Asynchrony and Collusion in the N-party BAR Transfer Problem

The problem of reliably transferring data from a set of $N_P$ producers to a set of $N_C$ consumers in the BAR model, named N-party BAR Transfer (NBART), is an important building block for volunteer computing systems. An algorithm to solve this problem in synchronous systems, which provides a Nash equilibrium, has been presented in previous work. In this paper, we propose an NBART algorithm for asynchronous systems. Furthermore, we also address the possibility of collusion among the Rational processes. Our game theoretic analysis shows that the proposed algorithm tolerates certain degree of arbitrary collusion, while still fulfilling the NBART properties.Comment: 13 pages, 3 algorithms, to appear in Proceedings of the 19th International Colloquium on Structural Information and Communication Complexity (SIROCCO 2012

Coping with Unreliable Workers in Internet-based Computing: An Evaluation of Reputation Mechanisms

We present reputation-based mechanisms for building reliable task computing systems over the Internet. The most characteristic examples of such systems are the volunteer computing and the crowdsourcing platforms. In both examples end users are offering over the Internet their computing power or their human intelligence to solve tasks either voluntarily or under payment. While the main advantage of these systems is the inexpensive computational power provided, the main drawback is the untrustworthy nature of the end users. Generally, this type of systems are modeled under the "master-worker" setting. A "master" has a set of tasks to compute and instead of computing them locally she sends these tasks to available "workers" that compute and report back the task results. We categorize these workers in three generic types: altruistic, malicious and rational. Altruistic workers that always return the correct result, malicious workers that always return an incorrect result, and rational workers that decide to reply or not truthfully depending on what increases their benefit. We design a reinforcement learning mechanism to induce a correct behavior to rational workers, while the mechanism is complemented by four reputation schemes that cope with malice. The goal of the mechanism is to reach a state of eventual correctness, that is, a stable state of the system in which the master always obtains the correct task results. Analysis of the system gives provable guarantees under which truthful behavior can be ensured. Finally, we observe the behavior of the mechanism through simulations that use realistic system parameters values. Simulations not only agree with the analysis but also reveal interesting trade-offs between various metrics and parameters. Finally, the four reputation schemes are assessed against the tolerance to cheaters.Comment: 28 pages, 12 figure

Proof of Work Without All the Work: Computationally Efficient Attack-Resistant Systems

Proof-of-work (PoW) is an algorithmic tool used to secure networks by imposing a computational cost on participating devices. Unfortunately, traditional PoW schemes require that correct devices perform computational work perpetually, even when the system is not under attack. We address this issue by designing a general PoW protocol that ensures two properties. First, the network stays secure. In particular, the fraction of identities in the system that are controlled by an attacker is always less than 1/2. Second, our protocol's computational cost is commensurate with the cost of an attacker. In particular, the total computational cost of correct devices is a linear function of the attacker's computational cost plus the number of correct devices that have joined the system. Consequently, if the network is attacked, we ensure security with cost that grows linearly with the attacker's cost; and, in the absence of attack, our computational cost remains small. We prove similar guarantees for bandwidth cost. Our results hold in a dynamic, decentralized system where participants join and depart over time, and where the total computational power of the attacker is up to a constant fraction of the total computational power of correct devices. We demonstrate how to leverage our results to address important security problems in distributed computing including: Sybil attacks, Byzantine consensus, and Committee election