분산 컴퓨팅과 캐시를 접목한 정보 검색에서의 보안 및 프라이버시

학위논문(박사)--서울대학교 대학원 :공과대학 전기·정보공학부,2020. 2. 이정우.많은 양의 데이터 저장이나 데이터 계산을 위해서는 분산 시스템이 필수적이다. 이러한 분산 시스템의 데이터 저장과 계산의 효율의 높이는 반면, 데이터의 보안과 프라이버시에 대한 위험도 증가시킨다. 본 논문에서는 데이터 저장과 데이터 계산을 위한 분산 시스템에서 데이터에 대한 보안과 프라이버시를 고려한다. 특히, 이러한 시스템에 대하여 보안과 프라이버시를 보장하는 부호화 기법을 제안한다. 우선, 유저가 사전에 캐시에 일정량의 데이터를 저장하고 있는 cache-aided PIR을 제안한다. 제안하는 기법은 기존 PIR 문제의 최적 기법을 기반으로 한다. 제안하는 기법에서, 캐시에 저장된 데이터는 부가정보로 이용되며, 이는 캐시가 없을 때 대비 다운로드양의 감소로 이어진다. 두 번째로, 부호화된 분산 컴퓨팅 시스템에서 마스터의 프라이버시를 고려한다. 이 시스템에서 워커들과 마스터는 각각 고유한 데이터를 가지며, 워커들의 데이터는 라이브러리 형태로 이루어진다. 마스터는 자신의 데이터와 데이터 라이브러리 내 특정 데이터의 함수를 계산해야 한다. 이 때 마스터의 프라이버시는 워커들이 마스터가 라이브러리 안의 어떤 데이터를 원하는지 모르는 것을 뜻한다. 이러한 시스템을 private coded computation이라 하며, 제안하는 기법을 private polynomial codes라 한다. 제안하는 기법에서는 기존의 polynomial codes에서는 고려되지 않았던 비동기적 기법이 도입된다. 이로 인하여 제안하는 기법은 변형된 최적의 RPIR 기법대비 더 빠른 계산시간을 달성한다. 끝으로, 부호화된 분산 컴퓨팅 시스템에서 마스터의 프라이버시와 데이터 보안을 동시에 고려한다. 데이터 보안은 마스터의 고유한 데이터를 워커들로부터 보호하는 것을 의미한다. 이러한 시스템을 private secure coded computation이라 하며, 제안하는 기법을 private secure polynomial codes라 한다. Private polynomial codes를 변형하여 private secure polynomial codes와 private polynomial codes를 계산시간과 통신량 측면에서 비교한다. 그 결과, 같은 양의 통신량에 대하여, private secure polynomial codes가 더 빠른 계산 시간을 달성한다.As a major format of data changes from the text to the videos, the amount of memory for storing data increases exponentially, as well as the amount of computation for handling the data. As a result, to alleviate these burdens of storage and computations, the distributed systems are actively studied. Meanwhile, since low latency is one of the main objectives in 5G communications, recent techniques such as edge computing or federated learning in machine learning become important. Since the decentralized systems are fundamental characteristics of these techniques, the distributed systems which include the decentralized systems also become important. In this dissertation, I consider the distributed systems for storage and computation. For the data storage, large-scale data centers collectively store a library of files where the size of each file is tremendous. When a user needs a specific file, it can be downloaded from distributed data centers. In this system, minimizing the amount of download is a significant concern. The user's privacy in this system implies that the user should conceal the index of its desired file against the databases. This kind of problem is referred to as private information retrieval (PIR) problem. The goal of PIR problem is to minimize the amount of download from the databases while ensuring the user's privacy. Meanwhile, for a large amount of computation, the user can divide the whole computation into sub-computations and distribute them to external workers who constitute a distributed system. There can be three cases for the computation. Firstly, the user may own all of the data to be computed and sends both of its data and instructions for the computation to the workers. Secondly, the workers collectively own all of the data and the user just sends instructions for the data selection and computation to the workers. Thirdly, the user and the workers have their own data respectively and the user sends the data and instructions for the data selection and computation to the workers. Since some of the workers can be slow for various reasons, the user may use a coding technique, e.g., an erasure code, to avoid the delaying effect caused by the slow workers. This kind of technique is referred to as coded computation. In these systems, speeding up the computation process is a significant concern. In this dissertation, I focus on the third system. In the considered system, the privacy is similar to that of distributed systems for storage. On the other hand, the security implies that the user should conceal the content of its own data against the workers so that the workers do not have any information about the user's own data. In this dissertation, I consider the