Security has been a growing concern for large organizations, especially financial and gov- ernmental institutions, as security breaches in the systems they depend have repeatedly resulted in losses of billions per year, and this cost is on the rise. A primary reason for these breaches is the “socio-technical” nature of today’s systems that consist of an amal- gam of social and human actors, processes, technology and infrastructure. We refer to such systems as Socio-Technical Systems (STSs). Finding secure solutions for STSs is a difficult and error-prone task because of their heterogeneity and complexity. The thesis proposes a holistic security requirements analysis framework which catego- rizes system security concerns into three layers, including a social layer (social actors and business processes), a software layer (software applications that support the social layer) and an infrastructure layer (physical infrastructure, hardware, and devices). Within each layer, security requirements are elicited, and security mechanisms are designed to satisfy the security requirements. In particular, a cross-layer support link is defined to capture how security mechanisms deployed at one layer influence security requirements of the next layer down, allowing us to systematically and iteratively analyze security for all three layers and eventually produce holistic security solutions for the systems. To ensure the quality of the analysis of our approach and to promote practical adoption of the three-layer approach, the thesis includes two additional components. Firstly, we propose a holistic attack analysis, which takes an attacker’s perspective to explore realistic attacks that can happen to a system and thus contributes to the identification of critical security requirements. This approach consists of an attack strategy identification method which analyzes attacker’s alternative malicious intentions, and an attack strategy operationalization method which analyzes realistic attack actions that can be performed by attackers. Secondly, the thesis proposes a systematic approach for selecting and applying security patterns, which describe proven security solutions to known security problems. As such, analysts with little security knowledge can efficiently leverage reusable security knowledge to operationalize security requirements in terms of security mechanisms. This approach also allows us to systematically analyze and enforce the impact of deployed security mechanisms on system functional specifications. We have developed a prototype tool, which implements the formalized analysis methods of our three-layer framework and enables the semi-automatic application of our proposal. With the help of the tool, we apply our framework to two large-scale case studies so as to validate the efficacy of our approach.

This thesis positions itself within the stream of research on HCI for sport and addresses the topic of designing wearable devices for sport. To date, the design of wearables for sport has focused on the measurable aspects of performance such as speed, heartbeat and calories burnt. Such design is driven by the possibilities offered by the miniaturisation of components and the trend to have a healthy lifestyle. The conjunction of these two trends, has created a breeding ground for technologies that offer self-tracking to improve personal fitness, health and wellbeing. Although these kinds of devices have great success on the market, several studies have shown poor long-term adoption, with people generally ceasing to use their devices around six months from the time of purchase. This thesis argues that the wearables produced until now do not address the full range of needs that sportspeople have and so aims to design wearables on the basis of a thorough understanding of the sport practice. The leading research question in this work was: what are the elements to consider for the design of useful, acceptable and desirable wearable devices for sport? This broad research question was then operationalised in two sub-questions: what elements constitute the sport practice?; and how can wearable devices support such practice? By adopting a practice perspective and a subsequent research methodology based on situatedness, embodiment, and co-design, it was possible to identify aspects of sport other than performance. Emotions, trust and community values emerged as pivotal aspects of the climbing experience. These findings led to the design of wearables for augmenting the interpersonal communication of the actors involved. This introduces a new role for wearables supporting sportspeople, which as a facilitator of expertise rather than a tracker of activity. The main contribution of this thesis is the articulation of a conceptual framework for the design of wearables for outdoor sports, with the goal of better acceptance and long-term adoption. The conceptual framework outlined here breaks down the complexity of the sport practice by identifying the elements that define it (i.e. type of performance, emotional involvement, social dynamics, physical context, values) and articulating their orchestration with product design aspects (such as ergonomics, comfort, and perceptibility) and the cultural value of wearing an artefact on the body.

