White Mirror: Leaking Sensitive Information from Interactive Netflix Movies using Encrypted Traffic Analysis

Privacy leaks from Netflix videos/movies is well researched. Current state-of-the-art works have been able to obtain coarse-grained information such as the genre and the title of videos by passive observation of encrypted traffic. However, leakage of fine-grained information from encrypted traffic has not been studied so far. Such information can be used to build behavioural profiles of viewers. On 28th December 2018, Netflix released the first mainstream interactive movie called 'Black Mirror: Bandersnatch'. In this work, we use this movie as a case-study to show for the first time that fine-grained information (i.e., choices made by users) can be revealed from encrypted traffic. We use the state information exchanged between the viewer's browser and Netflix as the side-channel. To evaluate our proposed technique, we built the first interactive video traffic dataset of 100 viewers; which we will be releasing. Preliminary results indicate that the choices made by a user can be revealed 96% of the time in the worst case.Comment: 2 pages, 2 figures, 1 tabl

Competition for Popularity in Bipartite Networks

We present a dynamical model for rewiring and attachment in bipartite networks in which edges are added between nodes that belong to catalogs that can either be fixed in size or growing in size. The model is motivated by an empirical study of data from the video rental service Netflix, which invites its users to give ratings to the videos available in its catalog. We find that the distribution of the number of ratings given by users and that of the number of ratings received by videos both follow a power law with an exponential cutoff. We also examine the activity patterns of Netflix users and find bursts of intense video-rating activity followed by long periods of inactivity. We derive ordinary differential equations to model the acquisition of edges by the nodes over time and obtain the corresponding time-dependent degree distributions. We then compare our results with the Netflix data and find good agreement. We conclude with a discussion of how catalog models can be used to study systems in which agents are forced to choose, rate, or prioritize their interactions from a very large set of options.Comment: 13 Pages, 19 Figure

An Open Letter to Netflix

If there is one thing that I will be absolutely ashamed in admitting to you, it’s that I love television. Love it. Not in a turn-it-on-watch-whatever-all-TV-rocks kind of way, but in an I’m-overly-obsessed-with-15-shows-at-a-time kind of way, to the point where I could say that being able to watch the latest episode of Suits or Community could easily be the highlight of my day (week, year…). [excerpt

Netflix and the Development of the Internet Television Network

When Netflix launched in April 1998, Internet video was in its infancy. Eighteen years later, Netflix has developed into the first truly global Internet TV network. Many books have been written about the five broadcast networks – NBC, CBS, ABC, Fox, and the CW – and many about the major cable networks – HBO, CNN, MTV, Nickelodeon, just to name a few – and this is the fitting time to undertake a detailed analysis of how Netflix, as the preeminent Internet TV networks, has come to be. This book, then, combines historical, industrial, and textual analysis to investigate, contextualize, and historicize Netflix\u27s development as an Internet TV network. The book is split into four chapters. The first explores the ways in which Netflix\u27s development during its early years a DVD-by-mail company – 1998-2007, a period I am calling Netflix as Rental Company – lay the foundations for the company\u27s future iterations and successes. During this period, Netflix adapted DVD distribution to the Internet, revolutionizing the way viewers receive, watch, and choose content, and built a brand reputation on consumer-centric innovation. This reputation served it well during its second phase, Netflix as Syndicator (2007-12), when the company turned from DVD rentals to online distribution. In chapter two, I explain who Netflix adapted syndication – a business model that has been a staple of US broadcasting for half a century – to Internet distribution. By doing so, Netflix up-ended both the TV industry\u27s traditional content release structures and viewers\u27 habits. By shifting TV distribution to the Internet, Netflix drastically increased the control viewers have over where, when, and on what devices viewers watch TV. In its third phase, Netflix entered the original programming business by subtly adapting traditional program genres, content, and release schedules to Internet video. I split this phase – Netflix as Internet Network (2012-present) – into two chapters. While many of Netflix\u27s concerns parallel those of traditional networks – in terms of production and financing, for example – Internet networks also have a number of unique concerns in areas such as Net Neutrality and distribution windows. Netflix has led the charge on these issues, and chapter three explores Netflix\u27s role as the first Internet network, including the development of its binge-viewing strategy and its push into international distribution. Finally, chapter four takes a deep dive in Netflix\u27s foray into original program production. In its third phase, Netflix has adapted traditional TV structures to Internet distribution. Despite the innovations in short-form and user-generated content that sites like YouTube, Crackle, and Twitch have named, Netflix\u27s traditional approach to programming has set the template for successful Internet networks that has been adopted by the likes of Hulu, Amazon, and Yahoo Screen. Chapter four analyses Netflix\u27s biggest programs - including House of Cards, Orange is the New Black, Daredevil and others - to explain how Netflix has adapted traditional TV genres and structures to the freedoms in production, marketing, and content possibilities that the Internet affords. In the same was that NBC set the example for broadcast networks in the 1950s and HBO developed the framework for cable TV in the 1990s, Netflix has set the template for Internet TV in the 2000s. Netflix\u27s mix of technological advancements, consumer-centric practices, personalized content, and global mindset have become the gold standard for the how-and-why of developing a successful Internet TV network. Although other aspiring Internet networks Hulu and Amazon started out with a different ethos than Netflix, Netflix\u27s financial, creative, and cultural success has forced a series of reactionary decisions from both Hulu and Amazon that have brought them closer and closer to the foundations Netflix began laying out in 1998. So while the Netflix model isn\u27t the only possible model for an Internet network, it has become the blueprint for the newly-developing Internet TV ecosystem

