Sealed-bid Auction Research Articles

Gage MPC: Bypassing Residual Function Leakage for Non-Interactive MPC

Abstract Existing models for non-interactive MPC cannot provide full privacy for inputs, because they inherently leak the residual function (i.e., the output of the function on the honest parties’ input together with all possible values of the adversarial inputs). For example, in any non-interactive sealed-bid auction, the last bidder can figure out what was the highest previous bid. We present a new MPC model which avoids this privacy leak. To achieve this, we utilize a blockchain in a novel way, incorporating smart contracts and arbitrary parties that can be incentivized to perform computation (“bounty hunters,” akin to miners). Security is maintained under a monetary assumption about the parties: an honest party can temporarily supply a recoverable collateral of value higher than the computational cost an adversary can expend. We thus construct non-interactive MPC protocols with strong security guarantees (full security, no residual leakage) in the short term. Over time, as the adversary can invest more and more computational resources, the security guarantee decays. Thus, our model, which we call Gage MPC, is suitable for secure computation with limited-time secrecy, such as auctions. A key ingredient in our protocols is a primitive we call “Gage Time Capsules” (GaTC): a time capsule that allows a party to commit to a value that others are able to reveal but only at a designated computational cost. A GaTC allows a party to commit to a value together with a monetary collateral. If the original party properly opens the GaTC, it can recover the collateral. Otherwise, the collateral is used to incentivize bounty hunters to open the GaTC. This primitive is used to ensure completion of Gage MPC protocols on the desired inputs. As a requisite tool (of independent interest), we present a generalization of garbled circuit that are more robust: they can tolerate exposure of extra input labels. This is in contrast to Yao’s garbled circuits, whose secrecy breaks down if even a single extra label is exposed. Finally, we present a proof-of-concept implementation of a special case of our construction, yielding an auction functionality over an Ethereum-like blockchain.

Adversarial Risk Analysis for Auctions Using Mirror Equilibrium and Bayes Nash Equilibrium

In this paper, we use the adversarial risk analysis (ARA) methodology to model first-price sealed-bid auctions under quite realistic assumptions. We extend prior work to find ARA solutions for mirror equilibrium and Bayes Nash equilibrium solution concepts, not only for risk-neutral but also for risk-averse and risk-seeking bidders. We also consider bidders having different wealth and assume that the auctioned item has a reserve price.

Quantum sealed-bid auction protocol for simultaneous ascending auction with GHZ states

Quantum sealed-bid auction protocol for simultaneous ascending auction with GHZ states

Strategic Polarization in Group Interactions

The authors study the phenomenon of strategic group polarization, in which members take more extreme actions than their preferences. The analysis is relevant for a broad range of formal and informal group settings, including social media, online platforms, sales teams, corporate and academic committees, and political action committees. In the model, agents with private preferences choose a public action (voice opinions), and the mean of their actions represents the group’s realized outcome. The agents face a trade-off between influencing the group decision and truth-telling. In a simultaneous-move game, agents strategically shade their actions toward the extreme. The strategic group influence motive can create substantial polarization in actions and group decisions even when the preferences are relatively moderate. Compared with a simultaneous game, a randomized-sequential-actions game lowers polarization when agents’ preferences are relatively similar. Sequential actions can even lead to moderation if the later agents have moderate preferences. Endogenizing the order of moves (through a first-price sealed-bid auction) always increases polarization, but it is also welfare enhancing. These findings can help group leaders, firms, and platforms design mechanisms that moderate polarization, such as the choice of speaking order, the group size, and the knowledge members have of others’ preferences and actions.

Testing for risk aversion in first-price sealed-bid auctions

We consider testing for risk aversion in first-price sealed-bid auctions with symmetric bidders and independent private values. We impose several restrictions on the parameter space, which are all implied by Guerre et al. (2009)’s exclusion restriction, and we articulate what restrictions are needed for our test to control the limiting size and to be pointwise consistent. Critical values can be obtained from the standard normal distribution. We also analyze local-power properties and show that our test detects local alternative at the parametric rate.

Signalling in auctions: Experimental evidence

We study the relative performance of the first-price sealed-bid auction, the second-price sealed-bid auction, and the all-pay sealed-bid auction in a laboratory experiment where bidders can signal information through their bidding behaviour to an outside observer. We consider two different information settings: the auctioneer reveals either the identity of the winning bidder only, or she also reveals the bidders’ payments to an outside observer. We find that the all-pay sealed-bid auction in which the bidders’ payments are revealed outperforms the other mechanisms in terms of revenue, while this mechanism underperforms in terms of efficiency relative to the winner-pay auctions.

