Nowadays, web applications are popular targets for security attackers. Using specific security mechanisms, we can prevent or detect a security attack on a web application, but we cannot find out the criminal who has carried out the security attack. Being unable to trace back an attack, encourages hackers to launch new attacks on the same system. Web application forensics aims to trace back and attribute a web application security attack to its originator. This may significantly reduce the security attacks targeting a web application every day, and hence improve its security. The aim of this paper is to carry out a detailed overview about the web application forensics. First, we define the web applications forensics, and we present a taxonomic structure of the digital forensics. Then, we present the methodology of a web application forensics investigation. After that, we illustrate the forensics supportive tools for a web application forensics investigation. After that, we present a detailed presentation of a set of the main considered web application forensics tools. Finally, we provide a comparison of the main considered web application forensics tools.

Voice over IP (VoIP) is the technology allowing voice traffic transmission as data packets over a private or a public IP network. VoIP allows significant benefits for customers and communication services providers. The main are cost savings, rich media service, phone and service portability and mobility, and the integration with other applications. Nevertheless, the deployment of the VoIP technology encounters many challenges such as architecture complexity, interoperability problems, QoS concerns, and security issues. Due to the inability of the IP networking technology to support the stringent QoS constraints of voice traffic, and the incapability of traditional security mechanisms to adequately protect VoIP systems from recent intelligent attacks, QoS and security issues are considered as the most serious challenges for successful deployment of the VoIP technology. The aim of this paper is to carry out a deep analysis of the security issues and QoS concerns of the VoIP technology. Firstly, we present a brief overview about the VoIP technology. Then, we discuss the QoS problems encountering the deployment of the VoIP technology. The presented discussion mainly address the QoS issues related to the use of the IP networking technology, the QoS concerns related to voice clarity, and the QoS mechanisms proposed to support voice traffic QoS constraints. After that, we investigate the security issues of the VoIP technology. The presented investigation mainly address the vulnerabilities and security attacks of VoIP systems, as well as the countermeasures that should be considered to help the deployment of secured VoIP systems.

The process of data mining produces various patterns from a given data source. The most recognized data mining tasks are the process of discovering frequent itemsets, frequent sequential patterns, frequent sequential rules and frequent association rules. Numerous efficient algorithms have been proposed to do the above processes. Frequent pattern mining has been a focused topic in data mining research with a good number of references in literature and for that reason an important progress has been made, varying from performant algorithms for frequent itemset mining in transaction databases to complex algorithms, such as sequential pattern mining, structured pattern mining, correlation mining. Association Rule mining (ARM) is one of the utmost current data mining techniques designed to group objects together from large databases aiming to extract the interesting correlation and relation among huge amount of data. In this article, we provide a brief review and analysis of the current status of frequent pattern mining and discuss some promising research directions. Additionally, this paper includes a comparative study between the performance of the described approaches.