A multi-designated verifier signature (MDVS) is a digital signature that empowers a signer to designate specific verifiers capable of verifying signatures. Notably, designated verifiers are allowed to not only verify signatures but also simulate “fake” signatures indistinguishable from real ones produced by the original signer. Since this property is useful for realizing off-the-record (i.e., deniable) communication in group settings, MDVS is attracting attention in secure messaging. Recently, Damgård et al. (TCC'20) and Chakraborty et al. (EUROCRYPT'23) have introduced new MDVS schemes, allowing a subset of designated verifiers to simulate signatures in contrast to the conventional one, which requires all designated verifiers for signature simulation. They also define a stronger notion of security for them. This work delves into this new MDVS and offers a comprehensive formalization. We identify all possible security levels of MDVS schemes in subset simulations and prove that some of them are not feasible. Furthermore, we demonstrate that MDVS schemes meeting the security notion defined by Chakraborty et al. imply IND-CCA secure public-key encryption schemes. Beyond formalization, we present new constructions of MDVS schemes in subset simulation. Notably, we introduce a new construction of strongly secure MDVS schemes based on ring signatures and public-key encryption, accompanied by a generic conversion for achieving consistency through non-interactive zero-knowledge arguments. Finally, we evaluate the efficiency of our MDVS schemes in classical and post-quantum settings, showing their practicality.

Demand Response (DR) has been extensively studied as one of the important features of smart grid. The DR strategies can be grouped into two categories, one is incentive-based DR and the other is pricing-based DR. Our work focuses on DR involving both pricing factor and incentive factor using scoring rule. In the literature, several DR mechanisms have been proposed, however, most studies have not focused on the cooperation among consumers although it is important to devise an efficient and stable DR. In this paper, we propose a cooperative demand response mechanism by using a truthful allocation mechanism with scoring rule. The brief ideas of our model are the following: the consumers will be rewarded a discount on the price to measure up how well they predict demand shift. A reward mechanism is based on a strictly proper scoring rule. This mechanism is applied between consumer agents (CA) to Cooperative Demand Response System (CDRS) and Generation Company (GENCO). The proposed mechanism is tested on real data provided by Chubu Electric Power Company and we show that this mechanism is capable of reducing peak demand.

Multi-issue negotiation protocols are an important field of study because real-world negotiation problems are often complex and involve multiple issues. Although much previous work has only addressed linear utility function, that is, simple negotiations involving independent issues, recently, non-linear utility functions for complex negotiations involing interdependent issues have gained attention. Most studies, however, do not focus on the changes in utility space over time. In economic theory, it is often assumed that the utility function changes dynamically over time. It is important to seek the Pareto front, which refers to the set of Pareto optimal points, in negotiation problems. Therefore, in this paper we propose a complex utility space that changes over time and a negotiation mechanism in which the mediator takes the lead in negotiation based on the genetic algorithm (GA). The experimental results show that our approach is suitable for utility that dynamically changes over time, and finds and follows the Pareto front effectively.