A study of EU data protection regulation and appropriate security for digital services and platforms

A law often has more than one purpose, more than one intention, and more than one interpretation. A meticulously formulated and context agnostic law text will still, when faced with a field propelled by intense innovation, eventually become obsolete. The European Data Protection Directive is a good example of such legislation. It may be argued that the technological modifications brought on by the EU General Data Protection Regulation (GDPR) are nominal in comparison to the previous Directive, but from a business perspective the changes are significant and important. The Directive’s lack of direct economic incentive for companies to protect personal data has changed with the Regulation, as companies may now have to pay severe fines for violating the legislation. The objective of the thesis is to establish the notion of trust as a key design goal for information systems handling personal data. This includes interpreting the EU legislation on data protection and using the interpretation as a foundation for further investigation. This interpretation is connected to the areas of analytics, security, and privacy concerns for intelligent service development. Finally, the centralised platform business model and its challenges is examined, and three main resolution themes for regulating platform privacy are proposed. The aims of the proposed resolutions are to create a more trustful relationship between providers and data subjects, while also improving the conditions for competition and thus providing data subjects with service alternatives. The thesis contributes new insights into the evolving privacy practices in the digital society at an important time of transition from the service driven business models to the platform business models. Firstly, privacy-related regulation and state of the art analytics development are examined to understand their implications for intelligent services that are based on automated processing and profiling. The ability to choose between providers of intelligent services is identified as the core challenge. Secondly, the thesis examines what is meant by appropriate security for systems that handle personal data, something the GDPR requires that organisations use without however specifying what can be considered appropriate. We propose a method for active network security in web software that is developed through the use of analytics for detection and by inserting data generators into a software installation. The active network security method is proposed as a framework for achieving compliance with the GDPR requirements for services and platforms to use appropriate security. Thirdly, the platform business model is considered from the privacy point of view and the implication of “processing silos” for intelligent services. The centralised platform model is considered problematic from both the data subject and from the competition standpoint. A resolution is offered for enabling user-initiated open data flow to counter the centralised “processing silos”, and thereby to facilitate the introduction of decentralised platforms. The thesis provides an interdisciplinary analysis considering the legal study (lex lata) and additionally the resolution (lex ferenda) is defined through argumentativist legal dogmatics and (de lege ferenda) of how the legal framework ought to be adapted to fit the described environment. User-friendly Legal Science is applied as a theory framework to provide a holistic approach to answering the research questions. The User-friendly Legal Science theory has its roots in design science and offers a way towards achieving interdisciplinary research in the fields of information systems and legal science

Feature Engineering for Detection of Wormhole Attacking in Mobile Ad Hoc Networks with Machine Learning Methods

Due to the self-configuring nature of a Mobile Ad Hoc Network (MANET), each node must participate in the routing process, in addition to its other activities. Therefore, routing in a MANET is especially vulnerable to malicious node activity leading to potentially severe disruption in network communications. The wormhole attack is a particularly severe MANET routing threat since it is easy to launch, can be launched in several modes, difficult to detect, and can cause significant communication disruption. In this paper we establish a practice for feature engineering of network data for wormhole attack prevention and detection with intrusion detection methods based on machine learning

Reinforcement Learning for Extended Reality: Designing Self-Play Scenarios

A common problem for deep reinforcement learning networks is a lack of training data to learn specific tasks through generalization. In this review, we look at extended reality, a promising but often overlooked field, for training agents using reinforcement learning. We review several techniques from the literature and then synthesize the information in order to propose a recommended design. Meta learning offers an important way forward, but the agents ability to perform self-play is considered crucial for achieving successful AI. Therefore, we focus on improving self-play scenarios for teaching self-learning agents, by providing a supportive environment for improved agent-environment interaction

Expectancies, Socioeconomic Status, and Self-Rated Health: Use of the Simplified TOMCATS Questionnaire

