1,983 research outputs found

    Interest-Based Access Control for Content Centric Networks (extended version)

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    Content-Centric Networking (CCN) is an emerging network architecture designed to overcome limitations of the current IP-based Internet. One of the fundamental tenets of CCN is that data, or content, is a named and addressable entity in the network. Consumers request content by issuing interest messages with the desired content name. These interests are forwarded by routers to producers, and the resulting content object is returned and optionally cached at each router along the path. In-network caching makes it difficult to enforce access control policies on sensitive content outside of the producer since routers only use interest information for forwarding decisions. To that end, we propose an Interest-Based Access Control (IBAC) scheme that enables access control enforcement using only information contained in interest messages, i.e., by making sensitive content names unpredictable to unauthorized parties. Our IBAC scheme supports both hash- and encryption-based name obfuscation. We address the problem of interest replay attacks by formulating a mutual trust framework between producers and consumers that enables routers to perform authorization checks when satisfying interests from their cache. We assess the computational, storage, and bandwidth overhead of each IBAC variant. Our design is flexible and allows producers to arbitrarily specify and enforce any type of access control on content, without having to deal with the problems of content encryption and key distribution. This is the first comprehensive design for CCN access control using only information contained in interest messages.Comment: 11 pages, 2 figure

    To NACK or not to NACK? Negative Acknowledgments in Information-Centric Networking

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    Information-Centric Networking (ICN) is an internetworking paradigm that offers an alternative to the current IP\nobreakdash-based Internet architecture. ICN's most distinguishing feature is its emphasis on information (content) instead of communication endpoints. One important open issue in ICN is whether negative acknowledgments (NACKs) at the network layer are useful for notifying downstream nodes about forwarding failures, or requests for incorrect or non-existent information. In benign settings, NACKs are beneficial for ICN architectures, such as CCNx and NDN, since they flush state in routers and notify consumers. In terms of security, NACKs seem useful as they can help mitigating so-called Interest Flooding attacks. However, as we show in this paper, network-layer NACKs also have some unpleasant security implications. We consider several types of NACKs and discuss their security design requirements and implications. We also demonstrate that providing secure NACKs triggers the threat of producer-bound flooding attacks. Although we discuss some potential countermeasures to these attacks, the main conclusion of this paper is that network-layer NACKs are best avoided, at least for security reasons.Comment: 10 pages, 7 figure

    Poseidon: Mitigating Interest Flooding DDoS Attacks in Named Data Networking

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    Content-Centric Networking (CCN) is an emerging networking paradigm being considered as a possible replacement for the current IP-based host-centric Internet infrastructure. In CCN, named content becomes a first-class entity. CCN focuses on content distribution, which dominates current Internet traffic and is arguably not well served by IP. Named-Data Networking (NDN) is an example of CCN. NDN is also an active research project under the NSF Future Internet Architectures (FIA) program. FIA emphasizes security and privacy from the outset and by design. To be a viable Internet architecture, NDN must be resilient against current and emerging threats. This paper focuses on distributed denial-of-service (DDoS) attacks; in particular we address interest flooding, an attack that exploits key architectural features of NDN. We show that an adversary with limited resources can implement such attack, having a significant impact on network performance. We then introduce Poseidon: a framework for detecting and mitigating interest flooding attacks. Finally, we report on results of extensive simulations assessing proposed countermeasure.Comment: The IEEE Conference on Local Computer Networks (LCN 2013

    Interest Flooding Attack in Named Data Networking: A Survey

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    Named Data Networking (NDN) is based on the principle of Content-Centric Networking (CCN) that aims to overcome the weaknesses of the current host-based Internet architecture. Like traditional networks, it is identified that NDN is also vulnerable to many security threats including denial-of-service (DoS) or distributed DoS (DDoS) and might offer avenues for new DoS/DDoS attacks. DDoS attacks can be triggered in NDN to exhaust resources within an NDN router or the content producer(s). This survey paper focuses on different types of possible distributed denial-ofservice (DDoS) attacks; in particular, we address Interest flooding, where an adversary with limited resources can implement this attack and significantly impact thenetwork performance and their proposed countermeasures.Keywords:Named Data Networking, Interest flooding, denial-of-service

    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
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