user's privacy in distributed systems for storage, and both of the privacy and security in distributed systems for the computation. In case of the distributed systems for storage, since the user does not have its own data, the data security on the user's data cannot be considered. Particularly, I propose some achievable schemes that ensure the privacy and security in these systems. To begin with, as a new variation of PIR problem, I consider a user's cache that has some pre-stored data of databases' library. I refer to this problem as cache-aided PIR problem. By introducing the user's cache in the PIR problem, the amount of download from the databases is significantly reduced. The achievable scheme is based on the optimal scheme for conventional PIR problem. In the achievable scheme, the pre-store cache was exploited as an side information, which reduces the amount of download, compared to the PIR problem without cache. Secondly, I consider the master's privacy in coded computation. In the system model, the workers have their own data, as well as the master. The workers' data constitutes a library of several files. The master should compute a function of its own data and a specific file in the library. The master's privacy implies that the workers' should not know which file in the library is desired by the user. I refer to this problem as private coded computation and propose an achievable scheme of private coded computation, namely private polynomial codes. The private polynomial codes are based on the polynomial codes which were proposed in the conventional coded computation system. In the achievable scheme, the workers are grouped for the privacy and asynchronous scheme is considered, which was not considered in the conventional polynomial codes. Due to the asynchronous scheme, the proposed scheme achieves the faster computation time, compared to the modified optimal RPIR scheme. Lastly, I consider the data security in coded computation, as well as the master's privacy. The system model is similar to that of private coded computation. The data security implies that the master should protect its own data against the workers. I refer to this problem as private secure coded computation and propose an achievable scheme, namely private secure polynomial codes. The private secure polynomial codes are based on the polynomial codes which were proposed in the conventional coded computation system. By modifying the private polynomial codes, the private secure polynomial codes and private secure polynomial codes are compared in terms of computation time and communication load. As a result, the private secure polynomial codes achieves faster computation time for the same communication load.1. Introduction 1 1.1 Related work 3 1.1.1 Private information retrieval 3 1.1.2 Coded computation 4 1.2 Contributions and Organization 5 2. Cache-aided Private Information Retrieval 8 2.1 Introduction 8 2.2 System model 9 2.3 Main results : 12 2.4 Achievable scheme 17 2.4.1 Cacheless phase 17 2.4.2 Cache-assisted phase 21 2.4.3 Cache-aided PIR 24 2.5 Tightness of achievable scheme 29 2.6 Conclusions and follow-up works 30 3. Private Coded Computation 32 3.1 Introduction 32 3.2 System model 37 3.3 Main results 41 3.4 Private polynomial codes 42 3.4.1 First example 42 3.4.2 Second example 48 3.4.3 General description 52 3.4.4 Privacy proof 56 3.4.5 Performance analysis 59 3.4.6 Special cases 61 3.5 Simulation results 62 3.5.1 Computation time 62 3.5.2 Communication load 68 3.6 Conclusion 69 4. Private Secure Coded Computation 71 4.1 Introduction 71 4.2 Main results 75 4.3 Private secure polynomial codes 76 4.3.1 Illustrative example 76 4.3.2 General description 80 4.3.3 Performance analysis 83 4.3.4 Privacy and security proof 84 4.4 Simulation results 85 4.4.1 Computation time 86 4.4.2 Communication load 90 4.5 Conclusion 91 5 Conclusion 93 5.1 Summary 93 5.2 Future directions 94 국문초록 105 Acknowledgement 107Docto