Evolution Strategies for Approximate Solution of Bayesian Games

We address the problem of solving complex Bayesian games, characterized by high-dimensional type and action spaces, many (> 2) players, and general-sum payoffs. Our approach applies to symmetric one-shot Bayesian games, with no given analytic structure. We represent agent strategies in parametric form as neural networks, and apply natural evolution strategies (NES) [wierstra2014natural] for deep model optimization. For pure equilibrium computation, we formulate the problem as bi-level optimization, and employ NES in an iterative algorithm to implement both inner-loop best response optimization and outer-loop regret minimization. In simple games including first- and second-price auctions, it is capable of recovering known analytic solutions. For mixed equilibrium computation, we adopt an incremental strategy generation framework, with NES as strategy generator producing a finite sequence of approximate best-response strategies. We then calculate equilibria over this finite strategy set via a model-based optimization process. Both our pure and mixed equilibrium computation methods employ NES to efficiently search for strategies over the functional space, given only black-box simulation access to noisy payoff samples. We experimentally demonstrate the efficacy of all methods on two simultaneous sealed-bid auction games with distinct type distributions, and observe that the solutions exhibit qualitatively different behavior in these two environments.

Quantum-based privacy-preserving sealed-bid auction on the blockchain

Sealed-bid auction is one of the major protocols used in the electronic commerce industry. Recently, many schemes have been proposed to implement sealed-bid auction protocols based on quantum computing, while other schemes have adopted the blockchain. However, each of the previous proposals has focused on a few sealed-bid auction features while simply ignoring others. A robust sealed-bid auction protocol should comprise all important features and satisfy all requirements. We design a sealed-bid auction protocol using quantum-based blockchain, in which the transactions of the sealed-bid auction are stored using the blockchain and supported by quantum computation and communication to enhance security and protect privacy. Our proposed protocol takes advantage of both quantum computing and blockchain technology to ensure essential features and requirements. Security analysis, evaluation, and comparisons are presented to demonstrate the advantages of our protocol.

Are strategies anchored?

Anchoring is one of the most studied and robust behavioral biases, but there is little knowledge about its persistence in economic strategic interactions. Using experimental auctions, we show that bidding strategies are anchored by irrelevant numbers. The announcement of a random group identification number has a positive effect on bids. We also find a strong effect of a maximal permissible bid, despite being irrelevant for a rational player: In first-price sealed-bid auctions, a higher upper bid limit increases bids, whereas, in Dutch auctions, the effect of the starting price is negative and consistent with a model that takes into account the value of time in auctions. We demonstrate that the long-established ranking that the Dutch auction generates lower revenue than the sealed-bid auction crucially depends on the size of the maximal permissible bid.

Resource allocation mechanisms for maximizing provider’s revenue in infrastructure as a service (IaaS) cloud

Infrastructure as a Service (IaaS) is a cloud computing service provided over the internet to facilitate the provisioning of various services such as storage, processes, etc. The provider in the IaaS market may offer some purchasing plans including: reservation, on-demand, and spot plans for its resources. As in real scenarios, demand volume for each plan is assumed to be a random variable with a given probability distribution. The provider maximizes its average revenue in the long run by optimal allocation of its resources among the plans. We formulate an Integer Linear Programming (ILP) model with a stochastic constraint, to determine the number of resources to be allocated for each plan in every time slot in the planning horizon. First, fixed prices are considered for each plan, then two mechanisms of Continuous Double Auction and Second Price Sealed Bid Auction are considered for reservations and spot plans, respectively, to obtain market-driven prices of the services. The Seasonal Weighted Moving Average method is used to predict the amount of demand in every slot. Finally, the proposed mechanisms are evaluated through simulations and the results confirm the effectiveness of the methods in maximizing the revenue and overall utilization of the available IaaS capacity.

