Data Mining - Concepts and Techniques.

National Institute of Standards and Technology における超伝導研究及び生活

Usually, a proof of a theorem contains more knowledge than the mere fact that the theorem is true. For instance, to prove that a graph is Hamiltonian it suffices to exhibit a Hamiltonian tour in it; however, this seems to contain more knowledge than the single bit Hamiltonian/non-Hamiltonian.In this paper a computational complexity theory of the “knowledge” contained in a proof is developed. Zero-knowledge proofs are defined as those proofs that convey no additional knowledge other than the correctness of the proposition in question. Examples of zero-knowledge proof systems are given for the languages of quadratic residuosity and 'quadratic nonresiduosity. These are the first examples of zero-knowledge proofs for languages not known to be efficiently recognizable.

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The knowledge complexity of interactive proof-systems

1. Introduction to text mining 2. Core text mining operations 3. Text mining preprocessing techniques 4. Categorization 5. Clustering 6. Information extraction 7. Probabilistic models for Information extraction 8. Preprocessing applications using probabilistic and hybrid approaches 9. Presentation-layer considerations for browsing and query refinement 10. Visualization approaches 11. Link analysis 12. Text mining applications Appendix Bibliography.

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The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data

An intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

Intelligent Automated Assistant

The basic pattern matching problem is to find the locations where a pattern occurs in a text. Recently, secure pattern matching has been received much attention in various areas, including privacy-preserving DNA matching and secure biometric authentication. The aim of this paper is to give a practical solution for this problem using homomorphic encryption, which is public key encryption supporting some operations on encrypted data.In this paper, we make use of the somewhat homomorphic encryption scheme presented by Lauter, Naehrig and Vaikuntanathan (ACM CCSW 2011), which supports a limited number of both additions and multiplications on encrypted data. In their work, some message encoding techniques are also presented for enabling us to efficiently compute sums and products over the integers. Based on their techniques, we propose a new packing method suitable for an efficient computation of multiple Hamming distance values on encrypted data. Our main extension gives two types of packed ciphertexts, and a linear computation over packed ciphertexts gives our desired results. We implemented the scheme with our packing method.Our experiments ran in an Intel Xeon at 3.07 GHz with our software library using inline assembly language in C programs. Our optimized implementation shows that the packed encryption of a text or a pattern, the computation of multiple Hamming distance values over packed ciphertexts, and the decryption respectively take about 3.65 milliseconds (ms), 5.31 ms, and 3.47 ms for secure exact and approximate pattern matching of a binary text of length 2048. The total time is about 12.43 ms, which would give the practical performance in real life. Our method gives both faster performance and lower communication than the state-of-the-art work for a binary text of several thousand bits in length.

Secure pattern matching using somewhat homomorphic encryption

Blind quantum computation is a new quantum secure protocol, which enables Alice who does not have enough quantum technology to delegate her computation to Bob who has a fully fledged quantum power without revealing her input, output, and algorithm. So far, blind quantum computation has been considered only for the circuit model and the measurement-based model. Here we consider the possibility and the limitation of blind quantum computation in the ancilla-driven model, which is a hybrid of the circuit and the measurement-based models.

Ancilla-Driven Universal Blind Quantum Computation

Among many approaches for privacy-preserving biometric authentication, we focus on the approach with homomorphic encryption, which is public key encryption supporting some operations on encrypted data. In biometric authentication, the Hamming distance is often used as a metric to compare two biometric feature vectors. In this paper, we propose an efficient method to compute the Hamming distance on encrypted data using the homomorphic encryption based on ideal lattices. In our implementation of secure Hamming distance of 2048-bit binary vectors with a lattice of 4096 dimension, encryption of a vector, secure Hamming distance, and decryption respectively take about 19.89, 18.10, and 9.08 milliseconds (ms) on an Intel Xeon X3480 at 3.07 GHz. We also propose a privacy-preserving biometric authentication protocol using our method, and compare it with related protocols. Our protocol has faster performance and shorter ciphertext size than the state-of-the-art prior work using homomorphic encryption.

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Packed homomorphic encryption based on ideal lattices and its application to biometrics

Somewhat homomorphic encryption is public key encryption supporting a limited number of both additions and multiplications on encrypted data, which is useful for performing fundamental computations with protecting the data confidentiality. In this paper, we focus on the scheme proposed by Lauter, Naehrig and Vaikuntanathan (ACM CCSW 2011), and present two types of packed ciphertexts based on their packing technique. Combinations of two types of our packing method give practical size and performance for wider computations such as statistical analysis and distances. To demonstrate its efficiency, we implemented the scheme with our packing method for secure Hamming distance, which is often used in privacy-preserving biometrics. For secure Hamming distance between two binary vekoshiba@mail.saitama-u.ac.jpctors of 2048-bit, it takes 5.31ams on an Intel Xeon X3480 at 3.07aGHz. This gives the best performance in the state-of-the-art work using homomorphic encryption.

Practical Packing Method in Somewhat Homomorphic Encryption

The system creates the aggregate of virtual particles in a cybernetic space on a computer and displays the shape of an object by means of a film covering its surface. When a user inputs a deforming designation, each particle moves and deforms the film. At this time the shape, sense of touch and counter force are output from the computer, and the user can deform the object with a feeling of working clay.

Takeshi Koshiba

Papers

Secure pattern matching using somewhat homomorphic encryption

Ancilla-Driven Universal Blind Quantum Computation

Packed homomorphic encryption based on ideal lattices and its application to biometrics

Practical Packing Method in Somewhat Homomorphic Encryption

Virtual clay system and its method of simulation