8,732 research outputs found
Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments
Decentralized systems are a subset of distributed systems where multiple
authorities control different components and no authority is fully trusted by
all. This implies that any component in a decentralized system is potentially
adversarial. We revise fifteen years of research on decentralization and
privacy, and provide an overview of key systems, as well as key insights for
designers of future systems. We show that decentralized designs can enhance
privacy, integrity, and availability but also require careful trade-offs in
terms of system complexity, properties provided, and degree of
decentralization. These trade-offs need to be understood and navigated by
designers. We argue that a combination of insights from cryptography,
distributed systems, and mechanism design, aligned with the development of
adequate incentives, are necessary to build scalable and successful
privacy-preserving decentralized systems
TRIDEnT: Building Decentralized Incentives for Collaborative Security
Sophisticated mass attacks, especially when exploiting zero-day
vulnerabilities, have the potential to cause destructive damage to
organizations and critical infrastructure. To timely detect and contain such
attacks, collaboration among the defenders is critical. By correlating
real-time detection information (alerts) from multiple sources (collaborative
intrusion detection), defenders can detect attacks and take the appropriate
defensive measures in time. However, although the technical tools to facilitate
collaboration exist, real-world adoption of such collaborative security
mechanisms is still underwhelming. This is largely due to a lack of trust and
participation incentives for companies and organizations. This paper proposes
TRIDEnT, a novel collaborative platform that aims to enable and incentivize
parties to exchange network alert data, thus increasing their overall detection
capabilities. TRIDEnT allows parties that may be in a competitive relationship,
to selectively advertise, sell and acquire security alerts in the form of
(near) real-time peer-to-peer streams. To validate the basic principles behind
TRIDEnT, we present an intuitive game-theoretic model of alert sharing, that is
of independent interest, and show that collaboration is bound to take place
infinitely often. Furthermore, to demonstrate the feasibility of our approach,
we instantiate our design in a decentralized manner using Ethereum smart
contracts and provide a fully functional prototype.Comment: 28 page
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Privacy-preserving scheme for mobile ad hoc networks.
This paper proposes a decentralized trust establishment protocol for mobile ad hoc networks (MANETs), where nodes establish security associations. In order to achieve privacy and security, we use homomorphic encryption and polynomial intersection so as to find the intersection of two sets. The first set represents a list of recommenders of the initiator and the second set is a list of trusted recommenders of the responder. The intersection of the sets represents a list of nodes that recommend the first node and their recommendations are trusted by the second node. In our experimental results we show that our scheme is effective even if there are 30 trusted nodes
Lightweight Blockchain Framework for Location-aware Peer-to-Peer Energy Trading
Peer-to-Peer (P2P) energy trading can facilitate integration of a large
number of small-scale producers and consumers into energy markets.
Decentralized management of these new market participants is challenging in
terms of market settlement, participant reputation and consideration of grid
constraints. This paper proposes a blockchain-enabled framework for P2P energy
trading among producer and consumer agents in a smart grid. A fully
decentralized market settlement mechanism is designed, which does not rely on a
centralized entity to settle the market and encourages producers and consumers
to negotiate on energy trading with their nearby agents truthfully. To this
end, the electrical distance of agents is considered in the pricing mechanism
to encourage agents to trade with their neighboring agents. In addition, a
reputation factor is considered for each agent, reflecting its past performance
in delivering the committed energy. Before starting the negotiation, agents
select their trading partners based on their preferences over the reputation
and proximity of the trading partners. An Anonymous Proof of Location (A-PoL)
algorithm is proposed that allows agents to prove their location without
revealing their real identity. The practicality of the proposed framework is
illustrated through several case studies, and its security and privacy are
analyzed in detail
ARPA Whitepaper
We propose a secure computation solution for blockchain networks. The
correctness of computation is verifiable even under malicious majority
condition using information-theoretic Message Authentication Code (MAC), and
the privacy is preserved using Secret-Sharing. With state-of-the-art multiparty
computation protocol and a layer2 solution, our privacy-preserving computation
guarantees data security on blockchain, cryptographically, while reducing the
heavy-lifting computation job to a few nodes. This breakthrough has several
implications on the future of decentralized networks. First, secure computation
can be used to support Private Smart Contracts, where consensus is reached
without exposing the information in the public contract. Second, it enables
data to be shared and used in trustless network, without disclosing the raw
data during data-at-use, where data ownership and data usage is safely
separated. Last but not least, computation and verification processes are
separated, which can be perceived as computational sharding, this effectively
makes the transaction processing speed linear to the number of participating
nodes. Our objective is to deploy our secure computation network as an layer2
solution to any blockchain system. Smart Contracts\cite{smartcontract} will be
used as bridge to link the blockchain and computation networks. Additionally,
they will be used as verifier to ensure that outsourced computation is
completed correctly. In order to achieve this, we first develop a general MPC
network with advanced features, such as: 1) Secure Computation, 2) Off-chain
Computation, 3) Verifiable Computation, and 4)Support dApps' needs like
privacy-preserving data exchange
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