First price sealed-bid auction of the grey game improvement model via double-parameter Bayesian estimation

PurposeThe improved classical model makes it possible that the evaluation strategy has an optimal tendency, which reveals the purpose of this paper is to facilitate the first price sealed-bid auction more in line with the actual situation. To be more specific, there are several merits in the improvement process. On the one hand, the bid-winning probability can be improved for the bidder; on the other hand, the real market value of the subject matter can be more clearly recognized for the employer.Design/methodology/approachBayesian estimation and grey system theory are referenced in this paper, with the use of double-parameter estimation, little historical data and expert experience. Specific implementation steps are as follows: first of all, using the double-parameter Bayesian estimation to correct the actual valuation of the bid matter v, then introducing the threat factor grey number R in the auction model, giving the improving of the optimal grey quotation and grey expectation utility under the two-party game and finally taking the aerospace component procurement as an example, simulating the bidding process of the bidding parties to arrive at the optimal bid strategy.FindingsThe improved model shows that the optimal strategy will change with the threat factor rather than a fixed value. When the threat factor grey number R follows [0.4, 0.6], the optimal quotation strategy will appear, which means quotation is higher than 50% of the bid matter's valuation.Practical implicationsThe improved model proposed in this paper can strengthen the cost control in the Chinese commercial space process and optimize the pricing strategy for the final launch.Originality/valueThe modified model changes the habit that the bidder's valuation of the bid subject to mainly come from experience and to prompt the model for making full use of little historical data on the foundation of the former. It can reduce the subjective judgment error in the game results; finally, the practical cases are simulated in MATLAB at the same time, and the simulation effect is good, so we can get some more realistic conclusions on this basis.

Experimental Evidence on Semi-Structured Bargaining with Private Information

We conduct a laboratory experiment to study a decentralized market where goods are differentiated and evaluations are private. We implement different semi-structured bargaining protocols based on deferred acceptance, and we compare their performance to the benchmark scenario of a sealed-bid auction. We show that bargaining dramatically improves efficiency, mainly to the benefit of players rather than the silent auctioneer. A protocol of unconstrained simultaneous bargaining performs best, doubling the proportion of deals relative to the benchmark. This is because participants seek to reveal information through a gradual bidding-up strategy that favors bargaining environments. Aggregate efficiency nonetheless suffers from the fact that buyers bargain harder than sellers, and that some players over-bargain to appropriate a larger share of the unknown surplus.

Strategy-Proof Spectrum Allocation Among Multiple Operators in Wireless Networks

The exponentially increasing demand for data necessitates efficient spectrum allocation among operators in wireless networks. In this paper, we address the spectrum allocation problem among non-cooperative operators via auctions. The classical Vickrey-Clarke-Groves (VCG) approach provides the framework for a strategy-proof and social welfare maximizing auction. However, the VCG mechanism has high computational complexity, which makes it infeasible for practical implementation. In this work, we propose sealed bid auction mechanisms for spectrum allocation, which are computationally tractable. These can be used for spectrum allocation by performing auctions at shorter intervals to cater to the dynamic load variation in the network. We establish that the proposed algorithm is strategy-proof for the uniform demand scenario. Furthermore, for non-uniform demand, we propose an algorithm that satisfies weak strategy-proofness. Here, we also consider non-linear increase in the marginal valuations with demand. Simulation results are also presented to exhibit the performance comparison of the proposed algorithms with VCG and other existing mechanisms.

Auctions with an Invitation Cost

We consider an auction in which a seller invites potential buyers to a sealed-bid first-price auction, without disclosing to the buyers the number of extended invitations. In the presence of a fixed invitation cost for each invited bidder, the whole auction can be described as a game, where the set of players consists of all bidders together with the seller. In a setting with fully observable common values we show the existence of a Nash equilibrium in mixed strategies. In this equilibrium, the seller should invite precisely one or two potential buyers with certain probabilities, and each invited buyer should place a randomized bid according to a certain distribution.

Quantum Sealed-Bid Auction Protocol Based on Semi-honest Model

In view of the possible disclosure of personal information in the quantum auction protocol, by using the correlation between entangled particles and quantum teleportation, we propose a secure quantum sealed-bid auction (QSBA) protocol based on semi-honest model. In this protocol, by introducing a trusted third party Trent, we separate the registration operation of users from the business function of auction center. Bidders and the auction center can realize quantum identity authentication without information disclosure, so as to reduce the risk of the auction center disclosing the personal information of bidders. With the help of Trent, using the quantum sequences to be the information carrier of bidding, the auction center and bidders can conduct quantum teleportation to obtain each bidding price. When the auction center publishes the bid price and serial number, the registration center also publishes the corresponding winning bidder. Through security analysis, our protocol can guarantee the anonymity of bidders and the integrity of bidding information.

