Your Smart Home Can't Keep a Secret: Towards Automated Fingerprinting of IoT Traffic with Neural Networks

The IoT (Internet of Things) technology has been widely adopted in recent years and has profoundly changed the people's daily lives. However, in the meantime, such a fast-growing technology has also introduced new privacy issues, which need to be better understood and measured. In this work, we look into how private information can be leaked from network traffic generated in the smart home network. Although researchers have proposed techniques to infer IoT device types or user behaviors under clean experiment setup, the effectiveness of such approaches become questionable in the complex but realistic network environment, where common techniques like Network Address and Port Translation (NAPT) and Virtual Private Network (VPN) are enabled. Traffic analysis using traditional methods (e.g., through classical machine-learning models) is much less effective under those settings, as the features picked manually are not distinctive any more. In this work, we propose a traffic analysis framework based on sequence-learning techniques like LSTM and leveraged the temporal relations between packets for the attack of device identification. We evaluated it under different environment settings (e.g., pure-IoT and noisy environment with multiple non-IoT devices). The results showed our framework was able to differentiate device types with a high accuracy. This result suggests IoT network communications pose prominent challenges to users' privacy, even when they are protected by encryption and morphed by the network gateway. As such, new privacy protection methods on IoT traffic need to be developed towards mitigating this new issue

Analysis of Client Anonymity in the Tor Network

The Tor Network has emerged as the most popular service providing sender anonymity on the Internet. It is a community-driven network with most of the infrastructure operated by volunteers. Peer-to-Peer (P2P) file sharing applications, such as BitTorrent, take up a large portion of the available resources in Tor, which reduce the quality of service for those browsing the web through Tor. In this thesis, experiences from operating a Tor exit relay with a reduced exit policy are recounted. Additionally, the lifecycle of the exit relay is presented and an analysis of the application distribution of exit traffic is done. This analysis uncovers that the reduced exit policy may reduce the BitTorrent traffic share as the total, byte-wise traffic share constituted by BitTorrent was 25.4%, which is lower than in similar analyses done earlier. Tor is a low latency service, thus it is possible that packet latency can leak information about either the source, the destination or both ends of the encrypted Tor traffic. There have been numerous proposals for side-channel attacks in the Tor Network, with one of the most interesting being the website fingerprinting attack. The website fingerprinting attack attempts to map encrypted client-side traffic with a web page by utilizing side-channel information from web page visits to train a machine learning classifier, which in turn is used to predict the web page corresponding to encrypted, client-side Tor traffic. This thesis aims to review existing website fingerprinting attacks as well as to propose a basic attack sorting under this category. The thesis argues that it is feasible that state of the art web site fingerprinting attacks can be applied in a real-world scenario under the assumption that certain Tor users visit censored web pages repeatedly. Website fingerprinting attacks proposed up until now attempt to identify individual web pages from an encrypted traffic stream. This thesis proposes a web site fingerprinting attack, an attack related to the general website fingerprinting attack, but instead of web pages, it attempts to identify web sites. The attack utilizes, among other things, the browsing pattern to attempt to map encrypted client-side traffic to a web site. The browsing pattern data is collected from a test group made up of volunteers who are asked to browse web sites as they feel natural. In one of the most successful experiments, the attack resulted in a True Positive Rate (TPR) of 91.7% and a corresponding False Positive Rate (FPR) of 0.95% from a total of 222 attempted web site predictions

Personal Learning Environments for Inquiry-Based Learning

Personal Learning Environments have recently emerged as a novel approach to learning, putting learners in the spotlight and providing them with the tools for building their own learning environments according to their specific learning needs and aspirations. This approach enables learners to take complete control over their learning, thus becoming self-regulated and independent. This paper introduces a new European initiative for supporting and enhancing inquiry-based learning through Personal Learning Environments consisting of personal and social inquiry tools. This approach aims at supporting students in developing their self-regulated learning skills by conducting their scientific inquiries in collaboration with their peers

Revisiting the legal regulation of digital identity in the light of global implementation and local difference

