Flexible Yet Secure De-Duplication Service for Enterprise Data on Cloud Storage

The cloud storage services bring forth infinite storage capacity and flexible access capability to store and share large-scale content. The convenience brought forth has attracted both individual and enterprise users to outsource data service to a cloud provider. As the survey shows 56% of the usages of cloud storage applications are for data back up and up to 68% of data backup are user assets. Enterprise tenants would need to protect their data privacy before uploading them to the cloud and expect a reasonable performance while they try to reduce the operation cost in terms of cloud storage, capacity and I/Os matter as well as systems’ performance, bandwidth and data protection. Thus, enterprise tenants demand secure and economic data storage yet flexible access on their cloud data. In this paper, we propose a secure de-duplication solution for enterprise tenants to leverage the benefits of cloud storage while reducing operation cost and protecting privacy. First, the solution uses a proxy to do flexible group access control which supports secure de-duplication within a group; Second, the solution supports scalable clustering of proxies to support large-scale data access; Third, the solution can be integrated with cloud storage seamlessly. We implemented and tested our solution by integrating it with Dropbox. Secure de-duplication in a group is performed at low data transfer latency and small storage overhead as compared to de-duplication on plaintext

Security: Hash Function-authentications

As security or firewall administrator, we got basically the same concerns (as a plumber) the size of the pipe the contents of the pipe, making sure the correct traffic is in the correct pipes and keeping the pipes from splitting and leaking all over the places of course like plumbers. When the pipes do leak: we are the ones responsible for cleaning up the mess and we are the ones who come up smelling awful. Firewall is a device that is used to provide protection to a system from network-based security threats. The firewall uses service, behavior, user and direction control techniques

Cryptanalytic Attacks on IDEA Block Cipher

International data encryption algorithm (IDEA) is a secret key or symmetric key block cipher. The purpose of IDEA was to replace data encryption standard (DES) cipher, which became practically insecure due to its small key size of 56 bits and increase in computational power of systems. IDEA cipher mainly to provide data confidentiality in variety of applications such as commercial and financial application e.g. pretty good privacy (PGP) protocol. Till 2015, no successful linear or algebraic weaknesses IDEA of have been reported. In this paper, author explained IDEA cipher, its application in PGP and did a systematic survey of various attacks attempted on IDEA cipher. The best cryptanalysis result which applied to all keys could break IDEA up to 6 rounds out of 8.5 rounds of the full IDEA cipher1. But the attack requires 264 known plaintexts and 2126.8 operations for reduced round version. This attack is practically not feasible due to above mention mammoth data and time requirements. So IDEA cipher is still completely secure for practical usage. PGP v2.0 uses IDEA cipher in place of BassOmatic which was found to be insecure for providing data confidentiality

On the security of NoSQL cloud database services

Processing a vast volume of data generated by web, mobile and Internet-enabled devices, necessitates a scalable and flexible data management system. Database-as-a-Service (DBaaS) is a new cloud computing paradigm, promising a cost-effective and scalable, fully-managed database functionality meeting the requirements of online data processing. Although DBaaS offers many benefits it also introduces new threats and vulnerabilities. While many traditional data processing threats remain, DBaaS introduces new challenges such as confidentiality violation and information leakage in the presence of privileged malicious insiders and adds new dimension to the data security. We address the problem of building a secure DBaaS for a public cloud infrastructure where, the Cloud Service Provider (CSP) is not completely trusted by the data owner. We present a high level description of several architectures combining modern cryptographic primitives for achieving this goal. A novel searchable security scheme is proposed to leverage secure query processing in presence of a malicious cloud insider without disclosing sensitive information. A holistic database security scheme comprised of data confidentiality and information leakage prevention is proposed in this dissertation. The main contributions of our work are: (i) A searchable security scheme for non-relational databases of the cloud DBaaS; (ii) Leakage minimization in the untrusted cloud. The analysis of experiments that employ a set of established cryptographic techniques to protect databases and minimize information leakage, proves that the performance of the proposed solution is bounded by communication cost rather than by the cryptographic computational effort

Tunable Security for Deployable Data Outsourcing

Security mechanisms like encryption negatively affect other software quality characteristics like efficiency. To cope with such trade-offs, it is preferable to build approaches that allow to tune the trade-offs after the implementation and design phase. This book introduces a methodology that can be used to build such tunable approaches. The book shows how the proposed methodology can be applied in the domains of database outsourcing, identity management, and credential management

On the security of multivariate encryption schemes

A criptografia moderna está em perigo por causa dos computadores quânticos, mesmo que, limitados por hardware, já existem algoritmos que podem quebrar os esquemas de chave pública mais utilizados para tráfego de informação. Criptografia multivariável é um bom candidato para criação de esquemas criptográficos seguros até para computadores quânticos, pois são baseadas em um problema NP-Difícil. Nesse trabalho, nós explicamos ataques comuns a criptossistemas multivariáveis além de estudarmos a teoria e implementação deles

Split Without a Leak: Reducing Privacy Leakage in Split Learning

The popularity of Deep Learning (DL) makes the privacy of sensitive data more imperative than ever. As a result, various privacy-preserving techniques have been implemented to preserve user data privacy in DL. Among various privacy-preserving techniques, collaborative learning techniques, such as Split Learning (SL) have been utilized to accelerate the learning and prediction process. Initially, SL was considered a promising approach to data privacy. However, subsequent research has demonstrated that SL is susceptible to many types of attacks and, therefore, it cannot serve as a privacy-preserving technique. Meanwhile, countermeasures using a combination of SL and encryption have also been introduced to achieve privacy-preserving deep learning. In this work, we propose a hybrid approach using SL and Homomorphic Encryption (HE). The idea behind it is that the client encrypts the activation map (the output of the split layer between the client and the server) before sending it to the server. Hence, during both forward and backward propagation, the server cannot reconstruct the client’s input data from the intermediate activation map. This improvement is important as it reduces privacy leakage compared to other SL-based works, where the server can gain valuable information about the client’s input. In addition, on the MIT-BIH dataset, our proposed hybrid approach using SL and HE yields faster training time (about~6 times) and significantly reduced communication overhead (almost~160 times) compared to other HE-based approaches, thereby offering improved privacy protection for sensitive data in DL