ABSTRACT:

The use of cloud computing has increased rapidly in many organizations. Cloud computing provides many benefits in terms of low cost and accessibility of data. Ensuring the security of cloud computing is a major factor in the cloud computing environment, as users often store sensitive information with cloud storage providers but these providers may be untrusted.

ABSTRACT

Cloud computing offers reduced capital expenditure, operational risks, complexity and maintenance, and increased scalability while providing services at different abstraction levels, namely Software-as-a-Service (SaaS),Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS).

ABSTRACT

We propose a different approach for securing data in the cloud using offensive decoy technology. We monitor data access in the cloud and detect abnormal data access patterns. When unauthorized access is suspected and then verified using challenge questions, we launch a disinformation attack by returning large amounts of decoy information to the attacker .This protects against the misuse of the user’s real data. Experiments conducted in a local file setting provide evidence that this approach may provide unprecedented levels of user data security in a Cloud environment.

ABSTRACT

We propose a different approach for securing data in the cloud using offensive decoy technology. We monitor data access in the cloud and detect abnormal data access patterns.

ABSTRACT

The use of Cloud Computing Services appears to offer significant cost advantages. Particularly start-up companies benefit from these advantages, since frequently they do not operate an internal IT infrastructure. But are costs associated with Cloud Computing Services really that low? We found that particular cost types and factors are frequently underestimated by practitioners.

ABSTRACT

We address the problem of resource management for a large-scale cloud environment that hosts sites.Our contribution centers around outlining a distributed middleware architecture and presenting one of its keyelements, a gossip protocol that meets our design goals: fairness of resource allocation with respect to hosted sites, efficient adaptation to load changes and scalability in terms of both the number of machines and sites.

ABSTRACT:

We address the problem of dynamic resource management for a large-scale cloud environment. Our contribution includes outlining a distributed middleware architecture and presenting one of its key elements: a gossip protocol that (1) ensures fair resource allocation among sites/applications, (2) dynamically adapts the allocation to load changes and (3) scales both in the number of physical machines and sites/applications.

Abstract:

In many applications, including location based services, queries may not be precise. In this paper, we study the problem of efficiently computing range aggregates in a multidimensional space when the query location is uncertain. Specifically, for a querypoint Q whose location is uncertain and a set S of points in a multi-dimensional space, we want to calculate the aggregate (e.g., count, average and sum) over the subset S_ of S such that for each p ∈ S_, Q has at least probability θ within the distance γ to p.

Abstract:

We introduce two approaches for improving privacy policy management in online social networks. First, we introduce a mechanism using proven clustering techniques that assists users in grouping their friends for group based policy management approaches.

ABSTRACT

Many celebrities and experts from various fields may have been referred by not only their personal names but also by their aliases on web. Aliases are very important in information retrieval to retrieve complete information about a personal name from the web, as some of the web pages of the person may also be referred by his aliases. The aliases for a personal name are extracted by previously proposed alias extraction method.