Classifying And Predicting Software Security Vulnerabilities based on Reproducibility

Security defects are common in large software systems because of their size and complexity. Although efficient development processes, testing, and maintenance policies are applied to software systems, there are still a large number of vulnerabilities that can remain, despite these measures. Some vulnerabilities stay in a system from one release to the next one because they cannot be easily reproduced through testing. These vulnerabilities endanger the security of the systems. We propose vulnerability classification and prediction frameworks based on vulnerability reproducibility. The frameworks are effective to identify the types and locations of vulnerabilities in the earlier stage, and improve the security of software in the next versions (referred to as releases). We expand an existing concept of software bug classification to vulnerability classification (easily reproducible and hard to reproduce) to develop a classification framework for differentiating between these vulnerabilities based on code fixes and textual reports. We then investigate the potential correlations between the vulnerability categories and the classical software metrics and some other runtime environmental factors of reproducibility to develop a vulnerability prediction framework. The classification and prediction frameworks help developers adopt corresponding mitigation or elimination actions and develop appropriate test cases. Also, the vulnerability prediction framework is of great help for security experts focus their effort on the top-ranked vulnerability-prone files. As a result, the frameworks decrease the number of attacks that exploit security vulnerabilities in the next versions of the software. To build the classification and prediction frameworks, different machine learning techniques (C4.5 Decision Tree, Random Forest, Logistic Regression, and Naive Bayes) are employed. The effectiveness of the proposed frameworks is assessed based on collected software security defects of Mozilla Firefox.

Registro de pacientes con distrofinopatías en Colombia

INTRODUCCIÓN. La distrofia muscular de Duchenne es una enfermedad neuromuscular con una herencia recesiva ligada al X que afecta a 1 de cada 3500 niños nacidos vivos. Se produce por mutaciones en el gen DMD que codifica para la distrofina. Se caracteriza por manifestaciones clínicas variables típicas de una distrofia muscular proximal progresiva. OBJETIVO. Realizar el primer registro en Colombia de los pacientes identificados con distrofinopatías, teniendo en cuenta características clínicas y paraclínicas, así como las mutaciones causales de esta patología. METODOLOGÍA Es un estudio descriptivo, transversal, de la revisión de historias clínicas de los pacientes con diagnóstico de DMD atendidos en la consulta de Genética de la Universidad del Rosario durante los años 2006 a 2015. RESULTADOS Se identificaron 99 pacientes, de los cuales 56 (56,56%) corresponden al fenotipo Duchenne y 12 (12,12%) al Becker. No fue posible clasificar a 31 pacientes (31,3%) por falta de datos clínicos. La edad de inicio de los síntomas fue en promedio de 4,41 años. Las mutaciones más frecuentes fueron las deleciones (69%), seguidas por las mutaciones puntuales(14%), las duplicaciones (11%) y por otras mutaciones (4%). CONCLUSIONES Este registro de distrofinopatías es el primero reportado en Colombia y el punto de partida para conocer la incidencia de la enfermedad, caracterización clínica y molecular de los pacientes, garantizando así el acceso oportuno a los nuevos tratamientos de medicina de precisión que permitan mejorar la calidad de vida de los pacientes y sus familias.

Tratamento de sementes para manejo do percevejo-barriga-verde na cultura de soja e milho em sucessão.

RESUMO: O objetivo deste trabalho foi avaliar o efeito do tratamento de sementes com inseticidas sobre o manejo de Dichelops melacanthus e a produtividade da soja e do milho, cultivados em sucessão. O estudo foi realizado em campo, nas safras 2012/2013 (I) e 2013/2014 (II). Avaliaram-se os inseticidas imidacloprido, tiametoxam, tiodicarbe, fipronil e abamectina. Determinaram-se: a densidade populacional do percevejo, a produtividade de soja e milho, e a intensidade da injúria em milho. A densidade do percevejo permaneceu abaixo de um inseto por metro quadrado, na maior parte do ciclo da soja. Os picos populacionais foram observados nas primeiras semanas, após a emergência do milho, e atingiram 2,2 (safra I) e 6,7 (safra II) percevejos por metro quadrado. Na cultura da soja, os inseticidas não reduziram a densidade populacional do percevejo. Na cultura do milho, o imidacloprido reduziu a densidade do percevejo em 23,2% (safra I) e 38,8% (safra II), e a injúria em 61,8% (safra I) e 26,4% (safra II). O tiametoxam reduziu a densidade dos insetos em 27,8% (safra II) e a injúria em 42,7% (safra I). O tratamento de sementes com inseticidas não proporciona aumento de produtividade à soja e ao milho, portanto, não se justifica sua utilização nas condições deste estudo. ABSTRACT: The objective of this work was to evaluate the effect of seed treatment with insecticides on the management of Dichelops melacanthus on the yield of soybean and corn, grown in succession. The study was carried out in a field, in the 2012/2013 (I) and 2013/2014 (II) crop seasons. The evaluated insecticides were: imidacloprid, thiamethoxam, thiodicarb, fipronil, and abamectin. The following were determined: stink bug population density, soybean and corn yield, and corn injury. Population density remained below one stink bug per square meter, in most of the soybean cycle. Population peaks were observed in the first weeks, after corn emergence, and they reached 2.2 (crop season I) and 6.7 (crop season II) stink bugs per square meter. In the soybean crop, the insecticides did not reduce the stink bug population density. In the corn crop, imidacloprid reduced the stink bug density in 23.2% (crop season I) and 38.8% (crop season II), and injury in 61.8% (crop season I) and 26.4% (crop season II). Thiamethoxam reduced the insect population density in 27.8% (crop season II) and injury in 42.7% (crop season I). Seed treatment with insecticides does not provide increase for soybean and corn yields, therefore, their use is not justified in this study's conditions.