Netflix and the design of the audience: The homogenous constraints of data-driven personalization

This paper explores how audiences engage with Netflix as an intermediary in their digital lives, and how Netflix, as it is designed, creates a highly constrained system for its users. The paper is based on a study of observed use and discussions with Netflix users. It explores the limitations that are designed into Netflix as a digital media platform, and how Netflix users engage with this system that obscures rather than clarifies the contents of the platform. The paper discusses examples of frustration, confusion, and misdirection that Netflix, as a heavily constrained system, cultivates. It argues that the thoughts, feelings, and desires of audiences are not reflected in the data-driven design of digital media platforms like Netflix. Instead, data are used by Netflix to design a personalized environment that acts as a set of blinders which constrain the agency of the audience through an interface designed to dazzle and disorient Netflix users

PENGARUH BAURAN PROMOSI DAN BRAND IMAGE TERHADAP MINAT BELI BELANGGANAN NETFLIX (Studi survei berlangganan netflix di masa pandemi)

Penelitian ini bertujuan untuk mengethui seberapa besar pengaruh Bauran Promosi dan Brand Image terhdap Minat Beli berlangganan Netflix. Netflix merupakan perusahaan yang bergerak dibidang jasa layanan perfilman streaming berbayar berbasis berlangganan, netflix menawarkan layanan Tv Show, Dokumenter dan Film dari berbagai negara. Metode penelitian kuantitatif, sampel sebesar 107 responden dengan menggunakan purposive sampling pengguna netflix. Data penilitian ini adalah data primer yang dikumpulkan menggunakan cara penyebaran kuesioner ke yang berlangganan netflix, berusia minimal 18-35 tahun. Pengujian hipotesis dilakukan dengan menggunakan metode analisis data Partial Least Square (PLS). Hasil penelitian menunjukan Bauran Promosi berdampak positif dan signifikan terhadap Minat Beli berlangganan Netflix. Brand Image berdampak positif dan sinifikan terhadap Minat Beli berlangganan Netflix. Kata kunci : Bauran Promosi, Brand Image, Minat Bel

Statistical Significance of the Netflix Challenge

Inspired by the legacy of the Netflix contest, we provide an overview of what has been learned---from our own efforts, and those of others---concerning the problems of collaborative filtering and recommender systems. The data set consists of about 100 million movie ratings (from 1 to 5 stars) involving some 480 thousand users and some 18 thousand movies; the associated ratings matrix is about 99% sparse. The goal is to predict ratings that users will give to movies; systems which can do this accurately have significant commercial applications, particularly on the world wide web. We discuss, in some detail, approaches to "baseline" modeling, singular value decomposition (SVD), as well as kNN (nearest neighbor) and neural network models; temporal effects, cross-validation issues, ensemble methods and other considerations are discussed as well. We compare existing models in a search for new models, and also discuss the mission-critical issues of penalization and parameter shrinkage which arise when the dimensions of a parameter space reaches into the millions. Although much work on such problems has been carried out by the computer science and machine learning communities, our goal here is to address a statistical audience, and to provide a primarily statistical treatment of the lessons that have been learned from this remarkable set of data.Comment: Published in at http://dx.doi.org/10.1214/11-STS368 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Penelitian Analisa Strategi Terhadap Netflix

