De-perimeterisation as a cycle: tearing down and rebuilding security perimeters

If an organisation wants to secure its IT assets, where should the security mechanisms be placed? The traditional view is the hard-shell model, where an organisation secures all its assets using a fixed security border: What is inside the security perimeter is more or less trusted, what is outside is not. Due to changes in technologies, business processes and their legal environments this approach is not adequate anymore.\ud This paper examines this process, which was coined de-perimeterisation by the Jericho Forum.\ud In this paper we analyse and define the concepts of perimeter and de-perimeterisation, and show that there is a long term trend in which de-perimeterisation is iteratively accelerated and decelerated. In times of accelerated de-perimeterisation, technical and organisational changes take place by which connectivity between organisations and their environment scales up significantly. In times of deceleration, technical and organisational security measures are taken to decrease the security risks that come with de-perimeterisation, a movement that we call re-perimeterisation. We identify the technical and organisational mechanisms that facilitate de-perimeterisation and re-perimeterisation, and discuss the forces that cause organisations to alternate between these two movements

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Efficient intrusion detection scheme based on SVM

The network intrusion detection problem is the focus of current academic research. In this paper, we propose to use Support Vector Machine (SVM) model to identify and detect the network intrusion problem, and simultaneously introduce a new optimization search method, referred to as Improved Harmony Search (IHS) algorithm, to determine the parameters of the SVM model for better classification accuracy. Taking the general mechanism network system of a growing city in China between 2006 and 2012 as the sample, this study divides the mechanism into normal network system and crisis network system according to the harm extent of network intrusion. We consider a crisis network system coupled with two to three normal network systems as paired samples. Experimental results show that SVMs based on IHS have a high prediction accuracy which can perform prediction and classification of network intrusion detection and assist in guarding against network intrusion

A model and framework for online security benchmarking

The variety of threats and vulnerabilities within the online business environment are dynamic and thus constantly changing in how they impinge upon online functionality, compromise organizational or customer information, contravene security implementations and thereby undermine online customer confidence. To nullify such threats, online security management must become proactive, by reviewing and continuously improving online security to strengthen the enterpriseis online security measures and policies, as modelled. The benchmarking process utilises a proposed benchmarking framework to guide both the development and application of security benchmarks created in the first instance, from recognized information technology (IT) and information security standards (ISS) and then their application to the online security measures and policies utilized within online business. Furthermore, the benchmarking framework incorporates a continuous improvement review process to address the relevance of benchmark development over time and the changes in threat focus.<br /

Reinforcement learning for efficient network penetration testing

Penetration testing (also known as pentesting or PT) is a common practice for actively assessing the defenses of a computer network by planning and executing all possible attacks to discover and exploit existing vulnerabilities. Current penetration testing methods are increasingly becoming non-standard, composite and resource-consuming despite the use of evolving tools. In this paper, we propose and evaluate an AI-based pentesting system which makes use of machine learning techniques, namely reinforcement learning (RL) to learn and reproduce average and complex pentesting activities. The proposed system is named Intelligent Automated Penetration Testing System (IAPTS) consisting of a module that integrates with industrial PT frameworks to enable them to capture information, learn from experience, and reproduce tests in future similar testing cases. IAPTS aims to save human resources while producing much-enhanced results in terms of time consumption, reliability and frequency of testing. IAPTS takes the approach of modeling PT environments and tasks as a partially observed Markov decision process (POMDP) problem which is solved by POMDP-solver. Although the scope of this paper is limited to network infrastructures PT planning and not the entire practice, the obtained results support the hypothesis that RL can enhance PT beyond the capabilities of any human PT expert in terms of time consumed, covered attacking vectors, accuracy and reliability of the outputs. In addition, this work tackles the complex problem of expertise capturing and re-use by allowing the IAPTS learning module to store and re-use PT policies in the same way that a human PT expert would learn but in a more efficient way

Smart Grid Technologies in Europe: An Overview

The old electricity network infrastructure has proven to be inadequate, with respect to modern challenges such as alternative energy sources, electricity demand and energy saving policies. Moreover, Information and Communication Technologies (ICT) seem to have reached an adequate level of reliability and flexibility in order to support a new concept of electricity network—the smart grid. In this work, we will analyse the state-of-the-art of smart grids, in their technical, management, security, and optimization aspects. We will also provide a brief overview of the regulatory aspects involved in the development of a smart grid, mainly from the viewpoint of the European Unio