A Fair and Secure Reverse Auction for Government Procurement

With the development of e-commerce, the electronic auction is attracting the attention of many people. Many Internet companies, such as eBay and Yahoo!, have launched online auction systems. Many researchers have studied the security problems of electronic auction systems, but few of them are multi-attribute-based. In 2014, Shi proposed a provable secure, sealed-bid, and multi-attribute auction protocol based on the semi-honest model. We evaluated this protocol and found that it has some design weaknesses and is vulnerable to the illegal operations of buyers, which results in unfairness. In this paper, we improved this protocol by replacing the Paillier’s cryptosystem with the elliptic curve discrete (ECC), and we designed a novel, online, and multi-attribute reverse-auction system using the semi-honest model. In our system, sellers’ identities are not revealed to the buyers, and the buyers cannot conduct illegal operations that may compromise the fairness of the auction.

A model of electoral alliances in highly fragmented party systems

Highly fragmented party systems are composed of a large number of political groups, many of which have negligible bargaining power when it comes to negotiations of electoral alliances. Inspired by the Brazilian system—one of the most fragmented in the world—we provide a stylized model of electoral alliances in which there is a competition for the support of the small parties. Two leading parties try to entice a small one by simultaneously offering transfers (e.g. government positions, support in other elections, prestige). Through a first-price sealed-bid auction approach, we can analyze the role of two particular factors in alliance formation, namely pragmatism and ideology. Our findings show that, in equilibrium, the favorite party tends to offer lower transfers than the underdog. Furthermore, the closer the leading and the small parties are in terms of ideology, the smaller the transferred amount. When the ideological closeness between the small party and the underdog is sufficiently large—relative to the favorite—the effect may be strong enough to overcome the electoral advantage of the favorite.

The beauty of Dutch: Bidding behavior in combinatorial first-price procurement auctions

Ex-post split-award auctions are a frequently used form of combinatorial auction mechanism in practice. The procurement quantity is split into several shares and suppliers can submit bids on separate shares as well as on the entire quantity. Markets with diseconomies of scale are wide-spread, but strategically challenging. In a game-theoretical equilibrium analysis, Kokott et al. (2019) have recently shown that in contrast to single-object auctions, there is no strategic equivalence between first-price sealed-bid (FPSB) and Dutch combinatorial auctions. The FPSB auctions are characterized by efficient and inefficient equilibria while the Dutch auctions only possess efficient equilibria. We report the results of extensive laboratory experiments and show that the theory explains the bid data surprisingly well. Importantly, a compound Dutch auction format weakly outperforms the wide-spread combinatorial first-price sealed-bid auction in efficiency and total procurement costs. The results provide guidance for procurement managers in the field.

Decentralized Transactive Energy for Flexible Resources in Distribution Systems

The increasing penetration of proactive agents in electric power distribution systems calls for mechanisms to coordinate their trading activities. The commonly employed centralized and distributed methods for supply-demand coordination are not only limited by hardware requirements but also restrictive for active participation of the market agents. This paper proposes a novel decentralized transactive coordination framework that allows participants to bid and clear transactions via a bilateral interaction process. The framework is based on 1) power consumption flexibility individually reported by demand agents using model-predictive control, 2) bilateral supply-side bidding individually determined by the supply agents using a Markowitz Portfolio Optimization model, and 3) individual simultaneous clearing of transactions by demand agents based on second-price sealed-bid auctions. The suppliers bid in the market to achieve desired returns while minimizing their risks. The demand agents harness their demand flexibility by competitively clearing the supplier bids. Unlike traditional approaches, the proposed framework does not require master nodes to orchestrate transactions and, therefore, facilitates massive participation of market agents. Simulation cases demonstrate that the proposed framework successfully performs the market function for bilateral transactions among thousands of proactive agents.

Common Values, Unobserved Heterogeneity, and Endogenous Entry in US Offshore Oil Lease Auctions

Although an auction of drilling rights is often cited as an example of common values, formal evidence has been limited by the problem of auction-level unobserved heterogeneity. We develop an empirical approach for first-price sealed-bid auctions with affiliated values, unobserved heterogeneity, and endogenous bidder entry. We show that important features of the model are nonparametrically identified and apply a semiparametric estimation approach to data from US offshore oil and gas lease auctions. We find that common values, affiliated private information, and unobserved heterogeneity are all present. Failing to account for unobserved heterogeneity obscures the evidence of common values. We examine implications of our estimates for the interaction between affiliation, the winner’s curse, the auction rules, and the number of bidders in determining the aggressiveness of bidding and seller revenue.