Privacy Preserving Data Mining, Evaluation Methodologies

Privacy is one of the most important properties an information system must satisfy. A relatively new trend shows that classical access control techniques are not sufficient to guarantee privacy when datamining techniques are used. Privacy Preserving Data Mining (PPDM) algorithms have been recently introduced with the aim of modifying the database in such a way to prevent the discovery of sensible information. Due to the large amount of possible techniques that can be used to achieve this goal, it is necessary to provide some standard evaluation metrics to determine the best algorithms for a specific application or context. Currently, however, there is no common set of parameters that can be used for this purpose. Moreover, because sanitization modifies the data, an important issue, especially for critical data, is to preserve the quality of data. However, to the best of our knowledge, no approaches have been developed dealing with the issue of data quality in the context of PPDM algorithms. This report explores the problem of PPDM algorithm evaluation, starting from the key goal of preserving of data quality. To achieve such goal, we propose a formal definition of data quality specifically tailored for use in the context of PPDM algorithms, a set of evaluation parameters and an evaluation algorithm. Moreover, because of the "environment related" nature of data quality, a structure to represent constraints and information relevance related to data is presented. The resulting evaluation core process is then presented as a part of a more general three step evaluation framework, taking also into account other aspects of the algorithm evaluation such as efficiency, scalability and level of privacy.JRC.G.6-Sensors, radar technologies and cybersecurit

State of the Art in Privacy Preserving Data Mining

Privacy is one of the most important properties an information system must satisfy. A relatively new trend shows that classical access control techniques are not sufficient to guarantee privacy when Data Mining techniques are used. Such a trend, especially in the context of public databases, or in the context of sensible information related to critical infrastructures, represents, nowadays a not negligible thread. Privacy Preserving Data Mining (PPDM) algorithms have been recently introduced with the aim of modifying the database in such a way to prevent the discovery of sensible information. This is a very complex task and there exist in the scientific literature some different approaches to the problem. In this work we present a "Survey" of the current PPDM methodologies which seem promising for the future.JRC.G.6-Sensors, radar technologies and cybersecurit

Privacy Preserving Data Mining, A Data Quality Approach

Privacy is one of the most important properties an information system must satisfy. A relatively new trend shows that classical access control techniques are not sufficient to guarantee privacy when datamining techniques are used. Privacy Preserving Data Mining (PPDM) algorithms have been recently introduced with the aim of sanitizing the database in such a way to prevent the discovery of sensible information (e.g. association rules). A drawback of such algorithms is that the introduced sanitization may disrupt the quality of data itself. In this report we introduce a new methodology and algorithms for performing useful PPDM operations, while preserving the data quality of the underlying database.JRC.G.6-Sensors, radar technologies and cybersecurit

ICT aspects of power systems and their security

This report provides a deep description of four complex Attack Scenarios that have as final goal to produce damage to the Electric Power Transmission System. The details about protocols used, vulnerabilities, devices etc. have been for obvious reasons hidden, and the ones presented have to be understood as mere (even if realistic) simplified versions of possible power systems.JRC.DG.G.6-Security technology assessmen

Malware Templates for MAlSim

This report describes the methodology of malware templates for MAlSim - Mobile Agent Malware Simulator, a mobile agent framework which aims at simulation of diverse malicious software in computer network of an arbitrary information system. Malware template is a pattern (a 'guide') for implementation of MAlSim agent aiming at simulation of a concrete malware. It indicates the selection and configuration of Java classes (MAlSim agent, one or more behavioural patterns and one or more migration/replication patterns) selected from MAlSim Toolkit.JRC.G.6-Sensors, radar technologies and cybersecurit

Food Neophobia or Distrust of Novelties? Exploring consumers' attitudes toward GMOs, insects and cultured meat

The food industry is constantly challenged to find new ideas to satisfy the increasingly specific consumer demand. However, innovative food products do not always become part of consumption habits or create a market. One of the major sources of resistance to novelty lies in the attitude of the consumer, who in many cases may be suspicious or hostile as a result of specific ideologies, overly attached to tradition, or affected by neophobia. This paper analyzes the construct of food neophobia (the "unwillingness to try new foods") in its phenomenology and its actual power to explain hostility to innovation in the agri-food sector. The limits of the concept, which is not always sufficient to shed light on the many reasons that could underlie the rejection of certain foods, will also be discussed. In addition, we review the recent literature on Europeans' attitude toward novel foods and innovation including Genetically modified organisms (GMOs), cultivated meat and insects as food. This literature reveals a number of paradoxes in consumers' behavior, and in the many complex conditions underpinning the success of innovation in food production. These conditions can only be understood by reconstructing the meanings consumers assign to food, and are often embedded in larger social and political frameworks

