Data mining for detecting Bitcoin Ponzi schemes

Soon after its introduction in 2009, Bitcoin has been adopted by cyber-criminals, which rely on its pseudonymity to implement virtually untraceable scams. One of the typical scams that operate on Bitcoin are the so-called Ponzi schemes. These are fraudulent investments which repay users with the funds invested by new users that join the scheme, and implode when it is no longer possible to find new investments. Despite being illegal in many countries, Ponzi schemes are now proliferating on Bitcoin, and they keep alluring new victims, who are plundered of millions of dollars. We apply data mining techniques to detect Bitcoin addresses related to Ponzi schemes. Our starting point is a dataset of features of real-world Ponzi schemes, that we construct by analysing, on the Bitcoin blockchain, the transactions used to perform the scams. We use this dataset to experiment with various machine learning algorithms, and we assess their effectiveness through standard validation protocols and performance metrics. The best of the classifiers we have experimented can identify most of the Ponzi schemes in the dataset, with a low number of false positives

Blockchain: A Graph Primer

Bitcoin and its underlying technology Blockchain have become popular in recent years. Designed to facilitate a secure distributed platform without central authorities, Blockchain is heralded as a paradigm that will be as powerful as Big Data, Cloud Computing and Machine learning. Blockchain incorporates novel ideas from various fields such as public key encryption and distributed systems. As such, a reader often comes across resources that explain the Blockchain technology from a certain perspective only, leaving the reader with more questions than before. We will offer a holistic view on Blockchain. Starting with a brief history, we will give the building blocks of Blockchain, and explain their interactions. As graph mining has become a major part its analysis, we will elaborate on graph theoretical aspects of the Blockchain technology. We also devote a section to the future of Blockchain and explain how extensions like Smart Contracts and De-centralized Autonomous Organizations will function. Without assuming any reader expertise, our aim is to provide a concise but complete description of the Blockchain technology.Comment: 16 pages, 8 figure

Bullying at the Middle School Level: A Descriptive Study

Bullying within schools has been a topic of great interest in recent years. Due to various factors, bullying is a particularly large problem at middle schools. In order to obtain further research on this topic, a study was conducted at a small suburban middle school in Connecticut. Teachers were given surveys to complete to address their thoughts on bullying. Additionally, a smaller subsample of teachers and the school social worker were interviewed. The data gathered from the surveys and interviews revealed that bullying was in fact present at the school. Participants expressed that students tend to bully one another in more indirect rather than direct ways, making it difficult for staff to notice when bullying is taking place. Being aware of this theme can help teachers and social workers at others schools learn how to better identify bullying behaviors and address them in more effective ways. On a higher level, this study has implications for policy and social work practice; legislators can work to create more uniform policies regarding bullying and social workers can gain a better understanding of how to effectively work with adolescents who are involved with bullying

Bullying in a networked era: a literature review

This research update presents an aggregation and summary of recent academic literature on youth bullying. The purpose of this document is to “translate” scholarly research for a concerned public audience, which may include but is not limited to parents, caregivers, educators, and practitioners. This translation highlights recent findings and developments in the literature and makes them accessible to the informed but non-expert reader. The document’s two guiding questions are “What is bullying?” (Section I) and “What can be done about bullying?” (Section II). Section I begins with a brief overview of key definitions and related research conversations and then addresses bullying’s prevalence, the types of individuals involved in bullying, the characteristics of individuals involved and the consequences of their involvement, and community-level dynamics related to bullying. Section II covers four areas where action has been taken to address problems associated with bullying – school policy, curricula, school climate, and parents – and ends on a note about approaches that mix or cut across these areas. The purpose is to render lessons learned from research and assessment accessible to those interested in deepening or expanding their knowledge of bullying-related issues

Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments

Decentralized systems are a subset of distributed systems where multiple authorities control different components and no authority is fully trusted by all. This implies that any component in a decentralized system is potentially adversarial. We revise fifteen years of research on decentralization and privacy, and provide an overview of key systems, as well as key insights for designers of future systems. We show that decentralized designs can enhance privacy, integrity, and availability but also require careful trade-offs in terms of system complexity, properties provided, and degree of decentralization. These trade-offs need to be understood and navigated by designers. We argue that a combination of insights from cryptography, distributed systems, and mechanism design, aligned with the development of adequate incentives, are necessary to build scalable and successful privacy-preserving decentralized systems

