Abstract
The information generated by a network monitoring system is overwhelming. Monitoring is imperative but very difficult to accomplish due to several reasons. More so for the case of non tech-savvy home users. Security Information Event Management applications generate alarms that correlate multiple occurrences on the network. These events are classified accordingly to their risk. An application that allows the sonification of events generated by a Security Information Event Management can facilitate the security monitoring of a home network by a less tech-savvy user by allowing him to just listen to the result of the sonification of such events.

Abstract
The increase in usage of smartphones and the ubiquity of Internet access have made mobile communications services very attractive to users. Messaging services are among the most popular services on the Internet. In recent years, this services started to support confidentiality and anonymity. A recurrent problem with the existing messaging solutions is their lack of resistance to impersonation attacks. The proposed solution addresses the impersonation problem, without neglecting user confidentiality and anonymity, by forcing users to exchange the required cryptographic material among themselves. Moreover, this exchange must use a proximity communication technology, forcing the users to physically meet.

Abstract
Road condition has an important role in our daily live. Anomalies in road surface can cause accidents, mechanical failure, stress and discomfort in drivers and passengers. Governments spend millions each year in roads maintenance for maintaining roads in good condition. But extensive maintenance work can lead to traffic jams, causing frustration in road users. In way to avoid problems caused by road anomalies, we propose a system that can detect road anomalies using smartphone sensors. The approach is based in data-mining algorithms to mitigate the problem of hardware diversity. In this work we used scikit-learn, a python module, and Weka, as tools for data-mining. All cleaning data process was made using python language. The fmal results show that it is possible detect road anomalies using only a smartphone. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
This paper presents a new technique for providing the analysis and comparison of wiretap codes in the small blocklength regime over the binary erasure wiretap channel. A major result is the development of Monte Carlo strategies for quantifying a code's equivocation, which mirrors techniques used to analyze forward error correcting codes. For this paper, we limit our analysis to coset-based wiretap codes, and give preferred strategies for calculating and/or estimating the equivocation in order of preference. We also make several comparisons of different code families. Our results indicate that there are security advantages to using algebraic codes for applications that require small to medium blocklengths. © 2017 IEEE.

Abstract
The collection and analysis of data are continuously growing due to the pervasiveness of computing devices. The analysis of such information is fostering businesses and contributing beneficially to the society in many different fields. However, this storage and flow of possibly sensitive data poses serious privacy concerns. Methods that allow the knowledge extraction from data, while preserving privacy, are known as privacy-preserving data mining (PPDM) techniques. This paper surveys the most relevant PPDM techniques from the literature and the metrics used to evaluate such techniques and presents typical applications of PPDM methods in relevant fields. Furthermore, the current challenges and open issues in PPDM are discussed. © 2017 IEEE.

Abstract
This paper presents a new technique for providing the analysis and comparison of wiretap codes in the small blocklength regime over the binary erasure wiretap channel. A major result is the development of Monte Carlo strategies for quantifying a code's equivocation, which mirrors techniques used to analyze forward error correcting codes. For this paper, we limit our analysis to coset-based wiretap codes, and give preferred strategies for calculating and/or estimating the equivocation in order of preference. We also make several comparisons of different code families. Our results indicate that there are security advantages to using algebraic codes for applications that require small to medium blocklengths.