Industrial Demilitarized Zone and Zero Trust cybersecurity models for Industrial Control Systems

Today more than ever, with the recent war in Ukraine and the increasing number of attacks that affect systems of nations and companies every day, the world realizes that cybersecurity can no longer be considered just as a ���cost���. It must become a pillar for our infrastructures that involve the security of our nations and the safety of people. Critical infrastructure, like energy, financial services, and healthcare, have become targets of many cyberattacks from several criminal groups, with an increasing number of resources and competencies, putting at risk the security and safety of companies and entire nations. This thesis aims to investigate the state-of-the-art regarding the best practice for securing Industrial control systems. We study the differences between two security frameworks. The first is Industrial Demilitarized Zone (I-DMZ), a perimeter-based security solution. The second one is the Zero Trust Architecture (ZTA) which removes the concept of perimeter to offer an entirely new approach to cybersecurity based on the slogan ���Never Trust, always verify���. Starting from this premise, the Zero Trust model embeds strict Authentication, Authorization, and monitoring controls for any access to any resource. We have defined two architectures according to the State-of-the-art and the cybersecurity experts��� guidelines to compare I-DMZ, and Zero Trust approaches to ICS security. The goal is to demonstrate how a Zero Trust approach dramatically reduces the possibility of an attacker penetrating the network or moving laterally to compromise the entire infrastructure. A third architecture has been defined based on Cloud and fog/edge computing technology. It shows how Cloud solutions can improve the security and reliability of infrastructure and production processes that can benefit from a range of new functionalities, that the Cloud could offer as-a-Service.We have implemented and tested our Zero Trust solution and its ability to block intrusion or attempted attacks.

Graphical simulators for AUV development

A long development time is needed from the design to the implementation of an AUV. During the first steps, simulation plays an important role, since it allows for the development of preliminary versions of the control system to be integrated. Once the robot is ready, the control systems are implemented, tuned and tested. The use of a real-time simulator can help closing the gap between off-line simulation and real testing using the already implemented robot. When properly interfaced with the robot hardware, a real-time graphical simulation with a "hardware in the loop" configuration, can allow for the testing of the implemented control system running in the actual robot hardware. Hence, the development time is drastically reduced. These paper overviews the field of graphical simulators used for AUV development proposing a classification. It also presents NEPTUNE, a multi-vehicle, real-time, graphical simulator based on OpenGL that allows hardware in the loop simulations

Modelling the Human Values Scale from Consumers Transactional Data Bases

The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the data base used by the recommender systems, and which allow to resolve the specific problems of prediction and recommendation. In this work, we propose to extract the user's human values scale from the data base of the users, to improve their suitability in open environments, such as the recommender systems. For this purpose, the methodology is applied with the data of the user after interacting with the system. The methodology is exemplified with a case study

Embedding objects into Matlab/Simulink for process supervision

This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools

Learning and adaptation in physical heterogeneous teams of robots

In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent���s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems

��lykk��iden ohjausj��rjestelmien k��ytt�� puutavarakuormaimen v��symiskestoi��n parantamisessa

Ty��n tavoitteena oli tutkia ��lykk��iden ohjausj��rjestelmien k��ytt���� mekatronisen koneen v��symiskeston parantamisessa. ��lykk��iden j��rjestelmien osalta ty��ss�� keskityttiin l��hinn�� neuroverkkojen ja sumean logiikan mahdollisuuksien tutkimiseen. T��m��n lis��ksi ty��ss�� kehitettiin v��symiskestoik���� lis����v�� ��lykk��isiin j��rjestelmiin perustuva ohjausalgoritmi. Ohjausalgoritmi liitettiin osaksi puutavarakuormaimen ohjausta. Ohjaimen kehittely suoritettiin aluksi simulointimallien avulla. Laajemmat ohjaimen testaukset suoritettiin laboratoriossa fyysisen prototyypin avulla. Tuloksena puutavarakuormaimen puomin v��symiskestoik��ennuste saatiin moninkertaistettua. V��symiskestoi��n parantumisen lis��ksi ohjainalgoritmi my��s vaimentaa kuormaimen v��r��htely��.

Keskitehoestimaattorin lis����minen diesel-s��hk��iseen hybridij��rjestelm����n

Nykyajan jatkuvasti kiristyv��t p����st��rajoitukset ja ilmastonmuutoksen uhka ovat ajavia voimia kehitt��m����n voimalaitosten tekniikkaa energiatehokkaampaan ja ymp��rist��yst��v��llisemp����n suuntaan. Polttomoottoritekniikan parantaminen on t��rke�� osa t��t�� kehityst��, mutta jo nykyisi�� moottoreita voitaisiin ajaa energiate-hokkaammin k��ytt��m��ll�� akustoa ja ��lyk��st�� s����t��j��rjestelm���� apuna. Ty��ss�� tutkitaan simulaatioiden avulla voidaanko ulkomerell�� toimivan huolto-aluksen energiatehokkuutta parantaa muokkaamalla sen tehon tuottoa keskitehoes-timaattorin ja akuston avulla.

Learning and adaptation in physical heterogeneous teams of robots

In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent���s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems

Graphical simulators for AUV development

A long development time is needed from the design to the implementation of an AUV. During the first steps, simulation plays an important role, since it allows for the development of preliminary versions of the control system to be integrated. Once the robot is ready, the control systems are implemented, tuned and tested. The use of a real-time simulator can help closing the gap between off-line simulation and real testing using the already implemented robot. When properly interfaced with the robot hardware, a real-time graphical simulation with a "hardware in the loop" configuration, can allow for the testing of the implemented control system running in the actual robot hardware. Hence, the development time is drastically reduced. These paper overviews the field of graphical simulators used for AUV development proposing a classification. It also presents NEPTUNE, a multi-vehicle, real-time, graphical simulator based on OpenGL that allows hardware in the loop simulations

Modelling the Human Values Scale from Consumers Transactional Data Bases

The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the data base used by the recommender systems, and which allow to resolve the specific problems of prediction and recommendation. In this work, we propose to extract the user's human values scale from the data base of the users, to improve their suitability in open environments, such as the recommender systems. For this purpose, the methodology is applied with the data of the user after interacting with the system. The methodology is exemplified with a case study

Embedding objects into Matlab/Simulink for process supervision

This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools

Robust identification for linear-in-the-parameters models

In this paper new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness, including three algorithms using combined A- or D-optimality or PRESS statistic (Predicted REsidual Sum of Squares) with regularised orthogonal least squares algorithm respectively. A common characteristic of these algorithms is that the inherent computation efficiency associated with the orthogonalisation scheme in orthogonal least squares or regularised orthogonal least squares has been extended such that the new algorithms are computationally efficient. A numerical example is included to demonstrate effectiveness of the algorithms. Copyright (C) 2003 IFAC.

Uma contribui����o da aplica����o de modelos fuzzy empregados na detec����o da queima de pe��as na retifica����o plana

P��s-gradua����o em Engenharia Mec��nica - FEB

Sistema inteligente para a predi����o de grupo de risco de evas��o discente

P��s-gradua����o em Engenharia El��trica - FEIS