Contributions to Lattice–based Cryptography

Post–quantum cryptography (PQC) is a new and fast–growing part of Cryptography. It focuses on developing cryptographic algorithms and protocols that resist quantum adversaries (i.e., the adversaries who have access to quantum computers). To construct a new PQC primitive, a designer must use a mathematical problem intractable for the quantum adversary. Many intractability assumptions are being used in PQC. There seems to be a consensus in the research community that the most promising are intractable/hard problems in lattices. However, lattice–based cryptography still needs more research to make it more efficient and practical. The thesis contributes toward achieving either the novelty or the practicality of lattice– based cryptographic systems

Survey on securing data storage in the cloud

Cloud Computing has become a well-known primitive nowadays; many researchers and companies are embracing this fascinating technology with feverish haste. In the meantime, security and privacy challenges are brought forward while the number of cloud storage user increases expeditiously. In this work, we conduct an in-depth survey on recent research activities of cloud storage security in association with cloud computing. After an overview of the cloud storage system and its security problem, we focus on the key security requirement triad, i.e., data integrity, data confidentiality, and availability. For each of the three security objectives, we discuss the new unique challenges faced by the cloud storage services, summarize key issues discussed in the current literature, examine, and compare the existing and emerging approaches proposed to meet those new challenges, and point out possible extensions and futuristic research opportunities. The goal of our paper is to provide a state-of-the-art knowledge to new researchers who would like to join this exciting new field

A HYBRIDIZED ENCRYPTION SCHEME BASED ON ELLIPTIC CURVE CRYPTOGRAPHY FOR SECURING DATA IN SMART HEALTHCARE

Recent developments in smart healthcare have brought us a great deal of convenience. Connecting common objects to the Internet is made possible by the Internet of Things (IoT). These connected gadgets have sensors and actuators for data collection and transfer. However, if users' private health information is compromised or exposed, it will seriously harm their privacy and may endanger their lives. In order to encrypt data and establish perfectly alright access control for such sensitive information, attribute-based encryption (ABE) has typically been used. Traditional ABE, however, has a high processing overhead. As a result, an effective security system algorithm based on ABE and Fully Homomorphic Encryption (FHE) is developed to protect health-related data. ABE is a workable option for one-to-many communication and perfectly alright access management of encrypting data in a cloud environment. Without needing to decode the encrypted data, cloud servers can use the FHE algorithm to take valid actions on it. Because of its potential to provide excellent security with a tiny key size, elliptic curve cryptography (ECC) algorithm is also used. As a result, when compared to related existing methods in the literature, the suggested hybridized algorithm (ABE-FHE-ECC) has reduced computation and storage overheads. A comprehensive safety evidence clearly shows that the suggested method is protected by the Decisional Bilinear Diffie-Hellman postulate. The experimental results demonstrate that this system is more effective for devices with limited resources than the conventional ABE when the system’s performance is assessed by utilizing standard model

Fully Key-Homomorphic Encryption, Arithmetic Circuit ABE and Compact Garbled Circuits

We construct the first (key-policy) attribute-based encryption (ABE) system with short secret keys: the size of keys in our system depends only on the depth of the policy circuit, not its size. Our constructions extend naturally to arithmetic circuits with arbitrary fan-in gates thereby further reducing the circuit depth. Building on this ABE system we obtain the first reusable circuit garbling scheme that produces garbled circuits whose size is the same as the original circuit plus an additive poly(λ,d) bits, where λ is the security parameter and d is the circuit depth. All previous constructions incurred a multiplicative poly(λ) blowup. We construct our ABE using a new mechanism we call fully key-homomorphic encryption, a public-key system that lets anyone translate a ciphertext encrypted under a public-key x into a ciphertext encrypted under the public-key (f(x),f) of the same plaintext, for any efficiently computable f. We show that this mechanism gives an ABE with short keys. Security of our construction relies on the subexponential hardness of the learning with errors problem. We also present a second (key-policy) ABE, using multilinear maps, with short ciphertexts: an encryption to an attribute vector x is the size of x plus poly(λ,d) additional bits. This gives a reusable circuit garbling scheme where the garbled input is short.United States. Defense Advanced Research Projects Agency (Grant FA8750-11-2-0225)Alfred P. Sloan Foundation (Sloan Research Fellowship

STP-LWE: A Variant of Learning with Error for a Flexible Encryption

We construct a flexible lattice based scheme based on semitensor product learning with errors (STP-LWE), which is a variant of learning with errors problem. We have proved that STP-LWE is hard when LWE is hard. Our scheme is proved to be secure against indistinguishable chosen message attacks, and it can achieve a balance between the security and efficiency in the hierarchical encryption systems. In addition, our scheme is almost as efficient as the dual encryption in GPV08

Still Wrong Use of Pairings in Cryptography

Several pairing-based cryptographic protocols are recently proposed with a wide variety of new novel applications including the ones in emerging technologies like cloud computing, internet of things (IoT), e-health systems and wearable technologies. There have been however a wide range of incorrect use of these primitives. The paper of Galbraith, Paterson, and Smart (2006) pointed out most of the issues related to the incorrect use of pairing-based cryptography. However, we noticed that some recently proposed applications still do not use these primitives correctly. This leads to unrealizable, insecure or too inefficient designs of pairing-based protocols. We observed that one reason is not being aware of the recent advancements on solving the discrete logarithm problems in some groups. The main purpose of this article is to give an understandable, informative, and the most up-to-date criteria for the correct use of pairing-based cryptography. We thereby deliberately avoid most of the technical details and rather give special emphasis on the importance of the correct use of bilinear maps by realizing secure cryptographic protocols. We list a collection of some recent papers having wrong security assumptions or realizability/efficiency issues. Finally, we give a compact and an up-to-date recipe of the correct use of pairings.Comment: 25 page

A Framework for Uncertain Cloud Data Security and Recovery Based on Hybrid Multi-User Medical Decision Learning Patterns

Machine learning has been supporting real-time cloud based medical computing systems. However, most of the computing servers are independent of data security and recovery scheme in multiple virtual machines due to high computing cost and time. Also, this cloud based medical applications require static security parameters for cloud data security. Cloud based medical applications require multiple servers to store medical records or machine learning patterns for decision making. Due to high Uncertain computational memory and time, these cloud systems require an efficient data security framework to provide strong data access control among the multiple users. In this work, a hybrid cloud data security framework is developed to improve the data security on the large machine learning patterns in real-time cloud computing environment. This work is implemented in two phases’ i.e. data replication phase and multi-user data access security phase. Initially, machine decision patterns are replicated among the multiple servers for Uncertain data recovering phase. In the multi-access cloud data security framework, a hybrid multi-access key based data encryption and decryption model is implemented on the large machine learning medical patterns for data recovery and security process. Experimental results proved that the present two-phase data recovering, and security framework has better computational efficiency than the conventional approaches on large medical decision patterns