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Background: The ongoing digitalization in the world with accelerated advancement of technology both develops and challenges the traditional view of means of payment. Legal and economic challenges havebeen recognized in regard to Bitcoin, one of these challenges refer to Bitcoin being defined as property of capital which has caused difficulties in individual income declaration and an overall challenge for cryptocurrencies to act as currencies. Furthermore, Bitcoin is being recognized as an investment possibility, however, since Bitcoin transactions are anonymous it contributes to issues within the public economy as profits made from Bitcoin trades are being evaded.  Purpose: The purpose of this study is to analyze tax evasion among Swedish investors when trading with Bitcoin. Furthermore, this study aims to expand the understanding of Bitcoin traders and determine whether some individuals are more likely to evade taxes in regard to trades with Bitcoin. The intentionis to identify whether there is a connection in demographic- and behavioral factors that indicate whether one is more willing to comply with tax obligations or not. This paper further aims to investigate the STA’s perception of Bitcoin in comparison to the general public as well as how the STA work with the challenges that exist today. Method: This study uses a combination of an inductive and an explorative approach with a mainly quantitative research strategy. Three sources of data have been used: 1) an online survey published in forums for Swedish investors, 2) interviews with the STA 3) court orders provided by the STA. Furthermore, a binary logistic model was performed in SPSS to examine statistically significant results. Conclusion: In regard to taxes linked to trades with Bitcoin, the findings of this study confirm that women are more likely to evade taxes, individuals between the ages of 50 and 79 are less likely to evade taxes in comparison to ages ranging between 18 and 29, individuals who are married are more likely to evade taxes than individuals who are single and investors using platforms registered within Scandinavia are more likely to evade taxes. In addition, the findings of this study indicates that behavioral factors such as morale, trust, awareness, social influence and probability of detection may be influential in tax compliance. Furthermore, the study found a deviation in the perception of taxation linked to Bitcoin where the STA does not recognize taxation linked to Bitcoin as a cause of concern whilst the general public find it to be difficult and an increased risk of tax evasion.

The aim of the project was to examine the feasibilityof evading continuous authentication systems with a generativeadversarial network. To this end, a group of supervised andunsupervised state-of-the-art classifiers were trained on a publiclyavailable dataset of stroke patterns on mobile devices. To find thebest configurations for each classifier, hyper-parameter searcheswere performed. To attack the classifiers, a generative adversarialnetwork was trained on the dataset to reproduce samples followingthe same distribution. The generative adversarial networkwas optimized to maximize the Equal Error Rate metric of theclassifiers on the reproduced data. Our results show that theEqual Error Rate and the Threshold False Acceptance Rateincreased on generated samples compared to random evasionattacks. Across the classifiers, the greatest increase in Equal ErrorRate was 26 percent (for the artificial neural network), and thegreatest increase in Threshold False Acceptance Rate was 60percent for the same classifier. Moreover, it was found that, ingeneral, the unsupervised classifiers were more robust towardsthis type of attack. The results indicate that evasion attacksagainst continuous authentication systems using a generativeadversarial network are feasible and thus constitute a real threat. / Målet med detta projekt var att undersökamöjligheten att undgå ett aktivt verifieringssystem med hjälpav ett generativt nätverk. För att göra detta valde vi ut ettantal moderna klassifieringsalgoritmer och tränade dem på enoffentlig datasamling av svepmönster på mobiltelefoner. För atterhålla de bästa konfigurationerna för varje klassifieringsalgoritmutfördes hyper-parameter sökningar. För att attackera klassifieringsalgorithmernaimplementerades ett generative adversarialnetwork som tränades på datasamlingen för att reproduceraliknande svepmönster. Det generativa nätverket optimerades föratt maximera klassifieringsalgoritmernas likvärdiga felkvot medden reproducerade datan. Resultaten visar att den likvärdigafelkvoten och tröskeln av den felaktiga verifieringskvoten ökademed den reproducerade datan jämfört med slumpmässiga tester.Den högsta ökningen av den likvärdiga felkvoten var 26 procent(för det artificiella neurala nätverket) och den högsta ökningenav tröskeln av den felaktiga verifieringskvoten var 60 procent forsamma algoritm. Därutöver fann vi att de oövervakade klassifieringsalgoritmernavar mer motståndskraftiga mot denna typenav attack jämfört med de övervakade klassifieringsalgoritmerna.Resultaten tyder på att det är möjligt att till viss del undgå ettaktivt verifieringssystem med hjälp av ett generative adversarialnetwork och att denna typen av attacker utgör ett konkret hot. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