교통기반시설투자의 지역간배분과 지역경제성장에 관한 연구(Regional allocation of transportation infrastructure investment and development of local economy)

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대형공공건설사업의 효율적 추진방안 연구

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High Dimensional Markov Chain Monte Carlo with Multiple GPUs

학위논문 (석사)-- 서울대학교 대학원 : 자연과학대학 통계학과, 2018. 2. 이재용.인공신경망과 같은 많은 계산을 요하는 모형이 다양한 분야에서 효과적임이 드러남에 따라 형렬 연산을 병렬처리 하기 위해 그래픽카드(GPU) 상 에서 계산하는 것이 일반화되고 있으며 이를 위해 계산을 여러 스레드로 나누는 방법을 찾는 것이 중요해지고 있다. 본 논문은 분할 된 샘플 공간에서 브리지 샘플링과 해밀토니안 몬테카를로를 결합하여 여러 GPU에 분산될 수 있는 새로운 MCMC 알고리즘을 제시한다. 이 접근법은 베이지안 뉴럴 네트워크 (Bayesian Neural Network)와 같은 타겟 분포에 대한 MCMC 샘플링을 빠르게 할 수 있다. 또한 다중 모달 (Multimodality)이 존재할 때 이 알고리즘은 낮은 확률 영역에서도 샘플링을 효율적으로 잘 할수 있는것으로 나타났다. 마지막으로 이 논문은 Adam Optimizer, 해밀토니안 몬테카를로와 같은 다른 학습 방법의 변수 분포와 본 알고리즘의 변수분포를 비교함으로써, 제한된 표본 공간이 일반화 오차에 미치는 영향에 대한 추가 연구가 수행 될 수 있음을 제시한다.Allocating computation over multiple threads to reduce running time has become a key to training big models such as deep neural networks because a Graphics Processing Unit (GPU), which is parallel in nature, can speed up intensive matrix operations. We present a new MCMC algorithm that can be distributed over multiple GPUs by combining bridge sampling with Hamiltonian Monte Carlo on partitioned sample spaces. We empirically show that this approach can expedite MCMC sampling for any unnormalized target distribution such as Bayesian Neural Network in a high dimensional setting. Furthermore, in the presence of multimodality, this algorithm is expected to be more efficient in mixing MCMC chains when proper partitions are chosen. Finally, by comparing the parameter distributions of different learning method, we suggest that further studies could be conducted on the effect of a constrained sample space on the generalization error.Abstract 3 Chapter 1 Introduction 9 1.1 Related Works 10 1.2 Contribution 12 Chapter 2 Hamiltonian Monte Carlo 13 2.1 Momentum proposal 15 2.2 Leap frog update 15 2.3 Metropolis Accept-Reject 16 Chapter 3 Bridged Hamiltonian Monte Carlo 18 3.1 Sampling from Partitioned Sample Space 18 3.1.1 Constrained HMC 19 3.2 Combining Samples from different Sample Space 20 3.2.1 Bridge Sampling 22 3.3 Practical Issues in Implementing Bridged Hamiltonian Monte Carlo 24 3.3.1 Numerical Overflow or Underflow 24 3.3.2 Partitioning Scheme 26 Chapter 4 Experiments 28 4.1 Bivariate Normal Mixture Model 28 4.2 Moon Data Classification 31 4.3 MNIST Data Classification 36 4.4 Result 37 Chapter 5 Discussion 42 초록 48Maste

국민경제 안정을 위한 주택산업 발전방향 연구(A study on improvement of housing industry for stability of national economy)

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Analytical Tools and Databases for Metagenomics in the Next-Generation Sequencing Era

Metagenomics has become one of the indispensable tools in microbial ecology for the last few decades, and a new revolution in metagenomic studies is now about to begin, with the help of recent advances of sequencing techniques. The massive data production and substantial cost reduction in next-generation sequencing have led to the rapid growth of metagenomic research both quantitatively and qualitatively. It is evident that metagenomics will be a standard tool for studying the diversity and function of microbes in the near future, as fingerprinting methods did previously. As the speed of data accumulation is accelerating, bioinformatic tools and associated databases for handling those datasets have become more urgent and necessary. To facilitate the bioinformatics analysis of metagenomic data, we review some recent tools and databases that are used widely in this field and give insights into the current challenges and future of metagenomics from a bioinformatics perspective.

Clinical features and long-term prognosis of acute fibrinous and organizing pneumonia histologically confirmed by surgical lung biopsy

Background: Acute fibrinous and organizing pneumonia (AFOP) is a rare interstitial pneumonia characterized by intra-alveolar fibrin deposition and organizing pneumonia. The clinical manifestations and long-term prognosis of AFOP are unclear. Our objective was to investigate the clinical features and prognosis of AFOP. Methods: We identified patients diagnosed with AFOP by surgical lung biopsy between January 2011 and May 2018 at Seoul National University Bundang Hospital. We retrospectively reviewed clinical and radiologic findings, treatment, and outcomes of AFOP. Results: Fifteen patients with histologically confirmed lung biopsies were included. The median follow-up duration was 2.4 (range, 0.1-82) months. The median age was 55 (range, 33-75) years, and four patients were immunocompromised. Fever was the most common clinical presentation (86.7%). Patchy ground-glass opacities and/or consolidations were the most predominant findings on chest computed tomography images. Nine patients (60%) received mechanical ventilator care, and eight patients (53.3%) died. The non-survivors tended to have slightly higher body mass index (BMI) and a long interval between symptom onset and diagnosis than the survivors, but these findings were not statistically significant. Among seven survivors, five patients were discharged without dyspnea and oxygen supplement. Conclusions: The clinical course of AFOP was variable. Although AFOP was fatal, most of the patients who recovered from AFOP maintained normal life without supplemental oxygen therapy and respiratory symptoms.ope