Miranda Mowbray

TrustCloud: A Framework for Accountability and Trust in Cloud Computing

The key barrier to widespread uptake of cloud computing is the lack of trust in clouds by potential customers. While preventive controls for security and privacy are actively researched, there is still little focus on detective controls related to cloud accountability and audit ability. The complexity resulting from large-scale virtualization and data distribution carried out in current clouds has revealed an urgent research agenda for cloud accountability, as has the shift in focus of customer concerns from servers to data. This paper discusses key issues and challenges in achieving a trusted cloud through the use of detective controls, and presents the Trust Cloud framework, which addresses accountability in cloud computing via technical and policy-based approaches.

A Privacy Manager for Cloud Computing

We describe a privacy manager for cloud computing, which reduces the risk to the cloud computing user of their private data being stolen or misused, and also assists the cloud computing provider to conform to privacy law. We describe different possible architectures for privacy management in cloud computing; give an algebraic description of obfuscation, one of the features of the privacy manager; and describe how the privacy manager might be used to protect private metadata of online photos.

Labs of the World, Unite!!!

AbstracteScience is rapidly changing the way we do research. As a result, many research labs now need non-trivial computational power. Grid and voluntary computing are well-established solutions for this need. However, not all labs can effectively benefit from these technologies. In particular, small and medium research labs (which are the majority of the labs in the world) have a hard time using these technologies as they demand high visibility projects and/or high-qualified computer personnel. This paper describes OurGrid, a system designed to fill this gap. OurGrid is an open, free-to-join, cooperative Grid in which labs donate their idle computational resources in exchange for accessing other labs’ idle resources when needed. It relies on an incentive mechanism that makes it in the best interest of participants to collaborate with the system, employs a novel application scheduling technique that demands very little information, and uses virtual machines to isolate applications and thus provide security. The vision is that OurGrid enables labs to combine their resources in a massive worldwide computing platform. OurGrid is in production since December 2004. Any lab can join it by downloading its software from http://www.ourgrid.org.

A client-based privacy manager for cloud computing

A significant barrier to the adoption of cloud services is that users fear data leakage and loss of privacy if their sensitive data is processed in the cloud. In this paper, we describe a client-based privacy manager that helps reduce this risk, and that provides additional privacy-related benefits. We assess its usage within a variety of cloud computing scenarios. We have built a proof-of-concept demo that shows how privacy may be protected via reducing the amount of sensitive information sent to the cloud.

Discouraging free riding in a peer-to-peer CPU-sharing grid

Grid computing has excited many with the promise of access to huge amounts of resources distributed across the globe. However, there are no largely adopted solutions for automatically assembling grids, and this limits the scale of todays grids. Some argue that this is due to the overwhelming complexity of the proposed economy-based solutions. Peer-to-peer grids Iwve emerged as a less complex alternative. We are currently deploying OurGrid, one such peer-to-peer grid. OurGrid is a CPU-sharing grid that targets bag-of-tasks applications (i.e. parallel applications whose tasks are independent). In order to ease system deployment, OurGrid is based on a very lightweight autonomous reputation scheme. Free riding is an important issue for any peer-to-peer system. The aim is to show that OurGrids reputation system successfully discourages free riding, making it in each peer s own interest to collaborate with the peer-to-peer community. We show this in two steps. First, we analyze the conditions under which a reputation scheme can discourage free riding in a CPU-sharing grid. Second, we show that OurGrids reputation scheme satisfies these conditions, even in the presence of malicious peers. Unlike other distributed mechanisms for discouraging free riding, OurGrids reputation scheme achieves this without requiring a shared cryptographic infrastructure or specialized storage.

Enhancing privacy in cloud computing via policy-based obfuscation

In this paper, we describe a privacy manager for cloud computing that controls policy-based obfuscation and de-obfuscation of personal, sensitive, or confidential data within cloud service provision. By these means, cloud computing users may reduce the risk of their private data being stolen or misused, and in addition assistance may be given to cloud computing providers in helping them conform to privacy law. We describe different possible architectures for such privacy management in cloud computing, give an algebraic description of obfuscation features provided by the privacy manager, and describe how policies may be defined to control such obfuscation. Furthermore, we assess the performance and scalability of this approach and consider mechanisms to enhance usability. Several examples of how the privacy manager might be used are given, including protection of private metadata associated with online photos and of confidential information contained within share portfolios.

Automatic grid assembly by promoting collaboration in peer-to-peer grids

Currently, most computational grids (systems allowing transparent sharing of computing resources across organizational boundaries) are assembled using human negotiation. This procedure does not scale well, and is too inflexible to allow for large open grids. Peer-to-peer (P2P) grids present an alternative way to build grids with many sites. However, to actually assemble a large grid, peers must have an incentive to provide resources to the system. In this paper we present an incentive mechanism called the Network of Favors, which makes it in the interest of each participating peer to contribute its spare resources. We show through simulations with up to 10,000 peers and experiments with software implementing the mechanism in a deployed system that the Network of Favors promotes collaboration in a simple, robust and scalable fashion. We also discuss experiences of using OurGrid, a grid based on this mechanism.

A Reciprocation-Based Economy for Multiple Services in Peer-to-Peer Grids

In this paper we study reciprocation-based mechanisms to encourage donation in peer-to-peer grids in which multiple services, such as processing power and data transfers, are shared explicitly. We have modeled such a system and established how peers should assess whether it is profitable to exchange services with another peer, an issue that is not present in the single service case. Unfortunately, this assessment relies on information provided by untrustworthy peers. As an alternative, we have extended, to the case of multiple services, a reciprocation-based mechanism which uses only reliable information gathered locally. We have assessed this mechanism by simulating scenarios in which services are exchanged that are combinations of two different basic services. In the explored scenarios the mechanism performs very well, and can marginalize free riders even when the cost to peers of donating a service is nearly as large as the utility gained by receiving it

Capacity reservation for multimedia traffic

We introduce a new scheduling algorithm for multimedia traffic using capacity reservation. We compare it with other algorithms in the literature. It has been implemented and its worst-case performance has been analysed. It appears to give a noticeably improved quality of service to delay-sensitive traffic.

Impact of peer incentives on the dissemination of polluted content

Recent studies have reported a new form of malicious behavior in file-sharing Peer-to-Peer systems: content pollution. The dissemination of polluted content in a P2P system has the detrimental effect of reducing content availability, and ultimately, decreasing the confidence of users in such systems. Two potential strategies for polluting P2P content are decoy insertion, which consists of injecting corrupted copies of a file into the system, and hash corruption, which consists of injecting a corrupted file with the same hash code as a non-corrupted one. Polluted content disseminates through P2P networks because users typically do not delete the corrupted files that they download.This paper investigates the effectiveness of peer incentives to delete corrupted files in reducing the dissemination of polluted content, considering the two aforementioned pollution mechanisms. Our simulation results show that the effectiveness of incentives is highly dependent on the pollution mechanism. We show that for a pollution dissemintation techinique called hash corruption, only effective incentive mechanisms are able to avoid spreading of polluted content.