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: "safe d self attestation for networks of heterogeneous embedded devices"
  Abstract: The Internet of Things (IoT) is an emerging paradigm that allows a fine-grained and autonomous control of the surrounding environment. This is achieved through a large number of devices that collaboratively perform complex tasks. To date, IoT networks are used in a variety of critical scenarios and therefore their security has become a primary concern. A robust technique to enhance the integrity of remote devices is called Remote Attestation (RA). However, classic RA schemes require a central and powerful entity, called Verifier, that manages the entire process of attestation. This makes the entire system dependent on an external entity and inevitably introduces a single point of failure. #R##N#In our work, we present SAFE^d: the first concrete solution to self-attest autonomous networks of heterogeneous embedded devices. SAFE d overcomes the limitations of the previous works by spreading the duties of the Verifier among all the devices in a scalable way. In our schema, the information needed for the attestation phase is replicated inside the network, thus raising the bar to accomplish an attack. As a result, the IoT network can self-inspect its integrity and self-recover in case of attack, without the need of an external entity. Our proposal exploits the security guarantees offered by ARM TrustZone chips to perform a decentralized attestation protocol based on an enhanced version of a distributed hash table. #R##N#We implemented a prototype of SAFE d for the Raspberry Pi platform to evaluate the feasibility and the security properties of our protocol. Moreover, we measured the scalable properties of SAFE d by using a large network of virtual devices. The results show that SAFE d can detect infected devices and recover up to 99.7% of its initial status in case of faults or attacks. Moreover, we managed to protect 50 devices with a logarithmic overhead on the network and the devices' memory.

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)