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BGP prefix hijacking is a critical threat to Internet organizations and users. Despite the availability of several defense approaches (ranging from RPKI to popular third-party services), none of them solves the problem adequately in practice. In fact, they suffer from: (i) lack of detection comprehensiveness, allowing sophisticated attackers to evade detection, (ii) limited accuracy, especially in the case of third-party detection, (iii) delayed verification and mitigation of incidents, reaching up to days, and (iv) lack of privacy and of flexibility in post-hijack counteractions, on the side of network operators. In this work, we propose ARTEMIS (Automatic and Real-Time dEtection and MItigation System), a defense approach (a) based on accurate and fast detection operated by the AS itself, leveraging the pervasiveness of publicly available BGP monitoring services and their recent shift towards real-time streaming, thus (b) enabling flexible and fast mitigation of hijacking events. Compared to previous work, our approach combines characteristics desirable to network operators such as comprehensiveness, accuracy, speed, privacy, and flexibility. Finally, we show through real-world experiments that, with the ARTEMIS approach, prefix hijacking can be neutralized within a minute. ✦

Caching has been successfully applied in wired networks, in the context of Content Distribution Networks (CDNs), and is quickly gaining ground for wireless systems. Storing popular content at the edge of the network (e.g. at small cells) is seen as a "win-win" for both the user (reduced access latency) and the operator (reduced load on the transport network and core servers). Nevertheless, the much smaller size of such edge caches, and the volatility of user preferences suggest that standard caching methods do not suffice in this context. What is more, simple popularity-based models commonly used (e.g. IRM) are becoming outdated, as users often consume multiple contents in sequence (e.g. YouTube, Spotify), and this consumption is driven by recommendation systems. The latter presents a great opportunity to bias the recommender to minimize content access cost (e.g. maximizing cache hit rates). To this end, in this paper we first propose a Markovian model for recommendation-driven user requests. We then formulate the problem of biasing the recommendation algorithm to minimize access cost, while maintaining acceptable recommendation quality. We show that the problem is non-convex, and propose an iterative ADMM-based algorithm that outperforms existing schemes, and shows significant potential for performance improvement on real content datasets.978-1-5386-4725-7/18/$31.00 c 2018 IEEE

Pushing popular content to cheap "helper" nodes (e.g., small cells) during off-peak hours has recently been proposed to cope with the increase in mobile data traffic. User requests can be served locally from these helper nodes, if the requested content is available in at least one of the nearby helpers. Nevertheless, the collective storage of a few nearby helper nodes does not usually suffice to achieve a high enough hit rate in practice. We propose to depart from the assumption of hard cache hits, common in existing works, and consider "soft" cache hits, where if the original content is not available, some related contents that are locally cached can be recommended instead. Given that Internet content consumption is entertainment-oriented, we argue that there exist scenarios where a user might accept an alternative content (e.g., better download rate for alternative content, low rate plans, etc.), thus avoiding to access expensive/congested links. We formulate the problem of optimal edge caching with soft cache hits in a relatively generic setup, propose efficient algorithms, and analyze the expected gains. We then show using synthetic and real datasets of related video contents that promising caching gains could be achieved in practice.

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BGP prefix hijacking is a threat to Internet operators and users. Several mechanisms or modifications to BGP that protect the Internet against it have been proposed. However, the reality is that most operators have not deployed them and are reluctant to do so in the near future. Instead, they rely on basic -and often inefficient -proactive defenses to reduce the impact of hijacking events, or on detection based on third party services and reactive approaches that might take up to several hours. In this work, we present the results of a survey we conducted among 75 network operators to study: (a) the operators' awareness of BGP prefix hijacking attacks, (b) presently used defenses (if any) against BGP prefix hijacking, (c) the willingness to adopt new defense mechanisms, and (d) reasons that may hinder the deployment of BGP prefix hijacking defenses. We expect the findings of this survey to increase the understanding of existing BGP hijacking defenses and the needs of network operators, as well as contribute towards designing new defense mechanisms that satisfy the requirements of the operators.

Caching popular content at the edge of future mobile networks has been widely considered in order to alleviate the impact of the data tsunami on both the access and backhaul networks. A number of interesting techniques have been proposed, including femto-caching and "delayed" or opportunistic cache access. Nevertheless, the majority of these approaches suffer from the rather limited storage capacity of the edge caches, compared to the tremendous and rapidly increasing size of the Internet content catalog. We propose to depart from the assumption of hard cache misses, common in most existing works, and consider "soft" cache misses, where if the original content is not available, an alternative content that is locally cached can be recommended. Given that Internet content consumption is increasingly entertainment-oriented, we believe that a related content could often lead to complete or at least partial user satisfaction, without the need to retrieve the original content over expensive links. In this paper, we formulate the problem of optimal edge caching with soft cache hits, in the context of delayed access, and analyze the expected gains. We then show using synthetic and real datasets of related video contents that promising caching gains could be achieved in practice.

No abstract