5,331 research outputs found
Hang With Your Buddies to Resist Intersection Attacks
Some anonymity schemes might in principle protect users from pervasive
network surveillance - but only if all messages are independent and unlinkable.
Users in practice often need pseudonymity - sending messages intentionally
linkable to each other but not to the sender - but pseudonymity in dynamic
networks exposes users to intersection attacks. We present Buddies, the first
systematic design for intersection attack resistance in practical anonymity
systems. Buddies groups users dynamically into buddy sets, controlling message
transmission to make buddies within a set behaviorally indistinguishable under
traffic analysis. To manage the inevitable tradeoffs between anonymity
guarantees and communication responsiveness, Buddies enables users to select
independent attack mitigation policies for each pseudonym. Using trace-based
simulations and a working prototype, we find that Buddies can guarantee
non-trivial anonymity set sizes in realistic chat/microblogging scenarios, for
both short-lived and long-lived pseudonyms.Comment: 15 pages, 8 figure
A Flexible Network Approach to Privacy of Blockchain Transactions
For preserving privacy, blockchains can be equipped with dedicated mechanisms
to anonymize participants. However, these mechanism often take only the
abstraction layer of blockchains into account whereas observations of the
underlying network traffic can reveal the originator of a transaction request.
Previous solutions either provide topological privacy that can be broken by
attackers controlling a large number of nodes, or offer strong and
cryptographic privacy but are inefficient up to practical unusability. Further,
there is no flexible way to trade privacy against efficiency to adjust to
practical needs. We propose a novel approach that combines existing mechanisms
to have quantifiable and adjustable cryptographic privacy which is further
improved by augmented statistical measures that prevent frequent attacks with
lower resources. This approach achieves flexibility for privacy and efficency
requirements of different blockchain use cases.Comment: 6 pages, 2018 IEEE 38th International Conference on Distributed
Computing Systems (ICDCS
TARANET: Traffic-Analysis Resistant Anonymity at the NETwork layer
Modern low-latency anonymity systems, no matter whether constructed as an
overlay or implemented at the network layer, offer limited security guarantees
against traffic analysis. On the other hand, high-latency anonymity systems
offer strong security guarantees at the cost of computational overhead and long
delays, which are excessive for interactive applications. We propose TARANET,
an anonymity system that implements protection against traffic analysis at the
network layer, and limits the incurred latency and overhead. In TARANET's setup
phase, traffic analysis is thwarted by mixing. In the data transmission phase,
end hosts and ASes coordinate to shape traffic into constant-rate transmission
using packet splitting. Our prototype implementation shows that TARANET can
forward anonymous traffic at over 50~Gbps using commodity hardware
A Developer-Friendly Library for Smart Home IoT Privacy-Preserving Traffic Obfuscation
The number and variety of Internet-connected devices have grown enormously in
the past few years, presenting new challenges to security and privacy. Research
has shown that network adversaries can use traffic rate metadata from consumer
IoT devices to infer sensitive user activities. Shaping traffic flows to fit
distributions independent of user activities can protect privacy, but this
approach has seen little adoption due to required developer effort and overhead
bandwidth costs. Here, we present a Python library for IoT developers to easily
integrate privacy-preserving traffic shaping into their products. The library
replaces standard networking functions with versions that automatically
obfuscate device traffic patterns through a combination of payload padding,
fragmentation, and randomized cover traffic. Our library successfully preserves
user privacy and requires approximately 4 KB/s overhead bandwidth for IoT
devices with low send rates or high latency tolerances. This overhead is
reasonable given normal Internet speeds in American homes and is an improvement
on the bandwidth requirements of existing solutions.Comment: 6 pages, 6 figure
Dovetail: Stronger Anonymity in Next-Generation Internet Routing
Current low-latency anonymity systems use complex overlay networks to conceal
a user's IP address, introducing significant latency and network efficiency
penalties compared to normal Internet usage. Rather than obfuscating network
identity through higher level protocols, we propose a more direct solution: a
routing protocol that allows communication without exposing network identity,
providing a strong foundation for Internet privacy, while allowing identity to
be defined in those higher level protocols where it adds value.
