State of The Art and Hot Aspects in Cloud Data Storage Security

Along with the evolution of cloud computing and cloud storage towards matu- rity, researchers have analyzed an increasing range of cloud computing security aspects, data security being an important topic in this area. In this paper, we examine the state of the art in cloud storage security through an overview of selected peer reviewed publications. We address the question of defining cloud storage security and its different aspects, as well as enumerate the main vec- tors of attack on cloud storage. The reviewed papers present techniques for key management and controlled disclosure of encrypted data in cloud storage, while novel ideas regarding secure operations on encrypted data and methods for pro- tection of data in fully virtualized environments provide a glimpse of the toolbox available for securing cloud storage. Finally, new challenges such as emergent government regulation call for solutions to problems that did not receive enough attention in earlier stages of cloud computing, such as for example geographical location of data. The methods presented in the papers selected for this review represent only a small fraction of the wide research effort within cloud storage security. Nevertheless, they serve as an indication of the diversity of problems that are being addressed

Securely Launching Virtual Machines on Trustworthy Platforms in a Public Cloud

In this paper we consider the Infrastructure-as-a-Service (IaaS) cloud model which allows cloud users to run their own virtual machines (VMs) on available cloud computing resources. IaaS gives enterprises the possibility to outsource their process workloads with minimal effort and expense. However, one major problem with existing approaches of cloud leasing, is that the users can only get contractual guarantees regarding the integrity of the offered platforms. The fact that the IaaS user himself or herself cannot verify the provider promised cloud platform integrity, is a security risk which threatens to prevent the IaaS business in general. In this paper we address this issue and propose a novel secure VM launch protocol using Trusted Computing techniques. This protocol allows the cloud IaaS users to securely bind the VM to a trusted computer configuration such that the clear text VM only will run on a platform that has been booted into a trustworthy state. This capability builds user confidence and can serve as an important enabler for creating trust in public clouds. We evaluate the feasibility of our proposed protocol via a full scale system implementation and perform a system security analysis

Overview of Polkadot and its Design Considerations

In this paper we describe the design components of the heterogenous multi-chain protocol Polkadot and explain how these components help Polkadot address some of the existing shortcomings of blockchain technologies. At present, a vast number of blockchain projects have been introduced and employed with various features that are not necessarily designed to work with each other. This makes it difficult for users to utilise a large number of applications on different blockchain projects. Moreover, with the increase in number of projects the security that each one is providing individually becomes weaker. Polkadot aims to provide a scalable and interoperable framework for multiple chains with pooled security that is achieved by the collection of components described in this paper

Deploying Virtual Machines on Shared Platforms

In this report, we describe mechanisms for secure deployment of virtual machines on shared platforms looking into a telecommunication cloud use case, which is also presented in this report. The architecture we present focuses on the security requirements of the major stakeholders’ part of the scenario we present. This report comprehensively covers all major security aspects including different security mechanisms and protocols, leveraging existing standards and state-of-the art wherever applicable. In particular, our architecture uses TCG technologies for trust establishment in the deployment of operator virtual machines on shared resource platforms. We also propose a novel procedure for securely launching and cryptographically binding a virtual machine to a target platform thereby protecting the operator virtual machine and its related credentials

SANNS: Scaling Up Secure Approximate k-Nearest Neighbors Search

The $k$-Nearest Neighbor Search ($k$-NNS) is the backbone of several cloud-based services such as recommender systems, face recognition, and database search on text and images. In these services, the client sends the query to the cloud server and receives the response in which case the query and response are revealed to the service provider. Such data disclosures are unacceptable in several scenarios due to the sensitivity of data and/or privacy laws. In this paper, we introduce SANNS, a system for secure $k$-NNS that keeps client's query and the search result confidential. SANNS comprises two protocols: an optimized linear scan and a protocol based on a novel sublinear time clustering-based algorithm. We prove the security of both protocols in the standard semi-honest model. The protocols are built upon several state-of-the-art cryptographic primitives such as lattice-based additively homomorphic encryption, distributed oblivious RAM, and garbled circuits. We provide several contributions to each of these primitives which are applicable to other secure computation tasks. Both of our protocols rely on a new circuit for the approximate top-$k$ selection from $n$ numbers that is built from $O(n + k^2)$ comparators. We have implemented our proposed system and performed extensive experimental results on four datasets in two different computation environments, demonstrating more than $18-31\times$ faster response time compared to optimally implemented protocols from the prior work. Moreover, SANNS is the first work that scales to the database of 10 million entries, pushing the limit by more than two orders of magnitude.Comment: 18 pages, to appear at USENIX Security Symposium 202