169 research outputs found

    Enhancing Cache Robustness in Named Data Networks

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    Information-centric networks (ICNs) are a category of network architectures that focus on content, rather than hosts, to more effectively support the needs of today’s users. One major feature of such networks is in-network storage, which is realized by the presence of content storage routers throughout the network. These content storage routers cache popular content object chunks close to the consumers who request them in order to reduce latency for those end users and to decrease overall network congestion. Because of their prominence, network storage devices such as content storage routers will undoubtedly be major targets for malicious users. Two primary goals of attackers are to increase cache pollution and decrease hit rate by legitimate users. This would effectively reduce or eliminate the advantages of having in-network storage. Therefore, it is crucial to defend against these types of attacks. In this thesis, we study a specific ICN architecture called Named Data Networking (NDN) and simulate several attack scenarios on different network topologies to ascertain the effectiveness of different cache replacement algorithms, such as LRU and LFU (specifically, LFU-DA.) We apply our new per-face popularity with dynamic aging (PFP-DA) scheme to the content storage routers in the network and measure both cache pollution percentages as well as hit rate experienced by legitimate consumers. The current solutions in the literature that relate to reducing the effects of cache pollution largely focus on detection of attacker behavior. Since this behavior is very unpredictable, it is not guaranteed that any detection mechanisms will work well if the attackers employ smart attacks. Furthermore, current solutions do not consider the effects of a particularly aggressive attack against any single or small set of faces (interfaces.) Therefore, we have developed three related algorithms, namely PFP, PFP-DA, and Parameterized PFP-DA. PFP ensures that interests that ingress over any given face do not overwhelm the calculated popularity of a content object chunk. PFP normalizes the ranks on all faces and uses the collective contributions of these faces to determine the overall popularity, which in turn determines what content stays in the cache and what is evicted. PFP-DA adds recency to the original PFP algorithm and ensures that content object chunks do not remain in the cache longer than their true, current popularity dictates. Finally, we explore PFP-β, a parameterized version of PFP-DA, in which a β parameter is provided that causes the popularity calculations to take on Zipf-like characteristics, which in turn reduces the numeric distance between top rated items, and lower rated items, favoring items with multi-face contribution over those with single-face contributions and those with contributions over very few faces. We explore how the PFP-based schemes can reduce impact of contributions over any given face or small number of faces on an NDN content storage router. This in turn, reduces the impact that even some of the most aggressive attackers can have when they overwhelm one or a few faces, by normalizing the contributions across all contributing faces for a given content object chunk. During attack scenarios, we conclude that PFP-DA performs better than both LRU and LFU-DA in terms of resisting the effects of cache pollution and maintaining strong hit rates. We also demonstrate that PFP-DA performs better even when no attacks are being leveraged against the content store. This opens the door for further research both within and outside of ICN-based architectures as a means to enhance security and overall performance.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/145175/1/John Baugh Final Dissertation.pdfDescription of John Baugh Final Dissertation.pdf : Dissertatio

    A Targeted Denial of Service Attack on Data Caching Networks

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    With the rise of data exchange over the Internet, information-centric networks have become a popular research topic in computing. One major research topic on Information Centric Networks (ICN) is the use of data caching to increase network performance. However, research in the security concerns of data caching networks is lacking. One example of a data caching network can be seen using a Mobile Ad Hoc Network (MANET). Recently, a study has shown that it is possible to infer military activity through cache behavior which is used as a basis for a formulated denial of service attack (DoS) that can be used to attack networks using data caching. Current security issues with data caching networks are discussed, including possible prevention techniques and methods. A targeted data cache DoS attack is developed and tested using an ICN as a simulator. The goal of the attacker would be to fill node caches with unpopular content, thus making the cache useless. The attack would consist of a malicious node that requests unpopular content in intervals of time where the content would have been just purged from the existing cache. The goal of the attack would be to corrupt as many nodes as possible without increasing the chance of detection. The decreased network throughput and increased delay would also lead to higher power consumption on the mobile nodes, thus increasing the effects of the DoS attack. Various caching polices are evaluated in an ICN simulator program designed to show network performance using three common caching policies and various cache sizes. The ICN simulator is developed using Java and tested on a simulated network. Baseline data are collected and then compared to data collected after the attack. Other possible security concerns with data caching networks are also discussed, including possible smarter attack techniques and methods

