Carlo Marcelo Revoredo da Silva

A Privacy Maturity Model for Cloud Storage Services

The purpose of this article is to present a PrivacyMaturity Model of services offered by Cloud ComputingProviders in the context of Cloud Storage. This study aims topresent an overview of the current barriers in these scenariosand present a model based on technical analysis of maturity inthese environments. We present the goals to be achieved in thisresearch, as well as the strategies to be pursued to the contents of sensitive data in order to establish a level of effectiveprivacy. Also featuring is planning an architectural model as aprototype, and set in stages as its research and implementation.

ConvertView - A Tool for Conversion and Visualization of Open Heterogenic Governmental Data to the RDF Standard

The diversity and relevance of the information made available by many governments, using the principles defined by the open data manifest, creates an opportunity for the populations aid in many fields of governmental administration, such as security, transportation, health care and education. However, most of this information was generated in unstructured digital files, making them hard to use. This paper presents an approach for the structuring of data, improving the processing and extraction of information. Thus, we created a tool based on a cloud computing environment, which has high processing and storage ability, to create files in a homogeneous and structured format, allowing for ominous and specific queries; contributing to the access of the information.

A cloud-based recommendation model

The recommendation systems aim to minimize information overload by helping users in searching desired information. Faced with this scenario, we investigate the use of cloud factors able to have a positive influence on generating recommendations. Thus, we present a new, simple model based on cloud features which is associated with the content-based technique of recommendation. The practical applicability of data storage environments in the cloud provides the best use of cloud resources and meets users preferences.

A meta-analysis for security threats over the Web ecosystem

This article presents an analysis on the attacks related to the sensitive data breach in the Web ecosystem. The study is based on an Meta-Analysis which identified the significance of 21 years of relevant contributions to the subject. Considering the results we elaborate two contributions: (i) we group attacks according to their behavior and (ii) we reveal the most serious emerging attacks. Additionally, we present our critical sense in relation to an overall perspective on the results.

Towards a taxonomy for security threats on the web ecosystem

The aim of this paper is to present a taxonomy for security threats on the Web ecosystem. We proposes a classification model based on 21 vectors divided into 8 distinct security threats, making use of levels of abstraction and criteria for discrimination which consider propagation and similarity in vulnerabilities. We also propose to estimate the risk factor and impacts on assets, considering data breaches, human aspects and service reliability. In addition, we validate the taxonomic model proposed through the catalogues of attacks facing the public. Thus, it was possible to observe its applicability for most of the attacks which appear before the public.

Aegis: A Lightweight Tool for Prevent Frauds in Web Browsers

Based on its daily use and volume of its applications -- both domestic and corporate environments -- it cannot be denied that Web Browsers are very important tools. However, due to the increase of its use, the web environment presents itself as an increasingly hostile place where people perform malicious cyber crimes aiming to steal or to tamper sensitive information of the web uses. These illegal activities are often performed by using social engineering techniques through web browser. To mitigate this problem, this paper proposes a tool which is capable to identify the fraud vectors focused on the privacy violation of the web browser users.