3,483 research outputs found
Enabling Social Applications via Decentralized Social Data Management
An unprecedented information wealth produced by online social networks,
further augmented by location/collocation data, is currently fragmented across
different proprietary services. Combined, it can accurately represent the
social world and enable novel socially-aware applications. We present
Prometheus, a socially-aware peer-to-peer service that collects social
information from multiple sources into a multigraph managed in a decentralized
fashion on user-contributed nodes, and exposes it through an interface
implementing non-trivial social inferences while complying with user-defined
access policies. Simulations and experiments on PlanetLab with emulated
application workloads show the system exhibits good end-to-end response time,
low communication overhead and resilience to malicious attacks.Comment: 27 pages, single ACM column, 9 figures, accepted in Special Issue of
Foundations of Social Computing, ACM Transactions on Internet Technolog
OnionBots: Subverting Privacy Infrastructure for Cyber Attacks
Over the last decade botnets survived by adopting a sequence of increasingly
sophisticated strategies to evade detection and take overs, and to monetize
their infrastructure. At the same time, the success of privacy infrastructures
such as Tor opened the door to illegal activities, including botnets,
ransomware, and a marketplace for drugs and contraband. We contend that the
next waves of botnets will extensively subvert privacy infrastructure and
cryptographic mechanisms. In this work we propose to preemptively investigate
the design and mitigation of such botnets. We first, introduce OnionBots, what
we believe will be the next generation of resilient, stealthy botnets.
OnionBots use privacy infrastructures for cyber attacks by completely
decoupling their operation from the infected host IP address and by carrying
traffic that does not leak information about its source, destination, and
nature. Such bots live symbiotically within the privacy infrastructures to
evade detection, measurement, scale estimation, observation, and in general all
IP-based current mitigation techniques. Furthermore, we show that with an
adequate self-healing network maintenance scheme, that is simple to implement,
OnionBots achieve a low diameter and a low degree and are robust to
partitioning under node deletions. We developed a mitigation technique, called
SOAP, that neutralizes the nodes of the basic OnionBots. We also outline and
discuss a set of techniques that can enable subsequent waves of Super
OnionBots. In light of the potential of such botnets, we believe that the
research community should proactively develop detection and mitigation methods
to thwart OnionBots, potentially making adjustments to privacy infrastructure.Comment: 12 pages, 8 figure
Security in Peer-to-Peer SIP VoIP
VoIP (Voice over Internet Protocol) is one of the fastest growing technologies in the world. It is used by people all over the world for communication. But with the growing popularity of internet, security is one of the biggest concerns. It is important that the intruders are not able to sniff the packets that are transmitted over the internet through VoIP. Session Initiation Protocol (SIP) is the most popular and commonly used protocol of VoIP. Now days, companies like Skype are using Peer-to-Peer SIP VoIP for faster and better performance. Through this project I am improving an already existing Peer-to-Peer SIP VoIP called SOSIMPLE P2P VoIP by adding confidentiality in the protocol with the help of public key cryptography
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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