Blockchain and other Distributed Ledger Technologies (DLTs) have evolved significantly in the last years and their use has been suggested for numerous applications due to their ability to provide transparency, redundancy and accountability. In the case of blockchain, such characteristics are provided through public-key cryptography and hash functions. However, the fast progress of quantum computing has opened the possibility of performing attacks based on Grover’s and Shor’s algorithms in the near future. Such algorithms threaten both public-key cryptography and hash functions, forcing to redesign blockchains to make use of cryptosystems that withstand quantum attacks, thus creating which are known as post-quantum, quantum-proof, quantum-safe or quantum-resistant cryptosystems. For such a purpose, this article first studies current state of the art on post-quantum cryptosystems and how they can be applied to blockchains and DLTs. Moreover, the most relevant post-quantum blockchain systems are studied, as well as their main challenges. Furthermore, extensive comparisons are provided on the characteristics and performance of the most promising post-quantum public-key encryption and digital signature schemes for blockchains. Thus, this article seeks to provide a broad view and useful guidelines on post-quantum blockchain security to future blockchain researchers and developers.

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Towards Post-Quantum Blockchain: A Review on Blockchain Cryptography Resistant to Quantum Computing Attacks

Welcome to the Proceedings of the 23rd ACM Symposium on Operating Systems Principles (SOSP 2011), held in Cascais, Portugal. This year's program includes 28 papers, and touches on a wide range of computer systems topics, from data center computing, storage systems and geo-replication to operating system architecture, virtualization, concurrency, security, and mobile platforms. The program committee made every effort to identify and include some of the most creative and thought-provoking ideas in computer systems today. Each accepted paper was shepherded by a program committee member to make sure the papers are as readable and complete as possible. We hope you will enjoy the program as much as we did in selecting it.

This year's proceedings are, for the first time, published digitally on a USB key with no paper copy distributed at the conference. The cost to the environment of so many reams of printed paper, plus the difficulty of shipping printed material to the conference site, made this an easy decision. The workshop proceedings appear on the conference USB key as well. You will find two copies of each of this year's SOSP papers: a traditional 2- column version designed for printing, and a one-column version intended for reading on a computer. In addition, the USB key contains a copy of every SOSP paper from each of the previous 22 instances of the conference, starting in 1967. The very nature of publishing is changing as we speak. We look forward to your feedback about the appropriate form and format for future SOSP proceedings.

We are most grateful to the authors of the 157 papers who chose to submit their work to SOSP (five papers were subsequently withdrawn by the authors). Their ideas and efforts are the basis of the conference's success. Selecting the program out of so many quality submissions was a difficult task. A program committee consisting of 28 leading scholars in the broad area of computer systems conducted a three-stage reviewing process and online discussion; final selections were made during a physical meeting in Boston, MA, which was attended by a core of 13 PC members. Each submission received at least three PC reviews, with a maximum of eight. All in all, 719 reviews were produced. The PC made every effort to provide detailed and constructive feedback, which should help authors to further improve their work. Author anonymity was maintained throughout the reviewing and selection process; PC members were removed from the deliberations of any paper with which they had a conflict of interest (co-author, same institution, recent collaborator, former student/adviser).

Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles

At CCS 2015 Naveed et al. presented first attacks on efficiently searchable encryption, such as deterministic and order-preserving encryption. These plaintext guessing attacks have been further improved in subsequent work, e.g. by Grubbs et al. in 2016. Such cryptanalysis is crucially important to sharpen our understanding of the implications of security models. In this paper we present an order-preserving encryption scheme in the form of an efficiently searchable, encrypted data structure that is provably secure against these and even more powerful chosen plaintext attacks. Our data structure supports logarithmic-time search with linear space complexity. The indices of our data structure can be used to search by standard comparisons and hence allow easy retrofitting to existing database management systems. We implemented our scheme and show that its search time overhead is only 10 ms compared to non-secure search on a database with 1 million entries.

An Efficiently Searchable Encrypted Data Structure for Range Queries

Federated learning is an improved version of distributed machine learning that further offloads operations which would usually be performed by a central server. The server becomes more like an assistant coordinating clients to work together rather than micro-managing the workforce as in traditional DML. One of the greatest advantages of federated learning is the additional privacy and security guarantees it affords. Federated learning architecture relies on smart devices, such as smartphones and IoT sensors, that collect and process their own data, so sensitive information never has to leave the client device. Rather, clients train a sub-model locally and send an encrypted update to the central server for aggregation into the global model. These strong privacy guarantees make federated learning an attractive choice in a world where data breaches and information theft are common and serious threats. This survey outlines the landscape and latest developments in data privacy and security for federated learning. We identify the different mechanisms used to provide privacy and security, such as differential privacy, secure multi-party computation and secure aggregation. We also survey the current attack models, identifying the areas of vulnerability and the strategies adversaries use to penetrate federated systems. The survey concludes with a discussion on the open challenges and potential directions of future work in this increasingly popular learning paradigm.

