Rodrigo Elia Assad

Measuring Distributed Applications through MapReduce and Traffic Analysis

Monitoring and evaluating distributed systems at runtime is a difficult effort. Network traffic analysis may be used to analyse distributed systems, but the capacity to analyse large amount of traffic is a challenge. This work proposes the use of Map Reduce for deeply inspecting distributed systems network traffic, evaluating the effectiveness and the processing capacity of Map Reduce for this inspection.

Accounting Federated Clouds Based on the JiTCloud Platform

Cloud accounting refers to how cloud usage is recorded and charged. We identified four federated cloud platforms which do not include an accounting system. This work presents an accounting mechanism implemented for one of these platforms focused on IaaS. Further, we analyse our proposal in a qualitative fashion.

USTO.RE: a private cloud storage software system

Cloud computing is a computing model where hardware, platforms and software are seen as services; viz. Infrastructure as a Service, Platform as a Service, and Software as a Service, respectively. Data as a Service (DaaS) is based on the concept that the product, data in this case, can be provided on demand to the user, regardless of geographic or organizational separation between provider and consumer. DaaS applications are for the most part based on excessive data replication in order to guarantee data availability, which means excessive costs in hardware investments. This white paper presents the specification, implementation and evaluation of a system called USTO.RE which aims to be an effective and low-cost alternative for storing data, thereby mitigating the problem of excessive data replication and thus allows itself to be considered a reliable platform from the perspective of data availability. Evaluation scenarios and the results achieved in our experiments to evaluate the system as well as possible lines for future development will be presented.

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.

aCCountS: A Service-Oriented Architecture for Flexible Pricing in Cloud Infrastructure

Cloud Computing is a recent paradigm where different IT resources such as applications or hardware are quickly provisioned to customers through a pay per use model. Substantial research has already been conducted concerning pricing services in cloud computing, but they lack on flexibility to establish how services are accounted. These services seem also very dependent on specific cloud infrastructures. This paper proposes an architecture for charging cloud services decoupled from specific providers. This service is complemented by a domain specific language that allows the creation of flexible pricing policies. Such policies aims at supporting cloud billing requirements collected from a survey, allowing the construction of rules that meet different customer profiles. Based on this architecture, a prototype has been implemented and tested to validate our proposal in two different cloud infrastructures. These experiments aims at testing (i) the correctness of the charging flow between two components (server and agent) and (ii) the invoice calculation.

Towards Automated Deployment of Self-adaptive Applications on Hybrid Clouds (Short Paper)

Cloud computing promises high dynamism, flexibility, and elasticity of applications at lower infrastructure costs. However, resource management, portability, and interoperability remain a challenge for cloud application users, since the current major cloud application providers have not converged to a standard interface, and the deployment supporting tools are highly heterogeneous. Besides, by their very nature, cloud applications bring serious traceability, security and privacy issues. This position paper describes a research thread on an extensible Domain Specific Language (DSL), a platform for the automated deployment , and a generic architecture of an ops application manager for self-adaptive distributed applications on hybrid cloud infrastructures. The idea is to overcome the cited limitations by empowering the cloud applications with self-configuration, self-healing, and self-protection capabilities. Such autonomous governance can be achieved by letting cloud users define their policies concerning security, data protection, dependability and functional compliance behavior using the proposed DSL. Real world trials in different application domains are discussed

uStorage - A Storage Architecture to Provide Block-Level Storage Through Object-Based Storage

Block-level Storage is widely used to support heavy workloads. It can be directly accessed by the operating system, but it faces some durability issues, hardware limitations and performance degradation in geographically distributed systems. Object-based Storage Device (OSD) is a data storage concept widely used to support write-once-read-many (WORM) systems. Because OSD contains data, metadata and an unique identifier, it becomes very powerful and customizable. OSDs are ideal for solving the increasing problems of data growth and resilience requirements while mitigating costs. This paper describes a scalable storage architecture that uses OSD from a distributed P2P Cloud Storage system and delivers a Block-level Storage layer to the user. This architecture combines the advantages of the replication, reliability, and scalability of a OSD on commodity hardware with the simplicity of raw block for data-intensive workload. We retrieve data from the OSD in a set of blocks called buckets, allowing read-ahead operations to improve the performance of the raw block layer. Through this architecture we show the possibility of using OSD on the back end and deliver a storage layer based on raw blocks with better performance to the end user. We evaluated the proposed architecture based on the cache behavior to understand non-functional properties. Experiments were performed with different cache sizes. High throughput performance was measured for heavy workloads at the two storage layers.

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.