435 research outputs found
Fighting Authorship Linkability with Crowdsourcing
Massive amounts of contributed content -- including traditional literature,
blogs, music, videos, reviews and tweets -- are available on the Internet
today, with authors numbering in many millions. Textual information, such as
product or service reviews, is an important and increasingly popular type of
content that is being used as a foundation of many trendy community-based
reviewing sites, such as TripAdvisor and Yelp. Some recent results have shown
that, due partly to their specialized/topical nature, sets of reviews authored
by the same person are readily linkable based on simple stylometric features.
In practice, this means that individuals who author more than a few reviews
under different accounts (whether within one site or across multiple sites) can
be linked, which represents a significant loss of privacy.
In this paper, we start by showing that the problem is actually worse than
previously believed. We then explore ways to mitigate authorship linkability in
community-based reviewing. We first attempt to harness the global power of
crowdsourcing by engaging random strangers into the process of re-writing
reviews. As our empirical results (obtained from Amazon Mechanical Turk)
clearly demonstrate, crowdsourcing yields impressively sensible reviews that
reflect sufficiently different stylometric characteristics such that prior
stylometric linkability techniques become largely ineffective. We also consider
using machine translation to automatically re-write reviews. Contrary to what
was previously believed, our results show that translation decreases authorship
linkability as the number of intermediate languages grows. Finally, we explore
the combination of crowdsourcing and machine translation and report on the
results
To NACK or not to NACK? Negative Acknowledgments in Information-Centric Networking
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
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
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