Netflix merupakan layanan streaming digital yang sangat dikenal oleh kalangan manapun di zaman sekarang, dengan 200 juta pelanggan dan tersebar di berbagai negara di seluruh dunia Netflix menawarkan film ataupun serial telivisi yang bisa dinikmati kapan saja dan dimana saja. Penelitian ini bertujuan untuk menggunakan sistem ERP pada Netflix serta mempertimbangkan proses bisnis dalam bentuk flow chart. Penelitian melakukan pendekatan dengan menggunakan pendekatan kualitatif dengan jenis pendekatan deskriptif kualitatif. Berdasarkan hasil penelitian menunjukkan bahwa dalam menerapkan sistem ERP pada Netflix, Suplly Chain Management, Human Resource, Accounting and Finance, dan Sales/Marketing menjadi faktor yang penting dalam kesuksesan bisnis perusahaan Netflix, dengan adanya dukungan dari sistem ERP yang diterapkan akan meningkatkan efektifitas dalam kinerja perusahaan Netflix. Sistem ERP dan dunia bisnis tidak dapat dipisahkan, karena sistem ERP akan mendukung dan membantu kegiatan operasional dalam rangka meningkatkan efisiensi dan efektif, yang akhirnya memberikan keuntungan bagi perusahaan.Penelitian ini bertujuan untuk menggunakan sistem ERP pada Netflix serta mempertimbangkan proses bisnis dalam bentuk flow chart. Tim penulis melakukan pendekatan dengan menggunakan pendekatan kualitatif dengan jenis pendekatan deskriptif kualitatif. Berdasarkan hasil penelitian menunjukkan bahwa dalam menerapkan sistem ERP pada Netflix, Suplly Chain Management, Human Resource, Accounting and Finance, dan Sales/Marketing menjadi faktor yang penting dalam kesuksesan bisnis perusahaan Netflix, dengan adanya dukungan dari sistem ERP yang diterapkan akan meningkatkan efektifitas dalam kinerja perusahaan Netflix

Analisis Harga Pada Minat Konsumen Dalam Berlangganan Netflix Pasca Pandemi

Pandemi COVID-19 merupakan bencana yang membawa banyak perubahan yang tidak terbayangkan sebelumnya. Tidak terkecuali industri perfilman dunia yang membuat masyarakat mencari alternatif hiburan yaitu dengan menonton film atau serial melalui layanan streaming yang mudah untuk diakses. Platform layanan streaming video mendunia adalah Netflix. Konsumen dapat membeli paket langganan untuk menikmati fasilitas video yang disediakan Harga berlangganan Netflix relatif lebih tinggi dibandingkan perusahaan jasa sejenis. Netflix mengalami penurunan jumlah pelanggan yang disebabkan oleh harga paket langganan yang dirasa sangat memberatkan konsumen. Namun Netflix tetap menjadi layanan streaming video paling populer di dunia. Metode penelitian ini menggunakan metode kualitatif dengan menggunakan studi literatur. Tujuan penelitian ini untuk menganalisis pengaruh harga dengan minat konsumen berlangganan Netflix dan menganalisis faktor-faktor yang dapat memengaruhi minat konsumen dalam berlangganan Netflix. Hasil penelitian ini menunjukkan bahwa harga memiliki pengaruh dengan minat konsumen dalam berlangganan Netflix Pasca Pandemi selain itu ada lima faktor yang dapat mempengaruhi minat konsumen dalam berlangganan netflix yaitu, perbedaan pekerjaan, perbedaan sosial ekonomi, perbedaan hobi dan kegemaran, perbedaan jenis kelamin dan perbedaan usia yang perlu untuk dipenuhi