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: "capacity of non malleable codes"
  Abstract: Non-malleable codes, introduced by Dziembowski, Pietrzak and Wichs (ICS 2010), encode messages $s$ in a manner so that tampering the codeword causes the decoder to either output $s$ or a message that is independent of $s$. While this is an impossible goal to achieve against unrestricted tampering functions, rather surprisingly non-malleable coding becomes possible against every fixed family $F$ of tampering functions that is not too large (for instance, when $|F| \le \exp(2^{\alpha n})$ for some $\alpha \in [0, 1)$ where $n$ is the number of bits in a codeword). #R##N#In this work, we study the "capacity of non-malleable coding", and establish optimal bounds on the achievable rate as a function of the family size, answering an open problem from Dziembowski et al. (ICS 2010). Specifically, #R##N#1. We prove that for every family $F$ with $|F| \le \exp(2^{\alpha n})$, there exist non-malleable codes against $F$ with rate arbitrarily close to $1-\alpha$ (this is achieved w.h.p. by a randomized construction). #R##N#2. We show the existence of families of size $\exp(n^{O(1)} 2^{\alpha n})$ against which there is no non-malleable code of rate $1-\alpha$ (in fact this is the case w.h.p for a random family of this size). #R##N#3. We also show that $1-\alpha$ is the best achievable rate for the family of functions which are only allowed to tamper the first $\alpha n$ bits of the codeword, which is of special interest. #R##N#As a corollary, this implies that the capacity of non-malleable coding in the split-state model (where the tampering function acts independently but arbitrarily on the two halves of the codeword) equals 1/2. #R##N#We also give an efficient Monte Carlo construction of codes of rate close to 1 with polynomial time encoding and decoding that is non-malleable against any fixed $c > 0$ and family $F$ of size $\exp(n^c)$, in particular tampering functions with, say, cubic size circuits.

Connected through hyperedge HE-1 (induced by source paper "improved non malleable extractors non malleable codes and independent source extractors"):
  with members:
    - "explicit non malleable extractors multi source extractors and almost optimal privacy amplification protocols"
    - "explicit resilient functions matching ajtai linial"
    - "non malleable extractors and codes with their many tampered extensions"
    - "three source extractors for polylogarithmic min entropy"
    - "non malleable coding against bit wise and split state tampering"
    - "non malleable condensers for arbitrary min entropy and almost optimal protocols for privacy amplification"
    - "non malleable extractors two source extractors and privacy amplification"
    - "fuzzy extractors how to generate strong keys from biometrics and other noisy data"

Connected through hyperedge HE-2 (induced by source paper "non malleable extractors and codes with their many tampered extensions"):
  with members:
    - "three source extractors for polylogarithmic min entropy"
    - "non malleable coding against bit wise and split state tampering"
    - "non malleable condensers for arbitrary min entropy and almost optimal protocols for privacy amplification"
    - "non malleable extractors two source extractors and privacy amplification"
    - "non malleable codes from the wire tap channel"
    - "fuzzy extractors how to generate strong keys from biometrics and other noisy data"

Connected through hyperedge HE-3 (induced by source paper "non malleable coding against bit wise and split state tampering"):
  with members:
    - "non malleable extractors and codes with their many tampered extensions"
    - "non malleable extractors two source extractors and privacy amplification"
    - "privacy amplification and non malleable extractors via character sums"
    - "applications of derandomization theory in coding"

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.IT(Information Theory)