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 heisenberg defense proactively defending sgx enclaves against page table based side channel attacks"
  Abstract: Protected-module architectures (PMAs) have been proposed to provide strong isolation guarantees, even on top of a compromised system. Unfortunately, Intel SGX -- the only publicly available high-end PMA -- has been shown to only provide limited isolation. An attacker controlling the untrusted page tables, can learn enclave secrets by observing its page access patterns. #R##N#Fortifying existing protected-module architectures in a real-world setting against side-channel attacks is an extremely difficult task as system software (hypervisor, operating system, ...) needs to remain in full control over the underlying hardware. Most state-of-the-art solutions propose a reactive defense that monitors for signs of an attack. Such approaches unfortunately cannot detect the most novel attacks, suffer from false-positives, and place an extraordinary heavy burden on enclave-developers when an attack is detected. #R##N#We present Heisenberg, a proactive defense that provides complete protection against page table based side channels. We guarantee that any attack will either be prevented or detected automatically before {\em any} sensitive information leaks. Consequently, Heisenberg can always securely resume enclave execution -- even when the attacker is still present in the system. #R##N#We present two implementations. Heisenberg-HW relies on very limited hardware features to defend against page-table-based attacks. We use the x86/SGX platform as an example, but the same approach can be applied when protected-module architectures are ported to different platforms as well. #R##N#Heisenberg-SW avoids these hardware modifications and can readily be applied. Unfortunately, it's reliance on Intel Transactional Synchronization Extensions (TSX) may lead to significant performance overhead under real-life conditions.

Connected through hyperedge HE-1 (induced by source paper "copycat controlled instruction level attacks on enclaves for maximal key extraction"):
  with members:
    - "tpm fail tpm meets timing and lattice attacks"
    - "dr sgx automated and adjustable side channel protection for sgx using data location randomization"
    - "sgxpectre stealing intel secrets from sgx enclaves via speculative execution"
    - "hybcache hybrid side channel resilient caches for trusted execution environments"
    - "mitigating branch shadowing attacks on intel sgx using control flow randomization"
    - "microwalk a framework for finding side channels in binaries"
    - "cachezoom how sgx amplifies the power of cache attacks"
    - "software grand exposure sgx cache attacks are practical"

Connected through hyperedge HE-2 (induced by source paper "a systematic evaluation of transient execution attacks and defenses"):
  with members:
    - "smotherspectre exploiting speculative execution through port contention"
    - "spoiler speculative load hazards boost rowhammer and cache attacks"
    - "speculative buffer overflows attacks and defenses"
    - "netspectre read arbitrary memory over network"
    - "safespec banishing the spectre of a meltdown with leakage free speculation"
    - "spectector principled detection of speculative information flows"
    - "spectre attacks exploiting speculative execution"
    - "you shall not bypass employing data dependencies to prevent bounds check bypass"

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)