730 research outputs found
Defending against Sybil Devices in Crowdsourced Mapping Services
Real-time crowdsourced maps such as Waze provide timely updates on traffic,
congestion, accidents and points of interest. In this paper, we demonstrate how
lack of strong location authentication allows creation of software-based {\em
Sybil devices} that expose crowdsourced map systems to a variety of security
and privacy attacks. Our experiments show that a single Sybil device with
limited resources can cause havoc on Waze, reporting false congestion and
accidents and automatically rerouting user traffic. More importantly, we
describe techniques to generate Sybil devices at scale, creating armies of
virtual vehicles capable of remotely tracking precise movements for large user
populations while avoiding detection. We propose a new approach to defend
against Sybil devices based on {\em co-location edges}, authenticated records
that attest to the one-time physical co-location of a pair of devices. Over
time, co-location edges combine to form large {\em proximity graphs} that
attest to physical interactions between devices, allowing scalable detection of
virtual vehicles. We demonstrate the efficacy of this approach using
large-scale simulations, and discuss how they can be used to dramatically
reduce the impact of attacks against crowdsourced mapping services.Comment: Measure and integratio
The Mason Test: A Defense Against Sybil Attacks in Wireless Networks Without Trusted Authorities
Wireless networks are vulnerable to Sybil attacks, in which a malicious node
poses as many identities in order to gain disproportionate influence. Many
defenses based on spatial variability of wireless channels exist, but depend
either on detailed, multi-tap channel estimation - something not exposed on
commodity 802.11 devices - or valid RSSI observations from multiple trusted
sources, e.g., corporate access points - something not directly available in ad
hoc and delay-tolerant networks with potentially malicious neighbors. We extend
these techniques to be practical for wireless ad hoc networks of commodity
802.11 devices. Specifically, we propose two efficient methods for separating
the valid RSSI observations of behaving nodes from those falsified by malicious
participants. Further, we note that prior signalprint methods are easily
defeated by mobile attackers and develop an appropriate challenge-response
defense. Finally, we present the Mason test, the first implementation of these
techniques for ad hoc and delay-tolerant networks of commodity 802.11 devices.
We illustrate its performance in several real-world scenarios
X-Vine: Secure and Pseudonymous Routing Using Social Networks
Distributed hash tables suffer from several security and privacy
vulnerabilities, including the problem of Sybil attacks. Existing social
network-based solutions to mitigate the Sybil attacks in DHT routing have a
high state requirement and do not provide an adequate level of privacy. For
instance, such techniques require a user to reveal their social network
contacts. We design X-Vine, a protection mechanism for distributed hash tables
that operates entirely by communicating over social network links. As with
traditional peer-to-peer systems, X-Vine provides robustness, scalability, and
a platform for innovation. The use of social network links for communication
helps protect participant privacy and adds a new dimension of trust absent from
previous designs. X-Vine is resilient to denial of service via Sybil attacks,
and in fact is the first Sybil defense that requires only a logarithmic amount
of state per node, making it suitable for large-scale and dynamic settings.
X-Vine also helps protect the privacy of users social network contacts and
keeps their IP addresses hidden from those outside of their social circle,
providing a basis for pseudonymous communication. We first evaluate our design
with analysis and simulations, using several real world large-scale social
networking topologies. We show that the constraints of X-Vine allow the
insertion of only a logarithmic number of Sybil identities per attack edge; we
show this mitigates the impact of malicious attacks while not affecting the
performance of honest nodes. Moreover, our algorithms are efficient, maintain
low stretch, and avoid hot spots in the network. We validate our design with a
PlanetLab implementation and a Facebook plugin.Comment: 15 page
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