From Distributed Machine Learning To Federated Learning: In The View Of Data Privacy And Security

Cloud computing is one of the significant development that utilizes progressive computational power and upgrades data distribution and data storing facilities. With cloud information services, it is essential for information to be saved in the cloud and also distributed across numerous customers. Cloud information repository is involved with issues of information integrity, data security and information access by unapproved users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art techniques in data auditing and security are discussed. Challenging problems in information repository auditing and security are presented. Finally, directions for future research in data auditing and security have been discussed.

https://www.ijcjournal.org/index.php/InternationalJournalOfComputer/article/download/1002/476

Data Auditing and Security in Cloud Computing: Issues, Challenges and Future Directions

In this article we describe two alternative order-preserving encryption schemes. First scheme is based on arithmetic coding and the second scheme uses sequence of matrices for data encrypting. In the beginning of this paper we briefly describe previous related work published in recent time. Then we propose alternative variants of OPE and consider them in details. We examine drawbacks of these schemes and suggest possible ways of their improvement. Finally we present statistical results of implemented prototypes and discuss further work.

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Order-preserving encryption schemes based on arithmetic coding and matrices

In this article we describe a simplified version of Polly Cracker-style fully homomorphic encryption scheme. The main feature of our scheme is an ability to define a strict upper bound of ciphertext size when performing calculations on it for both addition and multiplication. Combined with homomorphic properties of Polly Cracker it's able to reach high calculation performance without degrading in time. Another important aspect is utilization of large finite rings for calculations in untrusted environment, which prevents most of known attacks on Polly Cracker family.

Practical fully homomorphic encryption over polynomial quotient rings

Cloud computing and, more particularly, cloud databases, is a great technology for remote centralized data managing. However, there are some drawbacks including privacy issues, insider threats and potential database thefts. Full encryption of remote database does solve the problem, but disables many operations that can be held on DBMS side; therefore problem requires much more complex solution and specific encryptions. In this paper, we propose a solution for secure private data storage that protects confidentiality of user's data, stored in cloud. Solution uses order preserving and homomorphic proprietary developed encryptions. Proposed approach includes analysis of user's SQL queries, encryption of vulnerable data and decryption of data selection, returned from DBMS. We have validated our approach through the implementation of SQL queries and DBMS replies processor, which will be discussed in this paper. Secure cloud database architecture and used encryptions also will be covered.

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Solution for secure private data storage in a cloud

This paper describes an algorithm for creating hash function, resistant for quantum computer. The given approach is based on the problem of solving a system of polynomial equations in integers, where the number of equations is less than the number of unknown parameters. The developed algorithm is parameterized so the result of the hash function depends on several parameters, therefore, it will take considerably longer to select the solution of the task. The avalanche effect is about 50%, collision is impossible because the task to find a solution of the described system of equations with a degree greater than 3 is algorithmically unsolvable. This hash function was developed for blockchain to ensure its integrity, but it can also be used in any application where a hash function is needed.

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Parametric Hash Function Resistant to Attack by Quantum Computer

Outsourced computations and, more particularly, cloud computations, are widespread nowadays. That is why the problem of keeping the data security arises. Multiple fully homomorphic cryptosystems were proposed in order to perform secret computations in untrusted environments. But most of the existent solutions are practically inapplicable as they require huge computation resources and produce big (�1Gb) keys and ciphertexts. Therefore, we propose the undemanding fully homomorphic scheme with practically acceptable (�few Kb) keys and output data. Our solution uses modular arithmetic in order to avoid the increase in data size. We have validated our approach through the implementation of the proposed cryptosystem. The details of used algorithms and the results of security evaluation are covered in this paper.

/pdf/fully-homomorphic-encryption-for-secure-computations-in-2smn3h524u.pdf

Sergey Krendelev

Papers

Order-preserving encryption schemes based on arithmetic coding and matrices

Practical fully homomorphic encryption over polynomial quotient rings

Solution for secure private data storage in a cloud

Parametric Hash Function Resistant to Attack by Quantum Computer

Fully Homomorphic Encryption for Secure Computations in Protected Database