Antonis Michalas

Multi-party trust computation in decentralized environments in the presence of malicious adversaries

In this paper, we describe a decentralized privacy-preserving protocol for securely casting trust ratings in distributed reputation systems. Our protocol allows n participants to cast their votes in a way that preserves the privacy of individual values against both internal and external attacks. The protocol is coupled with an extensive theoretical analysis in which we formally prove that our protocol is resistant to collusion against as many as n-1 corrupted nodes in both the semi-honest and malicious adversarial models. The behavior of our protocol is tested in a real P2P network by measuring its communication delay and processing overhead. The experimental results uncover the advantages of our protocol over previous works in the area; without sacrificing security, our decentralized protocol is shown to be almost one order of magnitude faster than the previous best protocol for providing anonymous feedback.

New client puzzle approach for DoS resistance in ad hoc Networks

In this paper we propose a new client puzzle approach to prevent Denial of Service (DoS) attacks in ad hoc networks. Each node in the network first solves a computational problem and with the solution has to create and solve a client puzzle. By combining computational problems with puzzles, we improve the efficiency and latency of the communicating nodes and resistance in DoS attacks. Experimental results show the effectiveness of our approach.

Providing User Security Guarantees in Public Infrastructure Clouds

The infrastructure cloud (IaaS) service model offers improved resource flexibility and availability, where tenants – insulated from the minutiae of hardware maintenance – rent computing resources to deploy and operate complex systems. Large-scale services running on IaaS platforms demonstrate the viability of this model; nevertheless, many organizations operating on sensitive data avoid migrating operations to IaaS platforms due to security concerns. In this paper, we describe a framework for data and operation security in IaaS, consisting of protocols for a trusted launch of virtual machines and domain-based storage protection. We continue with an extensive theoretical analysis with proofs about protocol resistance against attacks in the defined threat model. The protocols allow trust to be established by remotely attesting host platform configuration prior to launching guest virtual machines and ensure confidentiality of data in remote storage, with encryption keys maintained outside of the IaaS domain. Presented experimental results demonstrate the validity and efficiency of the proposed protocols. The framework prototype was implemented on a test bed operating a public electronic health record system, showing that the proposed protocols can be integrated into existing cloud environments.

“One of our hosts in another country”: Challenges of data geolocation in cloud storage

Physical location of data in cloud storage is an increasingly urgent problem. In a short time, it has evolved from the concern of a few regulated businesses to an important consideration for many cloud storage users. One of the characteristics of cloud storage is fluid transfer of data both within and among the data centres of a cloud provider. However, this has weakened the guarantees with respect to control over data replicas, protection of data in transit and physical location of data. This paper addresses the lack of reliable solutions for data placement control in cloud storage systems. We analyse the currently available solutions and identify their shortcomings. Furthermore, we describe a high-level architecture for a trusted, geolocation-based mechanism for data placement control in distributed cloud storage systems, which are the basis of an on-going work to define the detailed protocol and a prototype of such a solution. This mechanism aims to provide granular control over the capabilities of tenants to access data placed on geographically dispersed storage units comprising the cloud storage.

PaaSword: A Holistic Data Privacy and Security by Design Framework for Cloud Services

The valuable transformation of organizations that adopt cloud computing is indisputably accompanied by a number of security threats that should be considered. In this paper, we outline significant ...

Domain based storage protection with secure access control for the cloud

Cloud computing has evolved from a promising concept to one of the fastest growing segments of the IT industry. However, many businesses and individuals continue to view cloud computing as a technology that risks exposing their data to unauthorized users. We introduce a data confidentiality and integrity protection mechanism for Infrastructure-as-a-Service (IaaS) clouds, which relies on trusted computing principles to provide transparent storage isolation between IaaS clients. We also address the absence of reliable data sharing mechanisms, by providing an XML-based language framework which enables clients of IaaS clouds to securely share data and clearly define access rights granted to peers. The proposed improvements have been prototyped as a code extension for a popular cloud platform.

Security aspects of e-Health systems migration to the cloud

As adoption of e-health solutions advances, new computing paradigms - such as cloud computing - bring the potential to improve efficiency in managing medical health records and help reduce costs. However, these opportunities introduce new security risks which can not be ignored. Based on our experience with deploying part of the Swedish electronic health records management system in an infrastructure cloud, we make an overview of major requirements that must be considered when migrating e-health systems to the cloud. Furthermore, we describe in-depth a new attack vector inherent to cloud deployments and present a novel data confidentiality and integrity protection mechanism for infrastructure clouds. This contribution aims to encourage exchange of best practices and lessons learned in migrating public e-health systems to the cloud.

Multi-Party Trust Computation in Decentralized Environments

In this paper, we describe a decentralized privacy- preserving protocol for securely casting trust ratings in distributed reputation systems. Our protocol allows n participants to cast their votes in a way that preserves the privacy of individual values against both internal and external attacks. The protocol is coupled with an extensive theoretical analysis in which we formally prove that our protocol is resistant to collusion against as many as n-1 corrupted nodes in the semi-honest model. The behavior of our protocol is tested in a real P2P network by measuring its communication delay and processing overhead. The experimental results uncover the advantages of our protocol over previous works in the area; without sacrificing security, our decentralized protocol is shown to be almost one order of magnitude faster than the previous best protocol for providing anonymous feedback.

Towards trusted ehealth services in the cloud

As adoption of eHealth solutions advances, new computing paradigms - such as cloud computing - bring the potential to improve efficiency in managing medical health records and help reduce costs. However, these opportunities introduce new security risks which can not be ignored. In this paper, we present a forward-looking design for a privacy-preserving eHealth cloud system. The proposed solution, is based on a Symmetric Searchable Encryption scheme that allows patients of an electronic healthcare system to securely store encrypted versions of their medical data and search directly on them without having to decrypt them first. As a result, the proposed protocol offers better protection than the current available solutions and paves the way for the next generation of eHealth systems.

Vulnerabilities of Decentralized Additive Reputation Systems Regarding the Privacy of Individual Votes

In this paper, we focus on attacks and defense mechanisms in additive reputation systems. We start by surveying the most important protocols that aim to provide privacy between individual voters. Then, we categorize attacks against additive reputation systems considering both malicious querying nodes and malicious reporting nodes that collaborate in order to undermine the vote privacy of the remaining users. To the best of our knowledge this is the first work that provides a description of such malicious behavior under both semi-honest and malicious model. In light of this analysis we demonstrate the inefficiencies of existing protocols.