Pursuit-evasion problems comprise a set of pursuers that strive to catch oneor several evaders, often in a constrained environment. This thesis proposesand compares heuristic algorithms for pursuit-evasion problems wherein several double integrator agents pursue a single evader in a bounded subset of theEuclidean plane. Different methods for assigning surrounding target points tothe pursuers are tested numerically. In addition, a method which finds the timeoptimal strategy for pursuing a static target in an unconstrained setting is presented, and is then used to pursue the assigned, dynamic, target. Numericalresults show that the time optimal strategy for pursuing a static target translateswell to the dynamic problem.

Mercantile law / LLM (Tax Law)

Mercantile law / LLM (Tax Law)

The aim of the diploma thesis is to answer the question of where is the line between tax evasion, tax avoidance and tax fraud. Furthermore to characterize methods of measurement tax evasion and introduced actions against tax evasion and tax avoidance at the national and international level. This aim is achieved through analytical and synthetic methods used from the first to third chapter of the diploma thesis. The main goal of diploma thesis is to use external sources of information to determining transfer pricing methods in small economic models. To achieve this goal is at first step explain the Arm's length principle, comparative analysis and subsequently introduced each transfer pricing method. The attention is also paid to assessment of each transfer pricing method with using analytical, synthetic and comparative methods.

The thesis is aimed at estimate of calculation of tax evasions at value-added tax (VAT) in the Czech Republic between 2005 and 2011. The estimates are executed on the basis of the concept of tax gap. Tax gap compares theoretically calculated tax amount with the real tax amount. Results of the calculations are compared to the results of calculations of cumulative studies of tax gap executed in the countries of European Union. The issue of grey economy is also topic of the thesis and different approaches to calculations of grey economy are mentioned. Topics like tax-evasions causes, tax-evasions types and ways of its solving follow. Conclusion of the thesis includes questionnaire survey among payers of VAT. Survey is especially aimed at tax evasions and possible solutions to them.

Целью данной работы совершенствование налоговой политики для достижения более эффективного противодействия уклонения от налога на доходы физических лиц. В первой главе проведен анализ угроз экономической безопасности государства, выявлены факторы сокрытия налогов, а также проведено сравнение методов оценки уклонения от налогообложения. Во второй главе произведена оценка масштабов сокрытия налогов и определены последствия от данного явления. В третьей главе определены проблемы и пути совершенствования механизма по противодействию от уплаты налогов. / The aim of this work is to improve tax policy in order to achieve more effective counteraction to personal income tax evasion. The first chapter analyzes the threats to the economic security of the state, identifies the factors of tax evasion, and compares methods for assessing tax evasion. The second chapter assesses the scale of tax evasion and determines the consequences of this phenomenon. The third chapter identifies the problems and ways of improving the mechanism for countering tax payments.

本文首先依據過去實際發生的案例彙總逃漏稅方法，再與國外逃漏稅的行政罰及刑事罰有關規定說明比較。 接著以經濟模型對罰款率、查獲率與逃漏稅關係作分析。發現因企業的平均稅率較個人平均稅率為高，查獲率提高對企業逃漏稅嚇阻作用較個人為大。而對個人逃漏稅則以罰款率的提高，較能發揮嚇阻作用。 最後在Stata軟體的運算下，選取89至91年的營利事業申報及漏稅資料，依Stata給予的評分標準，預測逃漏稅傾向較高的企業。歸納如下：1.有欠稅記錄者，2.3,000萬以上查帳案件，3.設籍台北市郊區者，4.行政區常異動者(遷址)，5.設立期間4－12年，6.營業收入3,700萬元以上，7.社會服務及個人服務業，虛報薪資有營造業。 由以上分析七要點可協助稽徵機關在選案查核中作參考，提高逃漏稅的查獲率，降低逃漏稅誘因。並提供稅務機關建議事項如下：1.加強獨資合夥企業的租稅輔導，2.依逃漏稅傾向調整抽查率，3.提高虛報薪資的罰款率，4.鼓勵臨時工所得扣繳，5.刑事罰適用性提高。 期盼本文的研究可幫助建立租稅公平、徵納和諧的租稅環境，並充足稅源，增益國庫。