Framework for privacy-aware content distribution in peer-to- peer networks with copyright protection

The use of peer-to-peer (P2P) networks for multimedia distribution has spread out globally in recent years. This mass popularity is primarily driven by the efficient distribution of content, also giving rise to piracy and copyright infringement as well as privacy concerns. An end user (buyer) of a P2P content distribution system does not want to reveal his/her identity during a transaction with a content owner (merchant), whereas the merchant does not want the buyer to further redistribute the content illegally. Therefore, there is a strong need for content distribution mechanisms over P2P networks that do not pose security and privacy threats to copyright holders and end users, respectively. However, the current systems being developed to provide copyright and privacy protection to merchants and end users employ cryptographic mechanisms, which incur high computational and communication costs, making these systems impractical for the distribution of big files, such as music albums or movies.El uso de soluciones de igual a igual (peer-to-peer, P2P) para la distribución multimedia se ha extendido mundialmente en los últimos años. La amplia popularidad de este paradigma se debe, principalmente, a la distribución eficiente de los contenidos, pero también da lugar a la piratería, a la violación del copyright y a problemas de privacidad. Un usuario final (comprador) de un sistema de distribución de contenidos P2P no quiere revelar su identidad durante una transacción con un propietario de contenidos (comerciante), mientras que el comerciante no quiere que el comprador pueda redistribuir ilegalmente el contenido más adelante. Por lo tanto, existe una fuerte necesidad de mecanismos de distribución de contenidos por medio de redes P2P que no supongan un riesgo de seguridad y privacidad a los titulares de derechos y los usuarios finales, respectivamente. Sin embargo, los sistemas actuales que se desarrollan con el propósito de proteger el copyright y la privacidad de los comerciantes y los usuarios finales emplean mecanismos de cifrado que implican unas cargas computacionales y de comunicaciones muy elevadas que convierten a estos sistemas en poco prácticos para distribuir archivos de gran tamaño, tales como álbumes de música o películas.L'ús de solucions d'igual a igual (peer-to-peer, P2P) per a la distribució multimèdia s'ha estès mundialment els darrers anys. L'àmplia popularitat d'aquest paradigma es deu, principalment, a la distribució eficient dels continguts, però també dóna lloc a la pirateria, a la violació del copyright i a problemes de privadesa. Un usuari final (comprador) d'un sistema de distribució de continguts P2P no vol revelar la seva identitat durant una transacció amb un propietari de continguts (comerciant), mentre que el comerciant no vol que el comprador pugui redistribuir il·legalment el contingut més endavant. Per tant, hi ha una gran necessitat de mecanismes de distribució de continguts per mitjà de xarxes P2P que no comportin un risc de seguretat i privadesa als titulars de drets i els usuaris finals, respectivament. Tanmateix, els sistemes actuals que es desenvolupen amb el propòsit de protegir el copyright i la privadesa dels comerciants i els usuaris finals fan servir mecanismes d'encriptació que impliquen unes càrregues computacionals i de comunicacions molt elevades que fan aquests sistemes poc pràctics per a distribuir arxius de grans dimensions, com ara àlbums de música o pel·lícules

Contribution to the construction of fingerprinting and watermarking schemes to protect mobile agents and multimedia content

