This paper presents an approach for retrofitting existing Web applications with run-time protection against known, as well as unseen, SQL injection attacks (SQLIAs) without the involvement of application developers. The precision of the approach is also enhanced with a method for reducing the rate of false positives in the SQLIA detection logic, via runtime discovery of the developers’ intentio...

Mapping potential archaeological sites using remote sensing and artificial intelligence can be an efficient tool to assist archaeologists during project planning fieldwork. This paper explores the use of airborne LiDAR data data-centric for identifying burial mounds. The challenge exploring landscape mapping new sites, coupled with difficulty them through visual analysis data, results in recurr...

Introduction/Background Currently, the diagnosis of borderline ovarian tumors (BOT) by ultrasound is a challenge. Our study proposes how to differentiate between true positives (TP) and false (FP) in BOT Methodology A retrospective patients who underwent transvaginal with adnexal mass subsequent surgery 2012 2022 at tertiary referral university hospital gynaecological oncology...

We have developed GFScan(Gene Family Scan), a tool that identifies members of a gene family by searching genomic DNA sequences with genomic DNA motifs (or matrices) that are representative of the family. We have tested GFScan on four human gene families including the neurotransmitter-gated ion-channels (NGIC) family, the carbonic anhydrases (CA) family, the Dbl homology (DH) domain family, and ...

Network anomaly detection has been a hot topic in the past years. However, high false alarm rate, difficulties in obtaining exact clean data for the modeling of normal patterns and the deterioration of detection rate because of “unclean” training set always make it not as good as we expect. Therefore, we propose a novel data mining method for network anomaly detection in this paper. Experimenta...

Whole-exome sequencing (WES) can identify causative mutations in hereditary diseases. However, WES data might have a large candidate variant list, including false positives. Moreover, in families, it is more difficult to select disease-associated variants because many variants are shared among members. To reduce false positives and extract accurate candidates, we used a multilocus variant inste...

A new approach for fMRI group data analysis is introduced to overcome the limitations of standard voxel-based testing methods, such as Statistical Parametric Mapping (SPM). Using a Bayesian model selection framework, the functional network associated with a certain cognitive task is selected according to the posterior probabilities of mean region activations, given a pre-defined anatomical parc...

It is well known that security prevention mechanisms are not sufficient to protect efficiently an information system. Intrusion detection systems are required. But these systems present many imperfections. In particular, they can either generate false positives (i.e., alarms that should not be produced) or miss attacks (false negatives). However, the main problem is the generation of false posi...