SpartanDark: Anonymity Model Integration with a Blockchain Network using SpartanGold

Demand for blockchain ecosystems has seen exponential growth in recent times due to its decentralized nature and trustless verification process for the transactions involved. However, transaction data needs to be leveraged for verification, which coupled with the transparent nature of the blockchain ledger, provides sufficient data for malicious entities to reveal identities and even financial history of users. Data masking techniques have been employed over the years to make blockchain transactions anonymous, making them resistant to identity analysis, a key set of methods being zero-knowledge proof (zk-proof) protocols that guarantee zero data leak. In this research, we develop SpartanDark, a fork of SpartanGold that integrates a zk-proof protocol, Zero-Knowledge Succinct Non-interactive Argument of Knowledge (zk-SNARK) for transaction verification. SpartanDark provides a Decentralized Anonymous Payment scheme (DAP) with anonymity guarantees, akin to the privacy transaction model in Zerocash. Our analysis shows that this transaction model presents a high degree of data privacy when compared to traditional blockchain models, carrying zero identifying information about the transaction across the blockchain, making it implausible for other entities to profile any user and thus reestablishing one of the core tenets of blockchain: privacy

Examining peer-controlled KR schedules during the learning of a movement-timing task as a function of task experience.

Learners can be provided with feedback in the form of knowledge of results (KR), under self-controlled and peer-controlled schedules. Recently, McRae, Hansen, and Patterson (2015), identified that inexperienced peers can provide KR that can facilitate motor skill acquisition. However, it is currently unknown whether previous task experience differentially impacts how peers present learners with KR and whether this KR impacts motor skill acquisition. In the present study, participants were randomly assigned to become inexperienced peer facilitators, learners with an inexperienced peer, learners with self-control who later became experienced peers, learners with an experienced peer, or learners in a control group. During acquisition learners completed a serial-timing task with a goal of 2500ms and returned approximately twenty four hours later for a delayed retention, time transfer, and pattern transfer test. We predicted that during the delayed tests, learners with self-control would outperform all other groups. Furthermore, we predicted that learners who received KR from experienced peers would outperform learners who received KR from inexperienced peers. However, our results indicated that participants who received peer-controlled and self-controlled KR schedules learned the task in an equivalent manner. Thus, our results are novel as they identify that inexperienced peers can provide KR that is as effective as KR provided by experienced peers and KR requested under self-controlled conditions

Social Media And Health: Implications For Primary Health Care Providers

This report is the second deliverable of the ?Digital Inclusion and Social Knowledge Media for Health: Frameworks and Roadmaps? project. The first discussed the concept of social and digital exclusion whilst this report focuses on the emerging phenomenon of social media. The report outlines current knowledge on the users and usages of social media for health and goes on to discuss social media in the context of a continuing focus (ref. D1.1) on the areas of mental health, smoking cessation and teenage lifestyles. The report concludes with an outline of an approach to a ?social media strategy? and with suggestions for directions for future research

Pretty Private Group Management

Group management is a fundamental building block of today's Internet applications. Mailing lists, chat systems, collaborative document edition but also online social networks such as Facebook and Twitter use group management systems. In many cases, group security is required in the sense that access to data is restricted to group members only. Some applications also require privacy by keeping group members anonymous and unlinkable. Group management systems routinely rely on a central authority that manages and controls the infrastructure and data of the system. Personal user data related to groups then becomes de facto accessible to the central authority. In this paper, we propose a completely distributed approach for group management based on distributed hash tables. As there is no enrollment to a central authority, the created groups can be leveraged by various applications. Following this paradigm we describe a protocol for such a system. We consider security and privacy issues inherently introduced by removing the central authority and provide a formal validation of security properties of the system using AVISPA. We demonstrate the feasibility of this protocol by implementing a prototype running on top of Vuze's DHT