human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "secure and efficient compressed sensing based encryption with sparse matrices"):
  Abstract: In this paper, we study the security of a compressed sensing (CS) based cryptosystem called a sparse one-time sensing (S-OTS) cryptosystem, which encrypts each plaintext with a sparse measurement matrix. To generate the secret matrix and renew it at each encryption, a bipolar keystream and a random permutation pattern are employed as cryptographic primitives, which are obtained by a keystream generator of stream ciphers. With a small number of nonzero elements in the measurement matrix, the S-OTS cryptosystem achieves an efficient CS encryption process in terms of data storage and computational cost. For security analysis, we show that the S-OTS cryptosystem can be computationally secure against ciphertext only attacks (COA) in terms of the indistinguishability, as long as each plaintext has constant energy. Also, we consider a chosen plaintext attack (CPA) against the S-OTS cryptosystem, which consists of two stages of keystream and key recovery attacks. Then, we show that the S-OTS cryptosystem can achieve the security against the CPA of keystream recovery with overwhelmingly high probability, as an adversary needs to distinguish a prohibitively large number of candidate keystreams. Finally, we conduct an information-theoretic analysis to demonstrate that the S-OTS cryptosystem has sufficient resistance against the CPA of key recovery by guaranteeing the extremely low probability of success. In conclusion, the S-OTS cryptosystem can be indistinguishable and secure against a CPA, while providing efficiency in CS encryption.

Includes members:
  Member "indistinguishability and energy sensitivity of asymptotically gaussian compressed encryption":
    also connected through other hyperedges:
      (none)
  Member "a survey on wireless security technical challenges recent advances and future trends":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "physical layer security in the finite blocklength regime over fading channels")
  Member "bi level protected compressive sampling":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adaptive image sampling using deep learning and its application on x ray fluorescence image reconstruction")
  Member "on known plaintext attacks to a compressed sensing based encryption a quantitative analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fast reconstruction algorithm for perturbed compressive sensing based on total least squares and proximal splitting")
  Member "low complexity multiclass encryption by compressed sensing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a greedy blind calibration method for compressed sensing with unknown sensor gains")
  Member "mergeshuffle a very fast parallel random permutation algorithm":
    also connected through other hyperedges:
      (none)
  Member "permutation meets parallel compressed sensing how to relax restricted isometry property for 2d sparse signals":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bi level protected compressive sampling")
  Member "compressive mechanism utilizing sparse representation in differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "differential privacy techniques for cyber physical systems a survey")

Question: Please tell me which class the source paper 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)