The main characteristic of fingerprinting codes is the need of high error-correction capacity due to the fact that they are designed to avoid collusion attacks which will damage many symbols from the codewords. Moreover, the use of fingerprinting schemes depends on the watermarking system that is used to embed the codeword into the content and how it honors the marking assumption. In this sense, even though fingerprinting codes were mainly used to protect multimedia content, using them on software protection systems seems an option to be considered. This thesis, studies how to use codes which have iterative-decoding algorithms, mainly turbo-codes, to solve the fingerprinting problem. Initially, it studies the effectiveness of current approaches based on concatenating tradicioanal fingerprinting schemes with convolutional codes and turbo-codes. It is shown that these kind of constructions ends up generating a high number of false positives. Even though this thesis contains some proposals to improve these schemes, the direct use of turbo-codes without using any concatenation with a fingerprinting code as inner code has also been considered. It is shown that the performance of turbo-codes using the appropiate constituent codes is a valid alternative for environments with hundreds of users and 2 or 3 traitors. As constituent codes, we have chosen low-rate convolutional codes with maximum free distance. As for how to use fingerprinting codes with watermarking schemes, we have studied the option of using watermarking systems based on informed coding and informed embedding. It has been discovered that, due to different encodings available for the same symbol, its applicability to embed fingerprints is very limited. On this sense, some modifications to these systems have been proposed in order to properly adapt them to fingerprinting applications. Moreover the behavior and impact over a video produced as a collusion of 2 users by the YouTube’s s ervice has been s tudied. We have also studied the optimal parameters for viable tracking of users who have used YouTube and conspired to redistribute copies generated by a collusion attack. Finally, we have studied how to implement fingerprinting schemes and software watermarking to fix the problem of malicious hosts on mobile agents platforms. In this regard, four different alternatives have been proposed to protect the agent depending on whether you want only detect the attack or avoid it in real time. Two of these proposals are focused on the protection of intrusion detection systems based on mobile agents. Moreover, each of these solutions has several implications in terms of infrastructure and complexity.Els codis fingerprinting es caracteritzen per proveir una alta capacitat correctora ja que han de fer front a atacs de confabulació que malmetran una part important dels símbols de la paraula codi. D'atra banda, la utilització de codis de fingerprinting en entorns reals està subjecta a que l'esquema de watermarking que gestiona la incrustació sigui respectuosa amb la marking assumption. De la mateixa manera, tot i que el fingerprinting neix de la protecció de contingut multimèdia, utilitzar-lo en la protecció de software comença a ser una aplicació a avaluar. En aquesta tesi s'ha estudiat com aplicar codis amb des codificació iterativa, concretament turbo-codis, al problema del rastreig de traïdors en el context del fingerprinting digital. Inicialment s'ha qüestionat l'eficàcia dels enfocaments actuals en la utilització de codis convolucionals i turbo-codis que plantegen concatenacions amb esquemes habituals de fingerprinting. S'ha demostrat que aquest tipus de concatenacions portaven, de forma implícita, a una elevada probabilitat d'inculpar un usuari innocent. Tot i que s'han proposat algunes millores sobre aquests esquemes , finalment s'ha plantejat l'ús de turbocodis directament, evitant així la concatenació amb altres esquemes de fingerprinting. S'ha demostrat que, si s'utilitzen els codis constituents apropiats, el rendiment del turbo-descodificador és suficient per a ser una alternativa aplicable en entorns amb varis centenars d'usuaris i 2 o 3 confabuladors . Com a codis constituents s'ha optat pels codis convolucionals de baix ràtio amb distància lliure màxima. Pel que fa a com utilitzar els codis de fingerprinting amb esquemes de watermarking, s'ha estudiat l'opció d'utilitzar sistemes de watermarking basats en la codificació i la incrustació informada. S'ha comprovat que, degut a la múltiple codificació del mateix símbol, la seva aplicabilitat per incrustar fingerprints és molt limitada. En aquest sentit s'ha plantejat algunes modificacions d'aquests sistemes per tal d'adaptar-los correctament a aplicacions de fingerprinting. D'altra banda s'ha avaluat el comportament i l'impacte que el servei de YouTube produeix sobre un vídeo amb un fingerprint incrustat. A més , s'ha estudiat els paràmetres òptims per a fer viable el rastreig d'usuaris que han confabulat i han utilitzat YouTube per a redistribuir la copia fruït de la seva confabulació. Finalment, s'ha estudiat com aplicar els esquemes de fingerprinting i watermarking de software per solucionar el problema de l'amfitrió maliciós en agents mòbils . En aquest sentit s'han proposat quatre alternatives diferents per a protegir l'agent en funció de si és vol només detectar l'atac o evitar-lo en temps real. Dues d'aquestes propostes es centren en la protecció de sistemes de detecció d'intrusions basats en agents mòbils. Cadascuna de les solucions té diverses implicacions a nivell d'infrastructura i de complexitat.Postprint (published version

