Measurement Device Independent Quantum Dialogue

Very recently, the experimental demonstration of Quantum Secure Direct Communication (QSDC) with state-of-the-art atomic quantum memory has been reported (Phys. Rev. Lett., 2017). Quantum Dialogue (QD) falls under QSDC where the secrete messages are communicated simultaneously between two legitimate parties. The successful experimental demonstration of QSDC opens up the possibilities for practical implementation of QD protocols. Thus, it is necessary to analyze the practical security issues of QD protocols for future implementation. Since the very first proposal for QD by Nguyen (Phys. Lett. A, 2004) a large number of variants and extensions have been presented till date. However, all of those leak half of the secret bits to the adversary through classical communications of the measurement results. In this direction, motivated by the idea of Lo et al. (Phys. Rev. Lett., 2012), we propose a Measurement Device Independent Quantum Dialogue (MDI-QD) scheme which is resistant to such information leakage as well as side channel attacks. In the proposed protocol, Alice and Bob, two legitimate parties, are allowed to prepare the states only. The states are measured by an untrusted third party (UTP) who may himself behave as an adversary. We show that our protocol is secure under this adversarial model. The current protocol does not require any quantum memory and thus it is inherently robust against memory attacks. Such robustness might not be guaranteed in the QSDC protocol with quantum memory (Phys. Rev. Lett., 2017)

Behavioral Mechanism Design: Optimal Contests for Simple Agents

Incentives are more likely to elicit desired outcomes when they are designed based on accurate models of agents' strategic behavior. A growing literature, however, suggests that people do not quite behave like standard economic agents in a variety of environments, both online and offline. What consequences might such differences have for the optimal design of mechanisms in these environments? In this paper, we explore this question in the context of optimal contest design for simple agents---agents who strategically reason about whether or not to participate in a system, but not about the input they provide to it. Specifically, consider a contest where $n$ potential contestants with types $(q_i,c_i)$ each choose between participating and producing a submission of quality $q_i$ at cost $c_i$, versus not participating at all, to maximize their utilities. How should a principal distribute a total prize $V$ amongst the $n$ ranks to maximize some increasing function of the qualities of elicited submissions in a contest with such simple agents? We first solve the optimal contest design problem for settings with homogenous participation costs $c_i = c$. Here, the optimal contest is always a simple contest, awarding equal prizes to the top $j^*$ contestants for a suitable choice of $j^*$. (In comparable models with strategic effort choices, the optimal contest is either a winner-take-all contest or awards possibly unequal prizes, depending on the curvature of agents' effort cost functions.) We next address the general case with heterogeneous costs where agents' types are inherently two-dimensional, significantly complicating equilibrium analysis. Our main result here is that the winner-take-all contest is a 3-approximation of the optimal contest when the principal's objective is to maximize the quality of the best elicited contribution.Comment: This is the full version of a paper in the ACM Conference on Economics and Computation (ACM-EC), 201

Truthful Assignment without Money

We study the design of truthful mechanisms that do not use payments for the generalized assignment problem (GAP) and its variants. An instance of the GAP consists of a bipartite graph with jobs on one side and machines on the other. Machines have capacities and edges have values and sizes; the goal is to construct a welfare maximizing feasible assignment. In our model of private valuations, motivated by impossibility results, the value and sizes on all job-machine pairs are public information; however, whether an edge exists or not in the bipartite graph is a job's private information. We study several variants of the GAP starting with matching. For the unweighted version, we give an optimal strategyproof mechanism; for maximum weight bipartite matching, however, we show give a 2-approximate strategyproof mechanism and show by a matching lowerbound that this is optimal. Next we study knapsack-like problems, which are APX-hard. For these problems, we develop a general LP-based technique that extends the ideas of Lavi and Swamy to reduce designing a truthful mechanism without money to designing such a mechanism for the fractional version of the problem, at a loss of a factor equal to the integrality gap in the approximation ratio. We use this technique to obtain strategyproof mechanisms with constant approximation ratios for these problems. We then design an O(log n)-approximate strategyproof mechanism for the GAP by reducing, with logarithmic loss in the approximation, to our solution for the value-invariant GAP. Our technique may be of independent interest for designing truthful mechanisms without money for other LP-based problems.Comment: Extended abstract appears in the 11th ACM Conference on Electronic Commerce (EC), 201