다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

Cloud computing is an emerging computing paradigm in which resources of the computing infrastructure are provided as services over the Internet. As promising as it is, this paradigm also brings forth many new challenges for data security and access control when users outsource sensitive data for sharing on cloud servers, which are not within the same trusted domain as data owners. To keep sensitive user data confidential against untrusted servers, existing solutions usually apply cryptographic methods by disclosing data decryption keys only to authorized users. However, in doing so, these solutions inevitably introduce a heavy computation overhead on the data owner for key distribution and data management when fine-grained data access control is desired, and thus do not scale well. The problem of simultaneously achieving fine-grainedness, scalability, and data confidentiality of access control actually still remains unresolved. This paper addresses this challenging open issue by, on one hand, defining and enforcing access policies based on data attributes, and, on the other hand, allowing the data owner to delegate most of the computation tasks involved in fine-grained data access control to untrusted cloud servers without disclosing the underlying data contents. We achieve this goal by exploiting and uniquely combining techniques of attribute-based encryption (ABE), proxy re-encryption, and lazy re-encryption. Our proposed scheme also has salient properties of user access privilege confidentiality and user secret key accountability. Extensive analysis shows that our proposed scheme is highly efficient and provably secure under existing security models.

/pdf/achieving-secure-scalable-and-fine-grained-data-access-3h59d4tpb3.pdf

Achieving Secure, Scalable, and Fine-grained Data Access Control in Cloud Computing

Deep learning based on artificial neural networks is a very popular approach to modeling, classifying, and recognizing complex data such as images, speech, and text The unprecedented accuracy of deep learning methods has turned them into the foundation of new AI-based services on the Internet Commercial companies that collect user data on a large scale have been the main beneficiaries of this trend since the success of deep learning techniques is directly proportional to the amount of data available for training Massive data collection required for deep learning presents obvious privacy issues Users' personal, highly sensitive data such as photos and voice recordings is kept indefinitely by the companies that collect it Users can neither delete it, nor restrict the purposes for which it is used Furthermore, centrally kept data is subject to legal subpoenas and extra-judicial surveillance Many data owners--for example, medical institutions that may want to apply deep learning methods to clinical records--are prevented by privacy and confidentiality concerns from sharing the data and thus benefitting from large-scale deep learning In this paper, we design, implement, and evaluate a practical system that enables multiple parties to jointly learn an accurate neural-network model for a given objective without sharing their input datasets We exploit the fact that the optimization algorithms used in modern deep learning, namely, those based on stochastic gradient descent, can be parallelized and executed asynchronously Our system lets participants train independently on their own datasets and selectively share small subsets of their models' key parameters during training This offers an attractive point in the utility/privacy tradeoff space: participants preserve the privacy of their respective data while still benefitting from other participants' models and thus boosting their learning accuracy beyond what is achievable solely on their own inputs We demonstrate the accuracy of our privacy-preserving deep learning on benchmark datasets

/pdf/privacy-preserving-deep-learning-3rlsmam417.pdf

Privacy-Preserving Deep Learning

Cloud Computing is the long dreamed vision of computing as a utility, where users can remotely store their data into the cloud so as to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources. By data outsourcing, users can be relieved from the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the possibly large size of outsourced data makes the data integrity protection in Cloud Computing a very challenging and potentially formidable task, especially for users with constrained computing resources and capabilities. Thus, enabling public auditability for cloud data storage security is of critical importance so that users can resort to an external audit party to check the integrity of outsourced data when needed. To securely introduce an effective third party auditor (TPA), the following two fundamental requirements have to be met: 1) TPA should be able to efficiently audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) The third party auditing process should bring in no new vulnerabilities towards user data privacy. In this paper, we utilize and uniquely combine the public key based homomorphic authenticator with random masking to achieve the privacy-preserving public cloud data auditing system, which meets all above requirements. To support efficient handling of multiple auditing tasks, we further explore the technique of bilinear aggregate signature to extend our main result into a multi-user setting, where TPA can perform multiple auditing tasks simultaneously. Extensive security and performance analysis shows the proposed schemes are provably secure and highly efficient.

https://www.cnsr.ictas.vt.edu/publication/INFOCOM10_Wang_PPPADSSCC.pdf

Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing

In 1998, Blaze, Bleumer, and Strauss (BBS) proposed an application called atomic proxy re-encryption, in which a semitrusted proxy converts a ciphertext for Alice into a ciphertext for Bob without seeing the underlying plaintext. We predict that fast and secure re-encryption will become increasingly popular as a method for managing encrypted file systems. Although efficiently computable, the wide-spread adoption of BBS re-encryption has been hindered by considerable security risks. Following recent work of Dodis and Ivan, we present new re-encryption schemes that realize a stronger notion of security and demonstrate the usefulness of proxy re-encryption as a method of adding access control to a secure file system. Performance measurements of our experimental file system demonstrate that proxy re-encryption can work effectively in practice.