Given current research initiatives advocating "clean slate" Internet designs,
an opportunity exists to design an internetwork layer routing protocol that
decouples identity from network location and thereby simplifies the anonymity
problem. Recently, Hsiao et al. proposed such a protocol (LAP), but it does not
protect the user against a local eavesdropper or an untrusted ISP, which will
not be acceptable for many users. Thus, we propose Dovetail, a next-generation
Internet routing protocol that provides anonymity against an active attacker
located at any single point within the network, including the user's ISP. A
major design challenge is to provide this protection without including an
application-layer proxy in data transmission. We address this challenge in path
construction by using a matchmaker node (an end host) to overlap two path
segments at a dovetail node (a router). The dovetail then trims away part of
the path so that data transmission bypasses the matchmaker. Additional design
features include the choice of many different paths through the network and the
joining of path segments without requiring a trusted third party. We develop a
systematic mechanism to measure the topological anonymity of our designs, and
we demonstrate the privacy and efficiency of our proposal by simulation, using
a model of the complete Internet at the AS-level
Low-latency mix networks for anonymous communication
Every modern online application relies on the network layer to transfer information, which exposes the metadata associated with digital communication. These distinctive characteristics encapsulate equally meaningful information as the content of the communication itself and allow eavesdroppers to uniquely identify users and their activities. Hence, by exposing the IP addresses and by analyzing patterns of the network traffic, a malicious entity can deanonymize most online communications. While content confidentiality has made significant progress over the years, existing solutions for anonymous communication which protect the network metadata still have severe limitations, including centralization, limited security, poor scalability, and high-latency. As the importance of online privacy increases, the need to build low-latency communication systems with strong security guarantees becomes necessary. Therefore, in this thesis, we address the problem of building multi-purpose anonymous networks that protect communication privacy. To this end, we design a novel mix network Loopix, which guarantees communication unlinkability and supports applications with various latency and bandwidth constraints. Loopix offers better security properties than any existing solution for anonymous communications while at the same time being scalable and low-latency. Furthermore, we also explore the problem of active attacks and malicious infrastructure nodes, and propose a Miranda mechanism which allows to efficiently mitigate them. In the second part of this thesis, we show that mix networks may be used as a building block in the design of a private notification system, which enables fast and low-cost online notifications. Moreover, its privacy properties benefit from an increasing number of users, meaning that the system can scale to millions of clients at a lower cost than any alternative solution
Vuvuzela: scalable private messaging resistant to traffic analysis
Private messaging over the Internet has proven challenging to implement, because even if message data is encrypted, it is difficult to hide metadata about who is communicating in the face of traffic analysis. Systems that offer strong privacy guarantees, such as Dissent [36], scale to only several thousand clients, because they use techniques with superlinear cost in the number of clients (e.g., each client broadcasts their message to all other clients). On the other hand, scalable systems, such as Tor, do not protect against traffic analysis, making them ineffective in an era of pervasive network monitoring.
Vuvuzela is a new scalable messaging system that offers strong privacy guarantees, hiding both message data and metadata. Vuvuzela is secure against adversaries that observe and tamper with all network traffic, and that control all nodes except for one server. Vuvuzela's key insight is to minimize the number of variables observable by an attacker, and to use differential privacy techniques to add noise to all observable variables in a way that provably hides information about which users are communicating. Vuvuzela has a linear cost in the number of clients, and experiments show that it can achieve a throughput of 68,000 messages per second for 1 million users with a 37-second end-to-end latency on commodity servers.National Science Foundation (U.S.) (Award CNS-1053143)National Science Foundation (U.S.) (Award CNS-1413920
Exploratory study to explore the role of ICT in the process of knowledge management in an Indian business environment
In the 21st century and the emergence of a digital economy, knowledge and the knowledge base economy are rapidly growing. To effectively be able to understand the processes involved in the creating, managing and sharing of knowledge management in the business environment is critical to the success of an organization. This study builds on the previous research of the authors on the enablers of knowledge management by identifying the relationship between the enablers of knowledge management and the role played by information communication technologies (ICT) and ICT infrastructure in a business setting. This paper provides the findings of a survey collected from the four major Indian cities (Chennai, Coimbatore, Madurai and Villupuram) regarding their views and opinions about the enablers of knowledge management in business setting. A total of 80 organizations participated in the study with 100 participants in each city. The results show that ICT and ICT infrastructure can play a critical role in the creating, managing and sharing of knowledge in an Indian business environment
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