MAlSim Deployment

This report describes the deployment issues related to MAlSim - Mobile Agent Malware Simulator - a mobile agent framework which aims at simulation of malware - malicious software that run on a computer and make the system behaving in a way wanted by an attacker. MAlSim was introduced in our previous report where we described its composition and functions, and provided the details of the simulation environment in which MAlSim is deployed and the auxiliary parts which support the experiments performed with MAlSim. In this report we are providing more technical details related to the installation and use of the framework.JRC.G.6-Sensors, radar technologies and cybersecurit

A model of distributed key generation for industrial control systems

11th International Workshop on Discrete Event Systems, WODES 2012; Guadalajara, Jalisco; Mexico; 3 October 2012 through 5 October 2012The cyber-security of industrial control systems (ICS) is gaining high relevance due to the impact of industrial system failures on the citizen life. There is an urgent need for the consideration of security in their design, and for the analysis of the related vulnerabilities and potential threats. The high exposure of industrial critical infrastructure to cyber-threats is mainly due to the intrinsic weakness of the communication protocols used to control the process network. The peculiarities of the industrial protocols (low computational power, large geographical distribution, near to real-time constraints) make hard the effective use of traditional cryptographic schemes and in particular the implementation of an effective key management infrastructure supporting a cryptographic layer. In this paper, we describe a "model of distributed key generation for industrial control systems" we have recently implemented. The model is based on a known Distributed Key Generator protocol we have adapted to an industrial control system environment and to the related communication protocol (Modbus). To validate in a formal way selected security properties of the model, we introduced a Petri Nets representation. This representation allows for modeling attacks against the protocol and understanding some potential weaknesses of its implementation in the industrial control system environment

Stealthy Deception Attacks Against SCADA Systems

SCADA protocols for Industrial Control Systems (ICS) are vulnerable to network attacks such as session hijacking. Hence, research focuses on network anomaly detection based on meta--data (message sizes, timing, command sequence), or on the state values of the physical process. In this work we present a class of semantic network-based attacks against SCADA systems that are undetectable by the above mentioned anomaly detection. After hijacking the communication channels between the Human Machine Interface (HMI) and Programmable Logic Controllers (PLCs), our attacks cause the HMI to present a fake view of the industrial process, deceiving the human operator into taking manual actions. Our most advanced attack also manipulates the messages generated by the operator's actions, reversing their semantic meaning while causing the HMI to present a view that is consistent with the attempted human actions. The attacks are totaly stealthy because the message sizes and timing, the command sequences, and the data values of the ICS's state all remain legitimate. We implemented and tested several attack scenarios in the test lab of our local electric company, against a real HMI and real PLCs, separated by a commercial-grade firewall. We developed a real-time security assessment tool, that can simultaneously manipulate the communication to multiple PLCs and cause the HMI to display a coherent system--wide fake view. Our tool is configured with message-manipulating rules written in an ICS Attack Markup Language (IAML) we designed, which may be of independent interest. Our semantic attacks all successfully fooled the operator and brought the system to states of blackout and possible equipment damage

Edukoi: developing an interactive sonification tool for astronomy between entertainment and education

Edukoi is a software that aims to make interactive sonification suitable to convey and extract information. The program design is a modification of the software Herakoi, which sonifies images in real time mapping pitch to colour using a motion-aware approach for allowing users to interact with images through sound. The pitch-colour association of Hearkoi, albeit pleasing from the entertainment side, is not efficient for communicating specific information regarding colours and hues to listeners. Hence we modified it to create an instrument to be used by visually impaired and sighted children to explore images through sound and extract accurate information. We aim at building a flexible software that can be used in middle-schools for both art and science teaching. We tested its effectiveness using astronomical images, given the great fascination that astronomy always has on kids of all ages and backgrounds. Astronomy is also considered a very visual science, a characteristic that prevents students from learning this subject and having a related career. With this project we aim to challenge this belief and give to students the possibility to explore astronomical data through sound. Here we discuss our experiment, the choices we made regarding sound mappings, and what psychophysiological aspects we aim to evaluate to validate and improve Edukoi.Comment: 4 pages, 3 figures, to be published in the proceedings of "The 28th International Conference on Auditory Display (ICAD 2023) - Special Session on Astronomical Data Sonification