A Marketplace for Efficient and Secure Caching for IoT Applications in 5G Networks

As the communication industry is progressing towards fifth generation (5G) of cellular networks, the traffic it carries is also shifting from high data rate traffic from cellular users to a mixture of high data rate and low data rate traffic from Internet of Things (IoT) applications. Moreover, the need to efficiently access Internet data is also increasing across 5G networks. Caching contents at the network edge is considered as a promising approach to reduce the delivery time. In this paper, we propose a marketplace for providing a number of caching options for a broad range of applications. In addition, we propose a security scheme to secure the caching contents with a simultaneous potential of reducing the duplicate contents from the caching server by dividing a file into smaller chunks. We model different caching scenarios in NS-3 and present the performance evaluation of our proposal in terms of latency and throughput gains for various chunk sizes

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

GraphSE2^2: An Encrypted Graph Database for Privacy-Preserving Social Search

In this paper, we propose GraphSE$^2$, an encrypted graph database for online social network services to address massive data breaches. GraphSE$^2$ preserves the functionality of social search, a key enabler for quality social network services, where social search queries are conducted on a large-scale social graph and meanwhile perform set and computational operations on user-generated contents. To enable efficient privacy-preserving social search, GraphSE$^2$ provides an encrypted structural data model to facilitate parallel and encrypted graph data access. It is also designed to decompose complex social search queries into atomic operations and realise them via interchangeable protocols in a fast and scalable manner. We build GraphSE$^2$ with various queries supported in the Facebook graph search engine and implement a full-fledged prototype. Extensive evaluations on Azure Cloud demonstrate that GraphSE$^2$ is practical for querying a social graph with a million of users.Comment: This is the full version of our AsiaCCS paper "GraphSE$^2$: An Encrypted Graph Database for Privacy-Preserving Social Search". It includes the security proof of the proposed scheme. If you want to cite our work, please cite the conference version of i

Secure communication using dynamic VPN provisioning in an Inter-Cloud environment

Most of the current cloud computing platforms offer Infrastructure as a Service (IaaS) model, which aims to provision basic virtualised computing resources as on-demand and dynamic services. Nevertheless, a single cloud does not have limitless resources to offer to its users, hence the notion of an Inter-Cloud enviroment where a cloud can use the infrastructure resources of other clouds. However, there is no common framework in existence that allows the srevice owners to seamlessly provision even some basic services across multiple cloud service providers, albeit not due to any inherent incompatibility or proprietary nature of the foundation technologies on which these cloud platforms are built. In this paper we present a novel solution which aims to cover a gap in a subsection of this problem domain. Our solution offer a security architecture that enables service owners to provision a dynamic and service-oriented secure virtual private network on top of multiple cloud IaaS providers. It does this by leveraging the scalability, robustness and flexibility of peer- to-peer overlay techniques to eliminate the manual configuration, key management and peer churn problems encountered in setting up the secure communication channels dynamically, between different components of a typical service that is deployed on multiple clouds. We present the implementation details of our solution as well as experimental results carried out on two commercial clouds

Secure Cloud Storage with Client-Side Encryption Using a Trusted Execution Environment

With the evolution of computer systems, the amount of sensitive data to be stored as well as the number of threats on these data grow up, making the data confidentiality increasingly important to computer users. Currently, with devices always connected to the Internet, the use of cloud data storage services has become practical and common, allowing quick access to such data wherever the user is. Such practicality brings with it a concern, precisely the confidentiality of the data which is delivered to third parties for storage. In the home environment, disk encryption tools have gained special attention from users, being used on personal computers and also having native options in some smartphone operating systems. The present work uses the data sealing, feature provided by the Intel Software Guard Extensions (Intel SGX) technology, for file encryption. A virtual file system is created in which applications can store their data, keeping the security guarantees provided by the Intel SGX technology, before send the data to a storage provider. This way, even if the storage provider is compromised, the data are safe. To validate the proposal, the Cryptomator software, which is a free client-side encryption tool for cloud files, was integrated with an Intel SGX application (enclave) for data sealing. The results demonstrate that the solution is feasible, in terms of performance and security, and can be expanded and refined for practical use and integration with cloud synchronization services

Security, Performance and Energy Trade-offs of Hardware-assisted Memory Protection Mechanisms

The deployment of large-scale distributed systems, e.g., publish-subscribe platforms, that operate over sensitive data using the infrastructure of public cloud providers, is nowadays heavily hindered by the surging lack of trust toward the cloud operators. Although purely software-based solutions exist to protect the confidentiality of data and the processing itself, such as homomorphic encryption schemes, their performance is far from being practical under real-world workloads. The performance trade-offs of two novel hardware-assisted memory protection mechanisms, namely AMD SEV and Intel SGX - currently available on the market to tackle this problem, are described in this practical experience. Specifically, we implement and evaluate a publish/subscribe use-case and evaluate the impact of the memory protection mechanisms and the resulting performance. This paper reports on the experience gained while building this system, in particular when having to cope with the technical limitations imposed by SEV and SGX. Several trade-offs that provide valuable insights in terms of latency, throughput, processing time and energy requirements are exhibited by means of micro- and macro-benchmarks.Comment: European Commission Project: LEGaTO - Low Energy Toolset for Heterogeneous Computing (EC-H2020-780681