    Implementation of Cache Attack on Real Information Centric Networking System

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    Network security is an ongoing major problem in today’s Internet world. Even though there have been simulation studies related to denial of service and cache attacks, studies of attacks on real networks are still lacking in the research. In this thesis, the effects of cache attacks in real information-centric networking systems were investigated. Cache attacks were implemented in real networks with different cache sizes and with Least Recently Used, Random and First In First Out algorithms to fill the caches in each node. The attacker hits the cache with unpopular content, making the user request that the results be fetched from web servers. The cache hit, time taken to get the result, and number of hops to serve the request were calculated with real network traffic. The results of the implementation are provided for different topologies and are compared with the simulation results

    Backscatter from the Data Plane --- Threats to Stability and Security in Information-Centric Networking

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    Information-centric networking proposals attract much attention in the ongoing search for a future communication paradigm of the Internet. Replacing the host-to-host connectivity by a data-oriented publish/subscribe service eases content distribution and authentication by concept, while eliminating threats from unwanted traffic at an end host as are common in today's Internet. However, current approaches to content routing heavily rely on data-driven protocol events and thereby introduce a strong coupling of the control to the data plane in the underlying routing infrastructure. In this paper, threats to the stability and security of the content distribution system are analyzed in theory and practical experiments. We derive relations between state resources and the performance of routers and demonstrate how this coupling can be misused in practice. We discuss new attack vectors present in its current state of development, as well as possibilities and limitations to mitigate them.Comment: 15 page

    ROVER: a DNS-based method to detect and prevent IP hijacks

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    2013 Fall.Includes bibliographical references.The Border Gateway Protocol (BGP) is critical to the global internet infrastructure. Unfortunately BGP routing was designed with limited regard for security. As a result, IP route hijacking has been observed for more than 16 years. Well known incidents include a 2008 hijack of YouTube, loss of connectivity for Australia in February 2012, and an event that partially crippled Google in November 2012. Concern has been escalating as critical national infrastructure is reliant on a secure foundation for the Internet. Disruptions to military, banking, utilities, industry, and commerce can be catastrophic. In this dissertation we propose ROVER (Route Origin VERification System), a novel and practical solution for detecting and preventing origin and sub-prefix hijacks. ROVER exploits the reverse DNS for storing route origin data and provides a fail-safe, best effort approach to authentication. This approach can be used with a variety of operational models including fully dynamic in-line BGP filtering, periodically updated authenticated route filters, and real-time notifications for network operators. Our thesis is that ROVER systems can be deployed by a small number of institutions in an incremental fashion and still effectively thwart origin and sub-prefix IP hijacking despite non-participation by the majority of Autonomous System owners. We then present research results supporting this statement. We evaluate the effectiveness of ROVER using simulations on an Internet scale topology as well as with tests on real operational systems. Analyses include a study of IP hijack propagation patterns, effectiveness of various deployment models, critical mass requirements, and an examination of ROVER resilience and scalability

    An ANFIS-based cache replacement method for mitigating cache pollution attacks in Named Data Networking

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    Named Data Networking (NDN) is a candidate next-generation Internet architecture designed to overcome the fundamental limitations of the current IP-based Internet, in particular strong security. The ubiquitous in-network caching is a key NDN feature. However, pervasive caching strengthens security problems namely cache pollution attacks including cache poisoning (i.e., introducing malicious content into caches as false-locality) and cache pollution (i.e., ruining the cache locality with new unpopular content as locality-disruption). In this paper, a new cache replacement method based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is presented to mitigate the cache pollution attacks in NDN. The ANFIS structure is built using the input data related to the inherent characteristics of the cached content and the output related to the content type (i.e., healthy, locality-disruption, and false-locality). The proposed method detects both false-locality and locality-disruption attacks as well as a combination of the two on different topologies with high accuracy, and mitigates them efficiently without very much computational cost as compared to the most common policies