Multimedia

The nowadays ubiquitous and effortless digital data capture and processing capabilities offered by the majority of devices, lead to an unprecedented penetration of multimedia content in our everyday life. To make the most of this phenomenon, the rapidly increasing volume and usage of digitised content requires constant re-evaluation and adaptation of multimedia methodologies, in order to meet the relentless change of requirements from both the user and system perspectives. Advances in Multimedia provides readers with an overview of the ever-growing field of multimedia by bringing together various research studies and surveys from different subfields that point out such important aspects. Some of the main topics that this book deals with include: multimedia management in peer-to-peer structures & wireless networks, security characteristics in multimedia, semantic gap bridging for multimedia content and novel multimedia applications

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

The use of wavelet watermarking and statistical classification techniques for collusion detection and identification in multimedia forensics

This research proposes a wavelet-based multimedia fingerprint scheme and statistical clustering algorithm for collusion detection and identification. The use of digital multimedia has steadily increased using mediums like the Internet. Encryption is generally used to safeguard content while in transmission, but offers no protection against duplication. Tracing unauthorized content distributors has become an increasing concern for the media industry. Unauthorized duplication, piracy, and illegal redistribution of multimedia content account for several billion dollars in losses every year. It is important to design reliable investigative techniques against unauthorized duplication and propagation, and provide protection in the form of theft deterrence. Some fingerprint embedding schemes are robust against single-user modification attacks. However, a new breed of attacks, known as collusion attacks, have been used to defeat those underlying schemes. These attacks use the combination of multiple fingerprinted copies to create a new version where the underlying fingerprint is highly attenuated, becoming untraceable to the colluders. This research adopts the use of wavelet transforms and statistical classification techniques to effectively identify the set of colluders involved in a collusion attack while maintaining low miss rates and false accusation rates. The experimental results show that the solution is effective in identifying large colluder sets without the knowledge of the number of colluders involved in an attack and the collusion attack used

Neyman-Pearson Decision in Traffic Analysis

The increase of encrypted traffic on the Internet may become a problem for network-security applications such as intrusion-detection systems or interfere with forensic investigations. This fact has increased the awareness for traffic analysis, i.e., inferring information from communication patterns instead of its content. Deciding correctly that a known network flow is either the same or part of an observed one can be extremely useful for several network-security applications such as intrusion detection and tracing anonymous connections. In many cases, the flows of interest are relayed through many nodes that reencrypt the flow, making traffic analysis the only possible solution. There exist two well-known techniques to solve this problem: passive traffic analysis and flow watermarking. The former is undetectable but in general has a much worse performance than watermarking, whereas the latter can be detected and modified in such a way that the watermark is destroyed. In the first part of this dissertation we design techniques where the traffic analyst (TA) is one end of an anonymous communication and wants to deanonymize the other host, under this premise that the arrival time of the TA\u27s packets/requests can be predicted with high confidence. This, together with the use of an optimal detector, based on Neyman-Pearson lemma, allow the TA deanonymize the other host with high confidence even with short flows. We start by studying the forensic problem of leaving identifiable traces on the log of a Tor\u27s hidden service, in this case the used predictor comes in the HTTP header. Afterwards, we propose two different methods for locating Tor hidden services, the first one is based on the arrival time of the request cell and the second one uses the number of cells in certain time intervals. In both of these methods, the predictor is based on the round-trip time and in some cases in the position inside its burst, hence this method does not need the TA to have access to the decrypted flow. The second part of this dissertation deals with scenarios where an accurate predictor is not feasible for the TA. This traffic analysis technique is based on correlating the inter-packet delays (IPDs) using a Neyman-Pearson detector. Our method can be used as a passive analysis or as a watermarking technique. This algorithm is first made robust against adversary models that add chaff traffic, split the flows or add random delays. Afterwards, we study this scenario from a game-theoretic point of view, analyzing two different games: the first deals with the identification of independent flows, while the second one decides whether a flow has been watermarked/fingerprinted or not