Background: Coping has traditionally been measured with inventories containing many items meant to identify specific coping strategies. An alternative is to develop a shorter inventory that focusses on coping expectancies which may determine the extent to which an individual attempts to cope actively. Purpose: This paper explores the usefulness and validity of a simplified seven-item questionnaire (Theoretically Originated Measure of the Cognitive Activation Theory of Stress, TOMCATS) for response outcome expectancies defined either as positive (“coping”), negative (“hopelessness”), or none (“helplessness”). The definitions are based on the Cognitive Activation Theory of Stress (CATS; Ursin and Eriksen, Psychoneuroendocrinology, 29(5):567–92, 2004). The questionnaire was tested in two different samples. First, the questionnaire was compared with a traditional test of coping and then tested for validity in relation to socioeconomic differences in self-reported health. Methods: The first study was a comparison of the brief TOMCATS with a short version of the Utrecht Coping List (UCL; Eriksen et al., Scand J Psychol, 38(3):175–82, 1997). Both questionnaires were tested in a population of 1,704 Norwegian municipality workers. The second study was a cross-sectional analysis of TOMCATS, subjective and objective socioeconomic status, and health in a representative sample of the Swedish working population in 2003– 2005 (N011,441). Results: In the first study, the coping item in the TOMCATS questionnaire showed an expected significant positive correlation with the UCL factors of instrumental masteryoriented coping and negative correlations with passive and depressive scores. There were also the expected correlations for the helplessness and hopelessness scores, but there was no clear distinction between helplessness and hopelessness in the way they correlated with the UCL. In the second study, the coping item in TOMCATS and the three-item helplessness scores showed clear and monotonous gradients over a subjective socioeconomic status (SES) ladder. Positive response outcome expectancy (“coping”) was related to high subjective SES and no expectancy (“helplessness”) to low subjective SES. In a model including age and sex, TOMCATS scores explained more variance (r200.16) in self-reported health than both subjective (r200.08) and objective SES (r200.02). Conclusion: The brief TOMCATS questionnaire showed acceptable and significant correlations with a traditional coping questionnaire and is sensitive enough to register systematic differences in response outcome expectancies across the socioeconomic ladder. The results furthermore confirm that psychological and learning factors contribute to the socioeconomic gradient in health.publishedVersio

Multiple drivers of large-scale lichen decline in boreal forest canopies

Thin, hair-like lichens (Alectoria, Bryoria, Usnea) form conspicuous epiphyte communities across the boreal biome. These poikilohydric organisms provide important ecosystem functions and are useful indicators of global change. We analyse how environmental drivers influence changes in occurrence and length of these lichens on Norway spruce (Picea abies) over 10 years in managed forests in Sweden using data from >6000 trees. Alectoria and Usnea showed strong declines in southern-central regions, whereas Bryoria declined in northern regions. Overall, relative loss rates across the country ranged from 1.7% per year in Alectoria to 0.5% in Bryoria. These losses contrasted with increased length of Bryoria and Usnea in some regions. Occurrence trajectories (extinction, colonization, presence, absence) on remeasured trees correlated best with temperature, rain, nitrogen deposition, and stand age in multinomial logistic regression models. Our analysis strongly suggests that industrial forestry, in combination with nitrogen, is the main driver of lichen declines. Logging of forests with long continuity of tree cover, short rotation cycles, substrate limitation and low light in dense forests are harmful for lichens. Nitrogen deposition has decreased but is apparently still sufficiently high to prevent recovery. Warming correlated with occurrence trajectories of Alectoria and Bryoria, likely by altering hydration regimes and increasing respiration during autumn/winter. The large-scale lichen decline on an important host has cascading effects on biodiversity and function of boreal forest canopies. Forest management must apply a broad spectrum of methods, including uneven-aged continuous cover forestry and retention of large patches, to secure the ecosystem functions of these important canopy components under future climates. Our findings highlight interactions among drivers of lichen decline (forestry, nitrogen, climate), functional traits (dispersal, lichen colour, sensitivity to nitrogen, water storage), and population processes (extinction/colonization)