CRIMINALISTIC CLASSIFICATION OF HARMFUL SOFTWARE

Software understanding: Automatic classification of software identifiers

Identifier names (e.g., packages, classes, methods, variables) are one of most important software comprehension sources. Identifier names need to be analyzed in order to support collaborative software engineering and to reuse source codes. Indeed, they convey domain concept of softwares. For instance, “getMinimumSupport” would be associated with association rule concept in data mining softwares...

Extreme Programming Considered Harmful for Reliable Software Development 2 . 0

Negative Training Data Can be Harmful to Text Classification

This paper studies the effects of training data on binary text classification and postulates that negative training data is not needed and may even be harmful for the task. Traditional binary classification involves building a classifier using labeled positive and negative training examples. The classifier is then applied to classify test instances into positive and negative classes. A fundamen...

2-Way Text Classification for Harmful Web Documents

The openness of the Web allows any user to access almost any type of information. However, some information, such as adult content, is not appropriate for all users, notably children. Additionally for adults, some contents included in abnormal porn sites can do ordinary people’s mental health harm. In this paper, we propose an efficient 2-way text filter for blocking harmful web documents and a...

Unified Criminalistic Information System for Investigation of Crimes and Violations of Law

The main objective in storing criminalistic records has always been to assist the smooth running of the criminal justice system. In other words the main objective of criminalistic databases and collections is provide with information the investigation of crimes and other violations of law. The research considers the use of criminalistic databases and other records within criminal justice system...