The study was conducted in Norrbottens County. The purpose with the study was to examine which way social studie teachers interpret and convert economy education. How do social studie teachers teach economy in social science? How for content do teacher choose to focus in economy section in social sciene subject and the choice or emphasis about the content in education: national economy or personal fiance or something else? Which factors lies as basis for teachers to convert economy education in different ways, one choice that could lead to students getting varied education? The theory that is used in the study is factor theoretical perspective and the research approach is deductive. The method that is used in the essay is a qualitative individual interview with a mix of open questions and half standardise questions and the study is a case study. Six teachers was interviewed in upper secondary school. The result of the study the teachers believes that in the economy part of social studies that regulatory documents controls the shape, what they evaluting after and pervade the teaching profession as a entirety. Which made the formulation arena to have a increased influence then transformation arena. That means that the teachers autonomy to interpret have decreased when teachers follows the regulatory documents stricter. / Studien genomfördes i Norrbottens län. Syftet med studien är att undersöka på vilket sätt samhällskunskapslärare tolkar och omvandlar ekonomiundervisningen. Vad undervisar samhällskunskapslärare om i samhällskunskap när det gäller ekonomi? Vilket innehåll väljer lärarna att fokusera på inom ekonomidelen av samhällskunskapsämnet, det vill säga valet av eller betoningen på själva innehållet i undervisningen: samhällsekonomi eller privatekonomi eller någonting annat? Vilka faktorer ligger till grund för att lärarna omsätter ekonomiundervisningen på olika sätt, val som i sin tur kan leda till att eleverna får varierande undervisning? Den teori som används i studien är ramfaktorperspektiv och forskningsansatsen är deduktiv. Metoden som används i uppsatsen är kvalitativa enskilda intervjuer med en blandning av öppna frågor och halvstandardiserade frågor och studien är en fallstudie. Sex lärare från gymnasiet intervjuades. I resultatet av studien anser lärarna att inom den ekonomiska delen av samhällskunskap så styr styrdokumenten utformningen gällande inriktningen för deras bedömning samt genomsyrar läraryrket i sin helhet. Vilket innebär att formuleringsarenan har fått en större påverkan än transformeringsarenan. Det innebär i sin tur att lärarnas friutrymme för tolkning har minskat när lärarna följer styrdokumenten till punkt och pricka.

<p>Advances in Artificial Intelligence (AI), or more precisely on Neural Networks (NNs), and fast processing technologies (e.g. Graphic Processing Units or GPUs) in recent years have positioned NNs as one of the main machine learning algorithms used to solved a diversity of problems in both academia and the industry. While they have been proved to be effective in solving many tasks, the lack of security guarantees and understanding of their internal processing disrupts their wide adoption in general and cybersecurity-related applications. In this dissertation, we present the findings of a comprehensive study aimed to enable the absorption of state-of-the-art NN algorithms in the development of enterprise solutions. Specifically, this dissertation focuses on (1) the development of defensive mechanisms to protect NNs against adversarial attacks and (2) application of NN models for anomaly detection in enterprise networks.</p><p>In this state of affairs, this work makes the following contributions. First, we performed a thorough study of the different adversarial attacks against NNs. We concentrate on the attacks referred to as trojan attacks and introduce a novel model hardening method that removes any trojan (i.e. misbehavior) inserted to the NN models at training time. We carefully evaluate our method and establish the correct metrics to test the efficiency of defensive methods against these types of attacks: (1) accuracy with benign data, (2) attack success rate, and (3) accuracy with adversarial data. Prior work evaluates their solutions using the first two metrics only, which do not suffice to guarantee robustness against untargeted attacks. Our method is compared with the state-of-the-art. The obtained results show our method outperforms it. Second, we proposed a novel approach to detect anomalies using LSTM-based models. Our method analyzes at runtime the event sequences generated by the Endpoint Detection and Response (EDR) system of a renowned security company running and efficiently detects uncommon patterns. The new detecting method is compared with the EDR system. The results show that our method achieves a higher detection rate. Finally, we present a Moving Target Defense technique that smartly reacts upon the detection of anomalies so as to also mitigate the detected attacks. The technique efficiently replaces the entire stack of virtual nodes, making ongoing attacks in the system ineffective.</p><p> </p>