Fabiane Cristine Dillenburg

Towards Theorem Proving Graph Grammars using Event-B

Graph grammars may be used as specification technique for different kinds of systems, specially in situations in which states are complex structures that can be adequately modeled as graphs (possibly with an attribute data part) and in which the behavior involves a large amount of parallelism and can be described as reactions to stimuli that can be observed in the state of the system. The verification of properties of such systems is a difficult task due to many aspects: in many situations the systems have an infinite number of states; states themselves are complex and large; there are a number of different computation possibilities due to the fact that rule applications may occur in parallel. There are already some approaches to verification of graph grammars based on model checking, but in these cases only finite state systems can be analyzed. Other approaches propose over- and/or under-approximations of the state-space, but in this case it is not possible to check arbitrary properties. In this work, we propose to use the Event-B formal method and its theorem proving tools to analyze graph grammars. We show that a graph grammar can be translated into an Event-B specification preserving its semantics, such that one can use several theorem provers available for Event-B to analyze the reachable states of the original graph grammar. The translation is based on a relational definition of graph grammars, that was shown to be equivalent to the Single-Pushout approach to graph grammars.

Towards a programming model for context-aware applications

In mobile computing scenarios, users move in different environments and applications can automatically explore their surroundings. This type of context-aware application is an emerging trend, so far not widely disseminated. We believe that the proposal of a programming model specifically designed for the specification of context-aware applications, using general abstractions, will foster a rapidly widespread of such kind of software. In this article, we propose the use of the Holoparadigm (in short Holo) to fill this gap. We created a programming language based on Holo (called HoloL) to demonstrate the strengths of Holoparadigm to develop context-aware applications. The article uses a sample scenario to show the Holos practical aspects related to implementation of context-aware applications. We also present a platform to HoloL (called HoloEnv), composed of a compiler, a virtual machine, and a distributed execution environment. Finally, different performance aspects of the HoloEnvs components were evaluated through experimental results.

Identification of intrusion scenarios through classification, characterization and analysis of firewall events

The content analysis of firewall logs is essential (i) to quantify and identify accesses to external and private networks, (ii) to follow the historical growth of accesses volume and applications used, (iii) to debug problems on the configuration of filtering rules and (iv) to recognize suspicious event sequences that indicate strategies used by intruders in attempts to obtain non-authorized access to stations and services. The paper presents an approach to classify, characterize and analyze events generated by firewalls. The proposed approach explores the case-based reasoning technique to identify possible intrusion scenarios. The paper also describes the validation of our approach carried out based on real logs generated during one week by the university firewall.

Context-oriented exception handling

The growing availability of small, faster computational devices has made mobile computing more popular in our daily life. The development of new applications demands an adoption of programming languages to this new reality, in order to take advantage of new available technologies. In this context, this paper presents a proposal for the specification of context-oriented exception handling features, aiming the development of mobile and ubiquitous applications. These features were implemented in the Holoparadigm mobile development and execution platform. Also, these features were tested using specially crafted applications that triggered exception handling.

NF κ B pathway analysis: an approach to analyze gene co-expression networks employing feedback cycles

The genes of the NFκB pathway are involved in the control of a plethora of biological processes ranking from inhibition of apoptosis to metastasis in cancer. It has been described that Gliobastoma multiforme (GBM) patients carry aberrant NFκB activation, but the molecular mechanisms are not completely understood. Here, we present a NFκB pathway analysis in tumor specimens of GBM compared to non-neoplasic brain tissues, based on the different kind of cycles found among genes of a gene co-expression network constructed using quantized data obtained from the microarrays. A cycle is a closed walk with all vertices distinct (except the first and last). Thanks to this way of finding relations among genes, a more robust interpretation of gene correlations is possible, because the cycles are associated with feedback mechanisms that are very common in biological networks. In GBM samples, we could conclude that the stoichiometric relationship between genes involved in NFκB pathway regulation is unbalanced. This can be measured and explained by the identification of a cycle. This conclusion helps to understand more about the biology of this type of tumor.

Spotting Intrusion Scenarios from Firewall Logs Through a Case-Based Reasoning Approach

Despite neglected by most security managers due to the low availability of tools, the content analysis of firewall logs is fundamental (a) to measure and identify accesses to external and private networks, (b) to access the historical growth of accesses volume and applications used, (c) to debug problems on the configuration of filtering rules and (d) to recognize suspicious event sequences that indicate strategies used by intruders in attempt to obtain non-authorized access to stations and services. This paper presents an approach to classify, characterize and analyze events generated by firewalls. The proposed approach explores the case-based reasoning technique, from the Artificial Intelligence field, to identify possible intrusion scenarios. The paper also describes the validation of our approach carried out based on real logs generated along one week by the university firewall.