Automatic behavior analysis lies at the intersection of different social and technical research domains. The interdisciplinarity of the field, provides researchers with the means to study the manifestations of human constructs, such as personality. A branch of human behavior analyis, the study of personality provides insight into the cognitive and psychological construction of the human being. Research in personality psychology, advances in com- puting power and the development of algorithms, have made it possible to analyze existing data in order to understand how people express their own personality, perceive others’, and what are the variables that influence its manifestation. We are pursuing this line of research because insights into the personality of the user can have an impact on how we interact with technology. Incorporating research on personality recogniton, both from a cognitive as well as an engineering perspective, into computers could facilitate the interactions between humans and machines. Previous attempts on personality recognition have focused on a variety of different corporas (ranging from text to audiovisual data), different scenarios (interviews, meetings), different channels of communication (audio, video, text) and different subsets of personality traits (out of the five ones present in the Big Five Model: Extraversion, Agreeableness, Conscientiousness, Emotional Stability and Creativity). Our work builds on previous research, by considering simple acoustic and visual non-verbal features extracted from multimodal data, but doesn’t fail to bring novelties: we consider previously uninvestigated scenarios, and at the same time, all of the five personality traits and not just a subset.

A framework to increase the level of automation of manufacturing processes towards the paradigm of intelligent manufacturing is proposed. The case study considered is the milling of aluminum alloys through a three-axes Computer Numerical Control (CNC) machine tool. The developed controller is called Evaluation and Perception Controller (EPC), and it con- sists of three layers: sensor, perception, and cognitive. A set of sensors displayed in the working volume collect the information necessary to reconstruct the state of the system. In the perception layer the acquired data are processed and learned, thus maintaining updated the models of the process which drive the process optimisation in the cognitive layer. The Optimal Control Problem (OCP) method is utilised to calculate the controls of the process that optimise a target function, defined accordingly to the specific context in which the operation is executed (namely roughing or finishing). In the general case, the objec- tive function takes into account: productivity, quality, and costs of the process. The material removal rate along the tool path is used as index for process productivity. The quality is quan- tified through measurements of roughness, therefore it is improved by limiting the static and dynamic displacements (i.e. the vibrations) of the tool. The costs of the process here con- sidered are those associated to tooling (i.e. wear of the tool), and energy absorbed by the spindle during on-air free movements. In order to ensure the feasibility of the solution, algebraic and differential constraints are im- posed on the dynamic response of drives and spindle. The OCP is then solved through an efficient optimisation library developed by the group of Mechatronic Engineering of the Uni- versity of Trento. The EPC has been designed as a portable system that can be integrated into any CNC ma- chine, once it has been calibrated, and a dedicated communication interface with the NC has been implemented. The tests necessary for the OCP calibration, and requirements for the communication layer between EPC and CN, are described and discussed. Finally, the EPC is tested on real milling processes. The validation of its performances is done by comparing the outcomes of the process with respect to a nominal case, in which the process is set up according to guidelines given by tool manufacturer. It worth be noted that this work represents not only a step foreword in increasing the level of automation of machining, but rather it proposes an architecture and an approach which can be generalised to several manufacturing processes.

Studio del processo di stampaggio delle lamiere in acciaio al boro utilizzate dall'industria automobilistica. Proposta di materiali innovativi da utilizzare per la produzione di stampi al fine di ottenere microstrutture differenziali con tempra contemporanea alla deformazione in stampo. Caratterizzazione delle proprietà termica d'interfaccia stampo-lamiera al variare del materiale dello stampo e delle pressione di contatto. Effetto dei parametri di processo sul trattamento termico in stampo del pezzo in lavorazione.

The employment of visual sensor networks in surveillance systems has brought in as many challenges as disadvantages. While the integration of multiple cameras into a network has the potential advantage of fusing complementary observations from sensors and enlarging visual coverage, it also increases the complexity of tracking tasks and poses challenges to system scalability. The research work in this thesis addresses the problem of building an efficient and scalable multi-camera tracking system that (i) adapts, in real time, to the dynamics of the monitored scenario and (ii) attempts to maximize usage and sharing of available sensing and processing resources. To perform reliable tracking, a preliminary step is fast and accurate people detection, for which we propose a locus-based probabilistic occupancy map (LPOM). The LPOM computes the probability of targets being in the map by using only motion information plus calibration data. To make the tracking system more scalable, we present a decentralized multi-camera multi-people tracking framework with a three-layer architecture, in which we formulate the overall task (i.e. tracking all people using all available cameras) as a vision based state estimation problem and aim to maximize utility and sharing of available sensing and processing resources. By exploiting the geometric relations between sensing geometry and people's positions, our method is able to dynamically and adaptively partition the overall task into a number of nearly independent subtasks with the aid of information theory, each of which tracks a subset of people with a subset of cameras (or agencies). The method hereby reduces task complexity dramatically and helps to boost parallelization and maximize the system's real time throughput and reliability while accounting for intrinsic uncertainty induced, e.g., by visual clutter, occlusion, and illumination changes. Moreover, we propose a preliminary information theoretical framework, in which we apply task-driven polling strategies that control the sensing process to minimize the number of observations to be processed while maximizing their expected impact on estimation process, and use parameter adaptation techniques to reallocate computational resources dynamically and opportunistically according to task complexity and measured evidence. For each proposed approach we carry out a number of experiments and demonstrate its efficiency and advantages.