/pdf/improved-proxy-re-encryption-schemes-with-applications-to-1ugoecwezg.pdf

Improved proxy re-encryption schemes with applications to secure distributed storage

Attribute-based encryption (ABE) is a new vision for public key encryption that allows users to encrypt and decrypt messages based on user attributes. For example, a user can create a ciphertext that can be decrypted only by other users with attributes satisfying ("Faculty" OR ("PhD Student" AND "Quals Completed")). Given its expressiveness, ABE is currently being considered for many cloud storage and computing applications. However, one of the main efficiency drawbacks of ABE is that the size of the ciphertext and the time required to decrypt it grows with the complexity of the access formula.

In this work, we propose a new paradigm for ABE that largely eliminates this overhead for users. Suppose that ABE ciphertexts are stored in the cloud. We show how a user can provide the cloud with a single transformation key that allows the cloud to translate any ABE ciphertext satisfied by that user's attributes into a (constant-size) El Gamal-style ciphertext, without the cloud being able to read any part of the user's messages.

To precisely define and demonstrate the advantages of this approach, we provide new security definitions for both CPA and replayable CCA security with outsourcing, several new constructions, an implementation of our algorithms and detailed performance measurements. In a typical configuration, the user saves significantly on both bandwidth and decryption time, without increasing the number of transmissions.

/pdf/outsourcing-the-decryption-of-abe-ciphertexts-20nk4elc32.pdf

Outsourcing the decryption of ABE ciphertexts

This paper presents efficient off-line anonymous e-cash schemes where a user can withdraw a wallet containing 2l coins each of which she can spend unlinkably. Our first result is a scheme, secure under the strong RSA and the y-DDHI assumptions, where the complexity of the withdrawal and spend operations is ${\mathcal O}(\ell + k)$ and the user's wallet can be stored using ${\mathcal O}(\ell + k)$ bits, where k is a security parameter. The best previously known schemes require at least one of these complexities to be ${\mathcal O}(2^{\rm \ell}\cdot k)$. In fact, compared to previous e-cash schemes, our whole wallet of 2l coins has about the same size as one coin in these schemes. Our scheme also offers exculpability of users, that is, the bank can prove to third parties that a user has double-spent. We then extend our scheme to our second result, the first e-cash scheme that provides traceable coins without a trusted third party. That is, once a user has double spent one of the 2l coins in her wallet, all her spendings of these coins can be traced. However, the price for this is that the complexity of the spending and of the withdrawal protocols becomes ${\mathcal O}(\ell \cdot k)$ and ${\mathcal O}(\ell \cdot k+k^{2})$ bits, respectively, and wallets take ${\mathcal O}(\ell \cdot k)$ bits of storage. All our schemes are secure in the random oracle model.

Compact e-cash

In a proxy re-encryption (PRE) scheme, a proxy is given special information that allows it to translate a ciphertext under one key into a ciphertext of the same message under a different key. The proxy cannot, however, learn anything about the messages encrypted under either key. PRE schemes have many practical applications, including distributed storage, email, and DRM. Previously proposed re-encryption schemes achieved only semantic security; in contrast, applications often require security against chosen ciphertext attacks. We propose a definition of security against chosen ciphertext attacks for PRE schemes, and present a scheme that satisfies the definition. Our construction is efficient and based only on the Decisional Bilinear Diffie-Hellman assumption in the standard model. We also formally capture CCA security for PRE schemes via both a game-based definition and simulation-based definitions that guarantee universally composable security. We note that, simultaneously with our work, Green and Ateniese proposed a CCA-secure PRE, discussed herein.

/pdf/chosen-ciphertext-secure-proxy-re-encryption-3mgdt3qbep.pdf

Chosen-ciphertext secure proxy re-encryption

In a proxy re-encryption (PRE) scheme, a proxy is given special information that allows it to translate a ciphertext under one key into a ciphertext of the same message under a dierent key. The proxy cannot, however, learn anything about the messages encrypted under either key. PRE schemes have many practical applications, including distributed storage, email, and DRM. Previously proposed re-encryption schemes achieved only semantic security; in contrast, applications often require security against chosen ciphertext attacks. We propose a denition of security against chosen ciphertext attacks for PRE schemes, and present a scheme that satises the denition. Our construction is ecient and based only on the Decisional Bilinear DieHellman assumption in the standard model. We also formally capture CCA security for PRE schemes via both a game-based denition and simulation-based denitions that guarantee universally composable security. We note that, simultaneously with our work, Green and Ateniese proposed a CCA-secure PRE, discussed herein.

/pdf/chosen-ciphertext-secure-proxy-re-encryption-2qqevd87mt.pdf

Susan Hohenberger

Papers

Improved proxy re-encryption schemes with applications to secure distributed storage

Outsourcing the decryption of ABE ciphertexts

Compact e-cash

Chosen-ciphertext secure proxy re-encryption

Chosen-Ciphertext Secure Proxy Re-Encryption.