Time-Lock Puzzles from Randomized Encodings

Time-lock puzzles are a mechanism for sending messages "to the future". A sender can quickly generate a puzzle with a solution s that remains hidden until a moderately large amount of time t has elapsed. The solution s should be hidden from any adversary that runs in time significantly less than t, including resourceful parallel adversaries with polynomially many processors. While the notion of time-lock puzzles has been around for 22 years, there has only been a single candidate proposed. Fifteen years ago, Rivest, Shamir and Wagner suggested a beautiful candidate time-lock puzzle based on the assumption that exponentiation modulo an RSA integer is an "inherently sequential" computation. We show that various flavors of randomized encodings give rise to time-lock puzzles of varying strengths, whose security can be shown assuming the mere existence of non-parallelizing languages, which are languages that require circuits of depth at least t to decide, in the worst-case. The existence of such languages is necessary for the existence of time-lock puzzles. We instantiate the construction with different randomized encodings from the literature, where increasingly better efficiency is obtained based on increasingly stronger cryptographic assumptions, ranging from one-way functions to indistinguishability obfuscation. We also observe that time-lock puzzles imply one-way functions, and thus the reliance on some cryptographic assumption is necessary. Finally, generalizing the above, we construct other types of puzzles such as proofs of work from randomized encodings and a suitable worst-case hardness assumption (that is necessary for such puzzles to exist)

Visual analytics for supply network management: system design and evaluation

We propose a visual analytic system to augment and enhance decision-making processes of supply chain managers. Several design requirements drive the development of our integrated architecture and lead to three primary capabilities of our system prototype. First, a visual analytic system must integrate various relevant views and perspectives that highlight different structural aspects of a supply network. Second, the system must deliver required information on-demand and update the visual representation via user-initiated interactions. Third, the system must provide both descriptive and predictive analytic functions for managers to gain contingency intelligence. Based on these capabilities we implement an interactive web-based visual analytic system. Our system enables managers to interactively apply visual encodings based on different node and edge attributes to facilitate mental map matching between abstract attributes and visual elements. Grounded in cognitive fit theory, we demonstrate that an interactive visual system that dynamically adjusts visual representations to the decision environment can significantly enhance decision-making processes in a supply network setting. We conduct multi-stage evaluation sessions with prototypical users that collectively confirm the value of our system. Our results indicate a positive reaction to our system. We conclude with implications and future research opportunities.The authors would like to thank the participants of the 2015 Businessvis Workshop at IEEE VIS, Prof. Benoit Montreuil, and Dr. Driss Hakimi for their valuable feedback on an earlier version of the software; Prof. Manpreet Hora for assisting with and Georgia Tech graduate students for participating in the evaluation sessions; and the two anonymous reviewers for their detailed comments and suggestions. The study was in part supported by the Tennenbaum Institute at Georgia Tech Award # K9305. (K9305 - Tennenbaum Institute at Georgia Tech Award)Accepted manuscrip