Side-channel timing attack on content privacy of named data networking

Tese de Doutoramento em Engenharia Electrónica e de ComputadoresA diversity of current applications, such as Netflix, YouTube, and social media, have used the Internet mainly as a content distribution network. Named Data Networking (NDN) is a network paradigm that attempts to answer today’s applications need by naming the content. NDN promises an optimized content distribution through a named content-centric design. One of the NDN key features is the use of in-network caching to improve network efficiency in terms of content distribution. However, the cached contents may put the consumer privacy at risk. Since the time response of cached contents is different from un-cached contents, the adversary may distinguish the cached contents (targets) from un-cached ones, through the side-channel timing responses. The scope of attack can be towards the content, the name, or the signature. For instance, the adversary may obtain the call history, the callee or caller location on a trusted Voice over NDN (VoNDN) and the popularity of contents in streaming applications (e.g. NDNtube, NDNlive) through side-channel timing responses of the cache. The side-channel timing attack can be mitigated by manipulating the time of the router responses. The countermeasures proposed by other researches, such as additional delay, random/probabilistic caching, group signatures, and no-caching can effectively be used to mitigate the attack. However, the content distribution may be affected by pre-configured countermeasures which may go against the goal of the original NDN paradigm. In this work, the detection and defense (DaD) approach is proposed to mitigate the attack efficiently and effectively. With the DaD usage, an attack can be detected by a multi-level detection mechanism, in order to apply the countermeasures against the adversarial faces. Also, the detections can be used to determine the severity of the attack. In order to detect the behavior of an adversary, a brute-force timing attack was implemented and simulated with the following applications and testbeds: i. a trusted application that mimics the VoNDN and identifies the cached certificate on a worldwide NDN testbed, and ii. a streaming-like NDNtube application to identify the popularity of videos on the NDN testbed and AT&T company. In simulation primary results showed that the multi-level detection based on DaD mitigated the attack about 39.1% in best-route, and 36.6% in multicast communications. Additionally, the results showed that DaD preserves privacy without compromising the efficiency benefits of in-network caching in NDNtube and VoNDN applications.Várias aplicações atuais, como o Netflix e o YouTube, têm vindo a usar a Internet como uma rede de distribuição de conteúdos. O Named Data Networking (NDN) é um paradigma recente nas redes de comunicações que tenta responder às necessidades das aplicações modernas, através da nomeação dos conteúdos. O NDN promete uma otimização da distribuição dos conteúdos usando uma rede centrada nos conteúdos. Uma das características principais do NDN é o uso da cache disponivel nos nós da rede para melhorar a eficiência desta em termos de distribuição de conteúdos. No entanto, a colocação dos conteúdos em cache pode colocar em risco a privacidade dos consumidores. Uma vez que a resposta temporal de um conteúdo em cache é diferente do de um conteúdo que não está em cache, o adversário pode distinguir os conteúdos que estão em cache dos que não estão em cache, através das respostas de side-channel. O objectivo do ataque pode ser direcionado para o conteúdo, o nome ou a assinatura da mensagem. Por exemplo, o adversário pode obter o histórico de chamadas, a localização do callee ou do caller num serviço seguro de voz sobre NDN (VoNDN) e a popularidade do conteúdos em aplicações de streaming (e.g. NDNtube, NDNlive) através das respostas temporais de side-channel. O side-channel timing attack pode ser mitigado manipulando o tempo das respostas dos routers. As contramedidas propostas por outros pesquisadores, tais como o atraso adicional, o cache aleatório /probabilístico, as assinaturas de grupo e não fazer cache, podem ser efetivamente usadas para mitigar um ataque. No entanto, a distribuição de conteúdos pode ser afetada por contramedidas pré-configuradas que podem ir contra o propósito original do paradigma NDN. Neste trabalho, a abordagem de detecção e defesa (DaD) é proposta para mitigar o ataque de forma eficiente e eficaz. Com o uso do DaD, um ataque pode ser detectado por um mecanismo de detecção multi-nível, a fim de aplicar as contramedidas contra as interfaces dos adversários. Além disso, as detecções podem ser usadas para determinar a gravidade do ataque. A fim de detectar o comportamento de um adversário, um timing attack de força-bruta foi implementado e simulado com as seguintes aplicações e plataformas (testbeds): i. uma aplicação segura que implementa o VoNDN e identifica o certificado em cache numa plataforma NDN mundial; e ii. uma aplicação de streaming do tipo NDNtube para identificar a popularidade de vídeos na plataforma NDN da empresa AT&T. Os resultados da simulação mostraram que a detecção multi-nível oferecida pelo DaD atenuou o ataque cerca de 39,1% em best-route e 36,5% em comunicações multicast. Para avaliar o efeito nos pedidos legítimos, comparou-se o DaD com uma contramedida estática, tendo-se verificado que o DaD foi capaz de preservar todos os pedidos legítimos

