human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Can homomorphic encryption be practical"
  Abstract: The prospect of outsourcing an increasing amount of data storage and management to cloud services raises many new privacy concerns for individuals and businesses alike. The privacy concerns can be satisfactorily addressed if users encrypt the data they send to the cloud. If the encryption scheme is homomorphic, the cloud can still perform meaningful computations on the data, even though it is encrypted.   In fact, we now know a number of constructions of  fully  homomorphic encryption schemes that allow arbitrary computation on encrypted data. In the last two years, solutions for fully homomorphic encryption have been proposed and improved upon, but it is hard to ignore the elephant in the room, namely efficiency --  can homomorphic encryption ever be efficient enough to be practical?  Certainly, it seems that all known  fully  homomorphic encryption schemes have a long way to go before they can be used in practice. Given this state of affairs, our contribution is two-fold.   First, we exhibit a number of real-world applications, in the medical, financial, and the advertising domains, which require only that the encryption scheme is "somewhat" homomorphic. Somewhat homomorphic encryption schemes, which support a limited number of homomorphic operations, can be much faster, and more compact than fully homomorphic encryption schemes.   Secondly, we show a  proof-of-concept  implementation of the recent somewhat homomorphic encryption scheme of Brakerski and Vaikuntanathan, whose security relies on the "ring learning with errors" (Ring LWE) problem. The scheme is very efficient, and has reasonably short ciphertexts. Our  unoptimized  implementation in  magma  enjoys comparable efficiency to even  optimized  pairing-based schemes with the same level of security and homomorphic capacity. We also show a number of  application-specific  optimizations to the encryption scheme, most notably the ability to convert between different message encodings in a ciphertext.

Connected through hyperedge HE-1 (induced by source paper "A Language for the Composition of Privacy-Enforcement Techniques"):
  with members:
    (none)

Connected through hyperedge HE-2 (induced by source paper "Computing Blindfolded: New Developments in Fully Homomorphic Encryption"):
  with members:
    - "Functional encryption for inner product predicates from learning with errors"
    - "On Privacy-Preserving Ways to Porting the Austrian eID System to the Public Cloud"

Connected through hyperedge HE-3 (induced by source paper "Fast Cryptographic Primitives and Circular-Secure Encryption Based on Hard Learning Problems"):
  with members:
    - "Key-dependent Message Security under Active Attacks--BRSIM/UC-Soundness of Symbolic Encryption with Key Cycles"
    - "High-Speed Signatures from Standard Lattices"
    - "An Improved Compression Technique for Signatures Based on Learning with Errors"
    - "Low Noise LPN: KDM Secure Public Key Encryption and Sample Amplification"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science