2 Search Results for "Baptista, Tiago"

Document
DOI: 10.4230/OASIcs.SLATE.2021.14
Using Machine Learning for Vulnerability Detection and Classification

Authors: Tiago Baptista, Nuno Oliveira, and Pedro Rangel Henriques

Published in: OASIcs, Volume 94, 10th Symposium on Languages, Applications and Technologies (SLATE 2021)

Abstract
The work described in this paper aims at developing a machine learning based tool for automatic identification of vulnerabilities on programs (source, high level code), that uses an abstract syntax tree representation. It is based on FastScan, using code2seq approach. Fastscan is a recently developed system aimed capable of detecting vulnerabilities in source code using machine learning techniques. Nevertheless, FastScan is not able of identifying the vulnerability type. In the presented work the main goal is to go further and develop a method to identify specific types of vulnerabilities. As will be shown, the goal will be achieved by optimizing the model’s hyperparameters, changing the method of preprocessing the input data and developing an architecture that brings together multiple models to predict different specific vulnerabilities. The preliminary results obtained from the training stage, are very promising. The best f1 metric obtained is 93% resulting in a precision of 90% and accuracy of 85%, according to the performed tests and regarding a trained model to predict vulnerabilities of the injection type.
Cite as

Tiago Baptista, Nuno Oliveira, and Pedro Rangel Henriques. Using Machine Learning for Vulnerability Detection and Classification. In 10th Symposium on Languages, Applications and Technologies (SLATE 2021). Open Access Series in Informatics (OASIcs), Volume 94, pp. 14:1-14:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{baptista_et_al:OASIcs.SLATE.2021.14,
  author =	{Baptista, Tiago and Oliveira, Nuno and Henriques, Pedro Rangel},
  title =	{{Using Machine Learning for Vulnerability Detection and Classification}},
  booktitle =	{10th Symposium on Languages, Applications and Technologies (SLATE 2021)},
  pages =	{14:1--14:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-202-0},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{94},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Sim\~{o}es, Alberto and Portela, Filipe and Pereira, Maria Jo\~{a}o},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2021.14},
  URN =		{urn:nbn:de:0030-drops-144315},
  doi =		{10.4230/OASIcs.SLATE.2021.14},
  annote =	{Keywords: Vulnerability Detection, Source Code Analysis, Machine Learning}
}
Document
DOI: 10.4230/OASIcs.SLATE.2013.271
Syntactic REAP.PT: Exercises on Clitic Pronouning

Authors: Tiago Freitas, Jorge Baptista, and Nuno Mamede

Published in: OASIcs, Volume 29, 2nd Symposium on Languages, Applications and Technologies (2013)

Abstract
The emerging interdisciplinary field of Intelligent Computer Assisted Language Learning (ICALL) aims to integrate the knowledge from computational linguistics into computer-assisted language learning (CALL). REAP.PT is a project emerging from this new field, aiming to teach Portuguese in an innovative and appealing way, and adapted to each student. In this paper, we present a new improvement of the REAP.PT system, consisting in developing new, automatically generated, syntactic exercises. These exercises deal with the complex phenomenon of pronominalization, that is, the substitution of a syntactic constituent with an adequate pronominal form. Though the transformation may seem simple, it involves complex lexical, syntactical and semantic constraints. The issues on pronominalization in Portuguese make it a particularly difficult aspect of language learning for non-native speakers. On the other hand, even native speakers can often be uncertain about the correct clitic positioning, due to the complexity and interaction of competing factors governing this phenomenon. A new architecture for automatic syntactic exercise generation is proposed. It proved invaluable in easing the development of this complex exercise, and is expected to make a relevant step forward in the development of future syntactic exercises, with the potential of becoming a syntactic exercise generation framework. A pioneer feedback system with detailed and automatically generated explanations for each answer is also presented, improving the learning experience, as stated in user comments. The expert evaluation and crowd-sourced testing positive results demonstrated the validity of the present approach.
Cite as

Tiago Freitas, Jorge Baptista, and Nuno Mamede. Syntactic REAP.PT: Exercises on Clitic Pronouning. In 2nd Symposium on Languages, Applications and Technologies. Open Access Series in Informatics (OASIcs), Volume 29, pp. 271-285, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@InProceedings{freitas_et_al:OASIcs.SLATE.2013.271,
  author =	{Freitas, Tiago and Baptista, Jorge and Mamede, Nuno},
  title =	{{Syntactic REAP.PT: Exercises on Clitic Pronouning}},
  booktitle =	{2nd Symposium on Languages, Applications and Technologies},
  pages =	{271--285},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-52-1},
  ISSN =	{2190-6807},
  year =	{2013},
  volume =	{29},
  editor =	{Leal, Jos\'{e} Paulo and Rocha, Ricardo and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2013.271},
  URN =		{urn:nbn:de:0030-drops-40433},
  doi =		{10.4230/OASIcs.SLATE.2013.271},
  annote =	{Keywords: Intelligent Computer Assisted Language Learning (ICALL), Portuguese, Syntactic Exercises, Automatic Exercise Generation, Clitic Pronouning}
}
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