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**11 - 15**of**15**### Private Approximate Heavy Hitters

, 2006

"... We consider the problem of private computation of approximate Heavy Hitters. Alice and Bob each hold a vector and, in the vector sum, they want to find the B largest values along with their indices. While the exact problem requires linear communication, protocols in the literature solve this problem ..."

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We consider the problem of private computation of approximate Heavy Hitters. Alice and Bob each hold a vector and, in the vector sum, they want to find the B largest values along with their indices. While the exact problem requires linear communication, protocols in the literature solve this problem approximately using polynomial computation time, polylogarithmic communication, and constantly many rounds. We show how to solve the problem privately with comparable cost, in the sense that nothing is learned by Alice and Bob beyond what is implied by their input, the ideal top-B output, and goodness of approximation (equivalently, the Euclidean norm of the vector sum). We give lower bounds showing that the Euclidean norm must leak by any efficient algorithm.

### Techniques for Efficient Keyword Search in Cloud Computing

"... Abstract — As cloud computing becomes most general, the important information is centralized into the cloud server. To protect the data stored in the cloud, the data must be encrypted. Although traditional encryption techniques allows the user to securely search through the keyword and return retrie ..."

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Abstract — As cloud computing becomes most general, the important information is centralized into the cloud server. To protect the data stored in the cloud, the data must be encrypted. Although traditional encryption techniques allows the user to securely search through the keyword and return retrieved files, these techniques are useful only for exact keyword search. In this paper, we solve the problem of exact keyword match by providing searching with fuzzy keyword. We also propose two more techniques called gram based technique which is useful for reducing the time, providing fast searching and increase the performance by considering substring from the given string. And Symbol-based tree traverse search scheme where a multi way tree structure is built by using symbols, which works for more than one keywords entered by the user. By providing security, we show that the proposed solution is secure and privacy-preserving.

### Private Approximation of the Set Cover Problem

, 2006

"... Private approximation, introduced by Feigenbaum, Ishai, Malkin, Nissim, Strauss, and Wright, allows us to find approximate solutions with disclosing as little information as possible. In STOC 2006, Beimel, Carmi, Nissim, and Weinreb studied the private approximation for both the vertex cover and the ..."

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Private approximation, introduced by Feigenbaum, Ishai, Malkin, Nissim, Strauss, and Wright, allows us to find approximate solutions with disclosing as little information as possible. In STOC 2006, Beimel, Carmi, Nissim, and Weinreb studied the private approximation for both the vertex cover and the max exact 3SAT problems. In this paper, we consider the set cover problem where the costs of all sets are polynomially bounded. We show that there exists neither a deterministic nor a randomized private approximation. We also consider the case that the frequencies of all elements are equal. We show that in this case there exist no deterministic private approximation.

### Thesis Proposal: New Algorithms for Preserving Differential Privacy

, 2009

"... In this thesis, we will consider the problem of how one should perform computations on private data. We will specifically consider algorithms which preserve the recent formalization of privacy known as differential privacy. The fundamental tradeoff that we consider is that of privacy and utility. Fo ..."

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In this thesis, we will consider the problem of how one should perform computations on private data. We will specifically consider algorithms which preserve the recent formalization of privacy known as differential privacy. The fundamental tradeoff that we consider is that of privacy and utility. For which tasks can we perform useful computations while still preserving privacy, and what exactly is the tradeoff between usefulness and privacy? Finally, we will also consider the intriguing connections between the fields of differential privacy and game theory. 1