Using Fuzzy Logic Algorithms and Growing Hierarchical Self-Organizing Maps to Define Efficient Security Inspection Strategies in a Container Terminal

Maritime transport is one of the oldest methods of moving various types of goods, and it continues to have an important role in our modern society. More than 20 million containers are transported across the oceans daily. However, this form of transportation is constantly threatened by illegal operations, such as the smuggling of goods or people and merchandise theft. Port security departments must be prepared to face the different threats and challenges that accompany the use of innovative techniques and devices to achieve efficient inspection strategies. Two inspection strategies are presented in this study. The first strategy is based on fuzzy logic (FL), and the second strategy is based on the growing hierarchical self-organizing map (GHSOM) approach. The weight variation and security index (SI) of a container and the readings from certain technologies, such as radio-frequency identification (RFID) and X-ray scanning, are considered as the input data. To minimize the inspection time and considering the costs associated with the security inspections of containers, the results of both inspection strategies are compared and analyzed. The findings indicate there is potential for improving the effectiveness of security inspections by employing both techniques, and the specific relevance in the case of GHSOMs is discussed.Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad - “Estrategias de diseño microelectronico para IOT en escenarios hostiles” TEC2016-80396-C2-2-

A systematic survey of online data mining technology intended for law enforcement

As an increasing amount of crime takes on a digital aspect, law enforcement bodies must tackle an online environment generating huge volumes of data. With manual inspections becoming increasingly infeasible, law enforcement bodies are optimising online investigations through data-mining technologies. Such technologies must be well designed and rigorously grounded, yet no survey of the online data-mining literature exists which examines their techniques, applications and rigour. This article remedies this gap through a systematic mapping study describing online data-mining literature which visibly targets law enforcement applications, using evidence-based practices in survey making to produce a replicable analysis which can be methodologically examined for deficiencies

Addressing the new generation of spam (Spam 2.0) through Web usage models

New Internet collaborative media introduce new ways of communicating that are not immune to abuse. A fake eye-catching profile in social networking websites, a promotional review, a response to a thread in online forums with unsolicited content or a manipulated Wiki page, are examples of new the generation of spam on the web, referred to as Web 2.0 Spam or Spam 2.0. Spam 2.0 is defined as the propagation of unsolicited, anonymous, mass content to infiltrate legitimate Web 2.0 applications.The current literature does not address Spam 2.0 in depth and the outcome of efforts to date are inadequate. The aim of this research is to formalise a definition for Spam 2.0 and provide Spam 2.0 filtering solutions. Early-detection, extendibility, robustness and adaptability are key factors in the design of the proposed method.This dissertation provides a comprehensive survey of the state-of-the-art web spam and Spam 2.0 filtering methods to highlight the unresolved issues and open problems, while at the same time effectively capturing the knowledge in the domain of spam filtering.This dissertation proposes three solutions in the area of Spam 2.0 filtering including: (1) characterising and profiling Spam 2.0, (2) Early-Detection based Spam 2.0 Filtering (EDSF) approach, and (3) On-the-Fly Spam 2.0 Filtering (OFSF) approach. All the proposed solutions are tested against real-world datasets and their performance is compared with that of existing Spam 2.0 filtering methods.This work has coined the term ‘Spam 2.0’, provided insight into the nature of Spam 2.0, and proposed filtering mechanisms to address this new and rapidly evolving problem