This thesis aims to address a vital gap that has emerged in the digital identity regulatory discourse: how can the legal regulation of digital identity mirror the global nature of digital identity and be compatible with national local difference? Digital identity, or the digital representation of an individual, is a complex concept, which manifests in myriad forms (e.g. authenticators, claims, data or information, identifiers, presence, relationship representations and reputation) and natures. As such, it engages a gamut of legal domains ranging from criminal law, constitutional law, human rights law, law of identity schemes, contract law, intellectual property law, tort law and data protection law. Digital identity is global and local in its nature, influence and effects. Yet, the digital identity regulatory discourse has primarily developed in and focussed on the digitally advanced West, leaving out countries like India which are developing strong digital presences, with their own digital identity perceptions and needs. This situation is adverse to the sustained future of digital identity. Thus, the contribution of this thesis lies in filling this gap and preparing the ground for a dialogue between different countries with different national agendas through building international and local awareness of how similarities and differences operate in respect of digital identity, its regulation and providing a modest solution to help preserve the global and local dimensions of digital identity and its regulation. To this end, the thesis carried out comparative legal research on the legal regulation of digital identity using the UK and India as base jurisdictions. The original hypothesis was that that immense differences in the legal regulation of digital identity between the comparator countries would emerge. Yet, though differences were evident, considerable degrees of similarity also emerged, not just on the superficial level of mere identity of rules, but also in legal practice, in large part attributable to India’s penchant for legal transplants. While the transplantation of Western law did not result in a full-scale rejection of the transplanted laws in relation to digital identity in India, there are indications of anomalies caused by the imposition of Western cultural norms through law on an Indian society ill prepared for it. Thus there has resulted a tension between the local and the global, the indigenous and the externally imposed. The challenge is thus to resolve this, taking into account, on the one hand the need to maintain the global nature and relevance of digital identity and the other, the need to accommodate and be responsive to local differences. The thesis proposes a tentative solution called the tri-elemental framework (TeF) which draws from the Indian philosophical and legal concept of dharma (and its elements of Sad Achara, Vyavahara and Prayaschitta) and learns from the most universally relevant digital identity proposal, De Hert’s right to identity. The solution provides one way in which the law regulating digital identity, whatever its nature, can be made sense of and acquire cultural meaning appropriate to local contexts

Deep Learning in Medical Image Analysis

The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

Implementing the measurement of modern service delivery mechanisms in a selected range of English councils.

This research provides the first thorough investigation into, and analysis of, the literature on e-government metrics and has opened up the topic and literature to the practitioner community. The research focuses on English local government, in response to what the researcher had experienced as haphazard implementation of e-government. Supplementary explorations included official and unofficial reasons for the adoption of e-government, along with the role of politics and Politics – local, national and international. Until this research, the main focus for e-government measurement had been on targets or large and complex analyses suitable only for central government. Instead, this research proposes parsimonious measurement. Such measurement, reliant upon collating citizen feedback across delivery channels, will assist improvement to services and assist channel migration. This had never been examined before. Since the subject of the research was electronic government, an action research methodology was employed, using electronic research instruments to deliver surveys, provide survey results and to house research models and background. The researcher is a practitioner within the field, so the instruments were designed to cross-fertilize the academic and practitioner thinking on the subject. It is expected that the research tool, in the form of the weblog, will continue (in the longer term) to assist professionals in debating the use of metrics. Ongoing research will continue to stretch across the academic and practitioner boundaries. This research makes original contributions to knowledge by revealing the most appropriate mechanism for the management and use of e-government, amongst other mechanisms for service delivery in the public sector, especially considering smaller authorities

CIMODE 2016: 3º Congresso Internacional de Moda e Design: proceedings

O CIMODE 2016 é o terceiro Congresso Internacional de Moda e Design, a decorrer de 9 a 12 de maio de 2016 na cidade de Buenos Aires, subordinado ao tema : EM--‐TRAMAS. A presente edição é organizada pela Faculdade de Arquitetura, Desenho e Urbanismo da Universidade de Buenos Aires, em conjunto com o Departamento de Engenharia Têxtil da Universidade do Minho e com a ABEPEM – Associação Brasileira de Estudos e Pesquisa em Moda.info:eu-repo/semantics/publishedVersio