Sociotechnical systems are systems of systems where social, technical, and organizational systems interact with each other to satisfy their requirements. The interplay of social and technical systems blurs the borders in between them, and the constant change within and outside the sociotechncial systems create difficulties to manage the overall evolution. This thesis explores the methods to model, analyse, and evolve the requirements of sociotechnical systems. We propose a systematic design process and a formal language to aid social systems refine their requirements into not other requirements but also social interactions to generate system as well as interaction specifications. Although such specifications are useful to generate interaction protocols among systems, they haven’t been investigated in detail by the requirements engineering community. We then explore the design space created during the design process with artificial intelligence planing to discover sequence of actions to satisfy requirements with minimal cost. We adopt an iterative approach for handling requirements evolution and focus on the problem of selecting the optimal set of requirements for the next release. We capture synergies among requirements in goal-oriented requirements models and transform the next release problem into a multi-objective satisfiability modulo theories/optimization modulo theories problem and solve it using an external reasoner. We apply a similar approach for risk analysis using goal models. We model goals, risks, and treatments in three layers and solve multi-objective risk analysis problem with SMT/OMT reasoning. We evaluate our proposal with self-evaluation studies, a case study and scalability experiments and report results. The novelty of these two approaches is the combination of satisfiability analysis with multi-objective optimization for goal models.

In this thesis we investigate the automatic analysis of agreement and disagreement in political documents. Our focus is on the comparison of statements about specific topics extracted from documents with no direct interaction (e.g. electoral speeches or political manifestos), in which politicians may express, sometime in an implicit way, their position. This is a challenging task, made difficult also due to the lack of annotated resources. Our contribution can be divided into two main areas. The first one is the creation of manually and automatically annotated corpora for the task (pairs of statements annotated for agreement or disagreement from different sources). The second one is a Natural Language Processing (NLP) pipeline for the automatic (supervised) classification of agreement and disagreement. This pipeline involves a novel approach to extract well-defined and accurate topics based on key-concept clusters, and two classifiers to identify the pairs of statements in agreement and disagreement (or holding no relation) according to a wide set of features, such as sentiment, entailment, and semantic representation of the topics. We think that our findings can effectively support political science researchers dealing with an increasing amount of digital data, providing insight into similarities and differences in ideologies.

Enforcing legal compliance into software systems is a non-trivial task that requires an interdisciplinary approach. This thesis presents a new methodology for legal compliance checking against European legal provisions, namely the EU Data Protection Directive, the EU General Data Protection Regulation and the revised EU Payment Services Directive. We propose two types of compliance checking mechanisms that should be exploited at design-time or run-time. The former is based on security policy analysis of access control policies. The later is built on top of an approach to synthesizing run-time monitors for workflow-driven applications. Our contributions include a comprehensive methodology for legal compliance checking, the formalization of the regulations and the prototype tool of the implemented compliance methodology.

This thesis describes the development and validation of a predictive model of graphical user interface (GUI) aesthetics. The development was informed by the processing-fluency theory of aesthetic pleasure and involved outlining several visual dimensions of GUI designs, which could affect aesthetics impression. Each of the dimensions was grounded in theory and represents a unique visual aspect of GUI design. The resulting model automatically evaluates the design dimensions and combines them in an estimate of the average impression that GUI appearance would make on the user population. The model was validated in a number of user studies proving high validity and reliability. The model outputs an aesthetics score ofuser impression and could inform the creation of more beautiful GUIs by highlighting which of the design dimensions could be improved. The thesis describes the studies that validated the model on several types of GUIs and demonstrated a potential application of the model in future research and practice.