    The use of computational intelligence for security in named data networking

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    Information-Centric Networking (ICN) has recently been considered as a promising paradigm for the next-generation Internet, shifting from the sender-driven end-to-end communication paradigma to a receiver-driven content retrieval paradigm. In ICN, content -rather than hosts, like in IP-based design- plays the central role in the communications. This change from host-centric to content-centric has several significant advantages such as network load reduction, low dissemination latency, scalability, etc. One of the main design requirements for the ICN architectures -since the beginning of their design- has been strong security. Named Data Networking (NDN) (also referred to as Content-Centric Networking (CCN) or Data-Centric Networking (DCN)) is one of these architectures that are the focus of an ongoing research effort that aims to become the way Internet will operate in the future. Existing research into security of NDN is at an early stage and many designs are still incomplete. To make NDN a fully working system at Internet scale, there are still many missing pieces to be filled in. In this dissertation, we study the four most important security issues in NDN in order to defense against new forms of -potentially unknown- attacks, ensure privacy, achieve high availability, and block malicious network traffics belonging to attackers or at least limit their effectiveness, i.e., anomaly detection, DoS/DDoS attacks, congestion control, and cache pollution attacks. In order to protect NDN infrastructure, we need flexible, adaptable and robust defense systems which can make intelligent -and real-time- decisions to enable network entities to behave in an adaptive and intelligent manner. In this context, the characteristics of Computational Intelligence (CI) methods such as adaption, fault tolerance, high computational speed and error resilient against noisy information, make them suitable to be applied to the problem of NDN security, which can highlight promising new research directions. Hence, we suggest new hybrid CI-based methods to make NDN a more reliable and viable architecture for the future Internet.Information-Centric Networking (ICN) ha sido recientemente considerado como un paradigma prometedor parala nueva generación de Internet, pasando del paradigma de la comunicación de extremo a extremo impulsada por el emisora un paradigma de obtención de contenidos impulsada por el receptor. En ICN, el contenido (más que los nodos, como sucede en redes IPactuales) juega el papel central en las comunicaciones. Este cambio de "host-centric" a "content-centric" tiene varias ventajas importantes como la reducción de la carga de red, la baja latencia, escalabilidad, etc. Uno de los principales requisitos de diseño para las arquitecturas ICN (ya desde el principiode su diseño) ha sido una fuerte seguridad. Named Data Networking (NDN) (también conocida como Content-Centric Networking (CCN) o Data-Centric Networking (DCN)) es una de estas arquitecturas que son objetode investigación y que tiene como objetivo convertirse en la forma en que Internet funcionará en el futuro. Laseguridad de NDN está aún en una etapa inicial. Para hacer NDN un sistema totalmente funcional a escala de Internet, todavía hay muchas piezas que faltan por diseñar. Enesta tesis, estudiamos los cuatro problemas de seguridad más importantes de NDN, para defendersecontra nuevas formas de ataques (incluyendo los potencialmente desconocidos), asegurar la privacidad, lograr una alta disponibilidad, y bloquear los tráficos de red maliciosos o al menos limitar su eficacia. Estos cuatro problemas son: detección de anomalías, ataques DoS / DDoS, control de congestión y ataques de contaminación caché. Para solventar tales problemas necesitamos sistemas de defensa flexibles, adaptables y robustos que puedantomar decisiones inteligentes en tiempo real para permitir a las entidades de red que se comporten de manera rápida e inteligente. Es por ello que utilizamos Inteligencia Computacional (IC), ya que sus características (la adaptación, la tolerancia a fallos, alta velocidad de cálculo y funcionamiento adecuado con información con altos niveles de ruido), la hace adecuada para ser aplicada al problema de la seguridad ND
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