using enclaves"):
  with members:
    - "an efficiently searchable encrypted data structure for range queries"
    - "stealthdb a scalable encrypted database with full sql query support"
    - "software grand exposure sgx cache attacks are practical"
    - "zerodb white paper"
    - "oblivious query processing"

Connected through hyperedge HE-2 (induced by source paper "accelerating forward and backward private searchable encryption using trusted execution"):
  with members:
    - "dr sgx automated and adjustable side channel protection for sgx using data location randomization"
    - "software grand exposure sgx cache attacks are practical"
    - "lightbox full stack protected stateful middlebox at lightning speed"

Connected through hyperedge HE-3 (induced by source paper "dr sgx automated and adjustable side channel protection for sgx using data location randomization"):
  with members:
    - "sgxpectre stealing intel secrets from sgx enclaves via speculative execution"
    - "hybcache hybrid side channel resilient caches for trusted execution environments"
    - "spectre attacks exploiting speculative execution"
    - "lazyfp leaking fpu register state using microarchitectural side channels"
    - "cachezoom how sgx amplifies the power of cache attacks"
    - "software grand exposure sgx cache attacks are practical"
    - "malware guard extension using sgx to conceal cache attacks"
    - "stacco differentially analyzing side channel traces for detecting ssl tls vulnerabilities in secure enclaves"

Connected through hyperedge HE-4 (induced by source paper "authenticated key value stores with hardware enclaves"):
  with members:
    - "software grand exposure sgx cache attacks are practical"
    - "blockbench a framework for analyzing private blockchains"
    - "inferring fine grained control flow inside sgx enclaves with branch shadowing"

Connected through hyperedge HE-5 (induced by source paper "enjoy the untrusted cloud a secure scalable and efficient sql like query framework for outsourcing data"):
  with members:
    - "interface based side channel attack against intel sgx"
    - "inferring fine grained control flow inside sgx enclaves with branch shadowing"

Connected through hyperedge HE-6 (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"
    - "the circle game scalable private membership test using trusted hardware"
    - "opening the black box of deep neural networks via information"
    - "squeezenet alexnet level accuracy with 50x fewer parameters and 0 5mb model size"

Connected through hyperedge HE-7 (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"
    - "the circle game scalable private membership test using trusted hardware"

Connected through hyperedge HE-8 (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"
    - "the circle game scalable private membership test using trusted hardware"
    - "opening the black box of deep neural networks via information"
    - "stealing machine learning models via prediction apis"
    - "communication efficient learning of deep networks from decentralized data"

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)