Location reliability and gamification mechanisms for mobile crowd sensing

People-centric sensing with smart phones can be used for large scale sensing of the physical world by leveraging the sensors on the phones. This new type of sensing can be a scalable and cost-effective alternative to deploying static wireless sensor networks for dense sensing coverage across large areas. However, mobile people-centric sensing has two main issues: 1) Data reliability in sensed data and 2) Incentives for participants. To study these issues, this dissertation designs and develops McSense, a mobile crowd sensing system which provides monetary and social incentives to users. This dissertation proposes and evaluates two protocols for location reliability as a step toward achieving data reliability in sensed data, namely, ILR (Improving Location Reliability) and LINK (Location authentication through Immediate Neighbors Knowledge). ILR is a scheme which improves the location reliability of mobile crowd sensed data with minimal human efforts based on location validation using photo tasks and expanding the trust to nearby data points using periodic Bluetooth scanning. LINK is a location authentication protocol working independent of wireless carriers, in which nearby users help authenticate each other’s location claims using Bluetooth communication. The results of experiments done on Android phones show that the proposed protocols are capable of detecting a significant percentage of the malicious users claiming false location. Furthermore, simulations with the LINK protocol demonstrate that LINK can effectively thwart a number of colluding user attacks. This dissertation also proposes a mobile sensing game which helps collect crowd sensing data by incentivizing smart phone users to play sensing games on their phones. We design and implement a first person shooter sensing game, “Alien vs. Mobile User”, which employs techniques to attract users to unpopular regions. The user study results show that mobile gaming can be a successful alternative to micro-payments for fast and efficient area coverage in crowd sensing. It is observed that the proposed game design succeeds in achieving good player engagement

Digital Watermarking for Verification of Perception-based Integrity of Audio Data

In certain application fields digital audio recordings contain sensitive content. Examples are historical archival material in public archives that preserve our cultural heritage, or digital evidence in the context of law enforcement and civil proceedings. Because of the powerful capabilities of modern editing tools for multimedia such material is vulnerable to doctoring of the content and forgery of its origin with malicious intent. Also inadvertent data modification and mistaken origin can be caused by human error. Hence, the credibility and provenience in terms of an unadulterated and genuine state of such audio content and the confidence about its origin are critical factors. To address this issue, this PhD thesis proposes a mechanism for verifying the integrity and authenticity of digital sound recordings. It is designed and implemented to be insensitive to common post-processing operations of the audio data that influence the subjective acoustic perception only marginally (if at all). Examples of such operations include lossy compression that maintains a high sound quality of the audio media, or lossless format conversions. It is the objective to avoid de facto false alarms that would be expectedly observable in standard crypto-based authentication protocols in the presence of these legitimate post-processing. For achieving this, a feasible combination of the techniques of digital watermarking and audio-specific hashing is investigated. At first, a suitable secret-key dependent audio hashing algorithm is developed. It incorporates and enhances so-called audio fingerprinting technology from the state of the art in contentbased audio identification. The presented algorithm (denoted as ”rMAC” message authentication code) allows ”perception-based” verification of integrity. This means classifying integrity breaches as such not before they become audible. As another objective, this rMAC is embedded and stored silently inside the audio media by means of audio watermarking technology. This approach allows maintaining the authentication code across the above-mentioned admissible post-processing operations and making it available for integrity verification at a later date. For this, an existent secret-key ependent audio watermarking algorithm is used and enhanced in this thesis work. To some extent, the dependency of the rMAC and of the watermarking processing from a secret key also allows authenticating the origin of a protected audio. To elaborate on this security aspect, this work also estimates the brute-force efforts of an adversary attacking this combined rMAC-watermarking approach. The experimental results show that the proposed method provides a good distinction and classification performance of authentic versus doctored audio content. It also allows the temporal localization of audible data modification within a protected audio file. The experimental evaluation finally provides recommendations about technical configuration settings of the combined watermarking-hashing approach. Beyond the main topic of perception-based data integrity and data authenticity for audio, this PhD work provides new general findings in the fields of audio fingerprinting and digital watermarking. The main contributions of this PhD were published and presented mainly at conferences about multimedia security. These publications were cited by a number of other authors and hence had some impact on their works

