0000000000326412
AUTHOR
Mohammad Sadeq Dousti
showing 2 related works from this author
Neural Networks, Inside Out: Solving for Inputs Given Parameters (A Preliminary Investigation)
2021
Artificial neural network (ANN) is a supervised learning algorithm, where parameters are learned by several back-and-forth iterations of passing the inputs through the network, comparing the output with the expected labels, and correcting the parameters. Inspired by a recent work of Boer and Kramer (2020), we investigate a different problem: Suppose an observer can view how the ANN parameters evolve over many iterations, but the dataset is oblivious to him. For instance, this can be an adversary eavesdropping on a multi-party computation of an ANN parameters (where intermediate parameters are leaked). Can he form a system of equations, and solve it to recover the dataset?
Moderated Redactable Blockchains: A Definitional Framework with an Efficient Construct
2020
Blockchain is a multiparty protocol to reach agreement on the order of events, and to record them consistently and immutably without centralized trust. In some cases, however, the blockchain can benefit from some controlled mutability. Examples include removing private information or unlawful content, and correcting protocol vulnerabilities which would otherwise require a hard fork. Two approaches to control the mutability are: moderation, where one or more designated administrators can use their private keys to approve a redaction, and voting, where miners can vote to endorse a suggested redaction. In this paper, we first present several attacks against existing redactable blockchain solut…