Publications

Publications by LIAAD

2019

Denial of Service Attacks: Detecting the Frailties of Machine Learning Algorithms in the Classification Process

Authors
Frazao, I; Abreu, PH; Cruz, T; Araújo, H; Simoes, P;

Publication
CRITICAL INFORMATION INFRASTRUCTURES SECURITY (CRITIS 2018)

Abstract
Denial of Service attacks, which have become commonplace on the Information and Communications Technologies domain, constitute a class of threats whose main objective is to degrade or disable a service or functionality on a target. The increasing reliance of Cyber-Physical Systems upon these technologies, together with their progressive interconnection with other infrastructure and/or organizational domains, has contributed to increase their exposure to these attacks, with potentially catastrophic consequences. Despite the potential impact of such attacks, the lack of generality regarding the related works in the attack prevention and detection fields has prevented its application in real-world scenarios. This paper aims at reducing that effect by analyzing the behavior of classification algorithms with different dataset characteristics. © 2019, Springer Nature Switzerland AG.

CloseRead Abstract

2019

Generating Synthetic Missing Data: A Review by Missing Mechanism

Authors
Santos, MS; Pereira, RC; Costa, AF; Soares, JP; Santos, JAM; Abreu, PH;

Publication
IEEE Access

Abstract

2019

Cyber-security Modbus ICS dataset

Authors
Frazão, I; Abreu, PH; Cruz, T; Araújo, H; Simões, P;

Publication

Abstract

2019

A Data Visualization Approach for Intersection Analysis using AIS Data

Authors
Pereira, RC; Abreu, PH; Polisciuc, E; Machado, P;

Publication
Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019, Volume 3: IVAPP, Prague, Czech Republic, February 25-27, 2019.

Abstract

2019

Analyzing the Footprint of Classifiers in Adversarial Denial of Service Contexts

Authors
Martins, N; Cruz, JM; Cruz, T; Abreu, PH;

Publication
Progress in Artificial Intelligence, 19th EPIA Conference on Artificial Intelligence, EPIA 2019, Vila Real, Portugal, September 3-6, 2019, Proceedings, Part II.

Abstract

2019

Going Back to Basics on Volumetric Segmentation of the Lungs in CT: A Fully Image Processing Based Technique

Authors
Oliveira, AC; Domingues, I; Duarte, H; Santos, J; Abreu, PH;

Publication
PATTERN RECOGNITION AND IMAGE ANALYSIS, IBPRIA 2019, PT II

Abstract
Radiotherapy planning is a crucial task in cancer patients’ management. This task is, however, very time consuming and prone to a high intra and inter subject variance and human errors. In this way, the present line of work aims at developing a tool to help the specialists in this task. The developed tool will consider the delimitation of anatomical regions of interest, since it is crucial to identify the organs at risk and minimize the exposure of these organs to the radiation. This paper, in particular, presents a lung segmentation algorithm, based on image processing techniques, such as intensity projection and region growing, for Computed Tomography volumes. Our pipeline consists in first separating two halves of the volume to isolate each lung. Then, three techniques for seed placement are developed. Finally, a traditional region growing algorithm has been changed in order to automatically derive the value of the threshold parameter. The results obtained for the three different techniques for seed placement were, respectively, 74%, 74% and 92% of DICE with the Iterative Region Growing algorithm. Although the presented results have as use case the Hodgkin Lymphoma, we believe that the developed method is generalizable to any other pathology. © 2019, Springer Nature Switzerland AG.

CloseRead Abstract