Traffic Monitoring and analysis for source identification

Ph.DDOCTOR OF PHILOSOPH

TOWARDS RELIABLE CIRCUMVENTION OF INTERNET CENSORSHIP

The Internet plays a crucial role in today\u27s social and political movements by facilitating the free circulation of speech, information, and ideas; democracy and human rights throughout the world critically depend on preserving and bolstering the Internet\u27s openness. Consequently, repressive regimes, totalitarian governments, and corrupt corporations regulate, monitor, and restrict the access to the Internet, which is broadly known as Internet \emph{censorship}. Most countries are improving the internet infrastructures, as a result they can implement more advanced censoring techniques. Also with the advancements in the application of machine learning techniques for network traffic analysis have enabled the more sophisticated Internet censorship. In this thesis, We take a close look at the main pillars of internet censorship, we will introduce new defense and attacks in the internet censorship literature. Internet censorship techniques investigate users’ communications and they can decide to interrupt a connection to prevent a user from communicating with a specific entity. Traffic analysis is one of the main techniques used to infer information from internet communications. One of the major challenges to traffic analysis mechanisms is scaling the techniques to today\u27s exploding volumes of network traffic, i.e., they impose high storage, communications, and computation overheads. We aim at addressing this scalability issue by introducing a new direction for traffic analysis, which we call \emph{compressive traffic analysis}. Moreover, we show that, unfortunately, traffic analysis attacks can be conducted on Anonymity systems with drastically higher accuracies than before by leveraging emerging learning mechanisms. We particularly design a system, called \deepcorr, that outperforms the state-of-the-art by significant margins in correlating network connections. \deepcorr leverages an advanced deep learning architecture to \emph{learn} a flow correlation function tailored to complex networks. Also to be able to analyze the weakness of such approaches we show that an adversary can defeat deep neural network based traffic analysis techniques by applying statistically undetectable \emph{adversarial perturbations} on the patterns of live network traffic. We also design techniques to circumvent internet censorship. Decoy routing is an emerging approach for censorship circumvention in which circumvention is implemented with help from a number of volunteer Internet autonomous systems, called decoy ASes. We propose a new architecture for decoy routing that, by design, is significantly stronger to rerouting attacks compared to \emph{all} previous designs. Unlike previous designs, our new architecture operates decoy routers only on the downstream traffic of the censored users; therefore we call it \emph{downstream-only} decoy routing. As we demonstrate through Internet-scale BGP simulations, downstream-only decoy routing offers significantly stronger resistance to rerouting attacks, which is intuitively because a (censoring) ISP has much less control on the downstream BGP routes of its traffic. Then, we propose to use game theoretic approaches to model the arms races between the censors and the censorship circumvention tools. This will allow us to analyze the effect of different parameters or censoring behaviors on the performance of censorship circumvention tools. We apply our methods on two fundamental problems in internet censorship. Finally, to bring our ideas to practice, we designed a new censorship circumvention tool called \name. \name aims at increasing the collateral damage of censorship by employing a ``mass\u27\u27 of normal Internet users, from both censored and uncensored areas, to serve as circumvention proxies