A countermeasure approach for brute-force timing attacks on cache privacy in named data networking architectures

One key feature of named data networks (NDN) is supporting in-network caching to increase the content distribution for today’s Internet needs. However, previously cached contents may be threatened by side-channel timing measurements/attacks. For example, one adversary can identify previously cached contents by distinguishing between uncached and cached contents from the in-network caching node, namely the edge NDN router. The attacks can be mitigated by the previously proposed methods effectively. However, these countermeasures may be against the NDN paradigm, affecting the content distribution performance. This work studied the side-channel timing attack on streaming over NDN applications and proposed a capable approach to mitigate it. Firstly, a recent side-channel timing attack, designated by brute-force, was implemented on ndnSIM using the AT&T network topology. Then, a multi-level countermeasure method, designated by detection and defense (DaD), is proposed to mitigate this attack. Simulation results showed that DaD distinguishes between legitimate and adversary nodes. During the attack, the proposed DaD multi-level approach achieved the minimum cache hit ratio (≈0.7%) compared to traditional countermeasures (≈4.1% in probabilistic and ≈3.7% in freshness) without compromising legitimate requests.This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Public key certificate privacy in VoNDN: voice over named data networks

Scenarios were scripted by the C++11 library in ndnSIM 2.6. The scenario implementations and required tools can be publicly accessible at the author’s GitHub account—https://git.io/JJqEwNamed Data Network (NDN) is a network paradigm that attempts to answer today's needs for distribution. One of the NDN key features is in-network caching to increase content distribution and network efficiency. However, this feature may increase the privacy concerns, as the adversary may identify the call history, and the callee/caller location through side-channel timing responses from the cache of trusted Voice over NDN (VoNDN) application routers. The side-channel timing attack can be mitigated by countermeasures, such as additional unpredictable delay, random caching, group signatures, and no-caching configurations. However, the content distribution may be affected by pre-configured countermeasures, which may be against the original purpose of NDN. In this work, the detection and defense (DaD) approach is proposed to mitigate the attack efficiently and effectively. With the DaD usage, an attack can be detected by a multi-level detection mechanism, in order to apply the countermeasures against the adversarial faces. Also, the detections can be used to determine the severity of the attack. In order to detect the behavior of an adversary, a brute-force timing attack was implemented and simulated of the VoNDN application on NDN-testbed. A trusted application that mimics the VoNDN and identifies the cached certificate on a worldwide NDN-testbed. In simulation primary results showed that the multi-level detection based on DaD mitigated the attack about 39.1% in best-route, and 36.5% in multicast communications. Additionally, the results showed that DaD preserves privacy without compromising the efficiency benefits of in-network caching in the VoNDN application.This work was supported by the Fundacao para a Ciencia e Tecnologia (FCT) within the Research and Development Units Project Scope under Grant UIDB/00319/2020

A Countermeasure Approach for Brute-Force Timing Attacks on Cache Privacy in Named Data Networking Architectures

One key feature of named data networks (NDN) is supporting in-network caching to increase the content distribution for today’s Internet needs. However, previously cached contents may be threatened by side-channel timing measurements/attacks. For example, one adversary can identify previously cached contents by distinguishing between uncached and cached contents from the in-network caching node, namely the edge NDN router. The attacks can be mitigated by the previously proposed methods effectively. However, these countermeasures may be against the NDN paradigm, affecting the content distribution performance. This work studied the side-channel timing attack on streaming over NDN applications and proposed a capable approach to mitigate it. Firstly, a recent side-channel timing attack, designated by brute-force, was implemented on ndnSIM using the AT&T network topology. Then, a multi-level countermeasure method, designated by detection and defense (DaD), is proposed to mitigate this attack. Simulation results showed that DaD distinguishes between legitimate and adversary nodes. During the attack, the proposed DaD multi-level approach achieved the minimum cache hit ratio (≈0.7%) compared to traditional countermeasures (≈4.1% in probabilistic and ≈3.7% in freshness) without compromising legitimate requests

Evaluating privacy attacks in named data network

The main usage pattern of the Internet is changing from end-to-end communication to content distribution and access. To support this change, the actual Internet has several add-on as Content Delivery Networks (CDNs) and Web caches.To have a native support architecture for content distribution, clean state information-centric networking is being proposed for Future Internet. The Named Data Network (NDN) is one of the most promising information-centric networking architecture. The in-network storage (aka caches) capability of ICNs and content name visibility bring more efficiency and lower traffic to the network for content distribution.However, the human-readable naming and in-network storage of data increase the opportunity and possible victims of cache privacy attacks. The most used attack type is called timing attack.Based on the hypothesis that almost all timing attacks are detectable, this work proposes a mechanism for turning on a random cache delay model only when a cache privacy attack is detected. Otherwise, there is not any additional delay. The rationale of this approach is to establish a tradeoff between the network efficiency and cache privacy guarantee. In comparison with other works proposed in the literature, the network efficiency is less affected.info:eu-repo/semantics/publishedVersio

A detection and defense approach for content privacy in named data network

The Named Data Network (NDN) is a promising network paradigm for content distribution based on caching. However, it may put consumer privacy at risk, as the adversary may identify the content, the name and the signature (namely a certificate) through side-channel timing responses from the cache of the routers. The adversary may identify the content name and the consumer node by distinguishing between cached and uncached contents. In order to mitigate the timing attack, effective countermeasure methods have been proposed by other authors, such as random caching, random freshness, and probabilistic caching. In this work, we have implemented a timing attack scenario to evaluate the efficiency of these countermeasures and to demonstrate how the adversary can be detected. For this goal, a brute force timing attack scenario based on a real topology was developed, which is the first brute force attack model applied in NDN. Results show that the adversary nodes can be effectively distinguished from other legitimate consumers during the attack period. It is also proposed a multi-level mechanism to detect an adversary node. Through this approach, the content distribution performance can be mitigated against the attack.This work has been supported by FCT -Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/201

Persistence Landscapes—Implementing a Dataset Verification Method in Resource-Scarce Embedded Systems

As more and more devices are being deployed across networks to gather data and use them to perform intelligent tasks, it is vital to have a tool to perform real-time data analysis. Data are the backbone of Machine Learning models, the core of intelligent systems. Therefore, verifying whether the data being gathered are similar to those used for model building is essential. One fantastic tool for the performance of data analysis is the 0-Dimensional Persistent Diagrams, which can be computed in a Resource-Scarce Embedded System (RSES), a set of memory and processing-constrained devices that are used in many IoT applications because they are cost-effective and reliable. However, it is challenging to compare Persistent Diagrams, and Persistent Landscapes are used because they allow Persistent Diagrams to be passed to a space where the mean concept is well-defined. The following work shows how one can perform a Persistent Landscape analysis in an RSES. It also shows that the distance between two Persistent Landscapes makes it possible to verify whether two devices collect the same data. The main contribution of this work is the implementation of Persistent Landscape analysis in an RSES, which is not provided in the literature. Moreover, it shows that devices can now verify, in real-time, whether they can trust the data being collected to perform the intelligent task they were designed to, which is essential in any system to avoid bugs or errors