A Dynamical Graph Prior for Relational Inference

Relational inference aims to identify interactions between parts of a dynamical system from the observed dynamics. Current state-of-the-art methods fit a graph neural network (GNN) on a learnable graph to the dynamics. They use one-step message-passing GNNs -- intuitively the right choice since non-locality of multi-step or spectral GNNs may confuse direct and indirect interactions. But the \textit{effective} interaction graph depends on the sampling rate and it is rarely localized to direct neighbors, leading to local minima for the one-step model. In this work, we propose a \textit{dynamical graph prior} (DYGR) for relational inference. The reason we call it a prior is that, contrary to established practice, it constructively uses error amplification in high-degree non-local polynomial filters to generate good gradients for graph learning. To deal with non-uniqueness, DYGR simultaneously fits a ``shallow'' one-step model with shared graph topology. Experiments show that DYGR reconstructs graphs far more accurately than earlier methods, with remarkable robustness to under-sampling. Since appropriate sampling rates for unknown dynamical systems are not known a priori, this robustness makes DYGR suitable for real applications in scientific machine learning

Cyber-Syndrome: Concept, Theoretical Characterization, and Control Mechanism

The prevalence of social media and mobile computing has led to intensive user engagement in the emergent Cyber-Physical-Social-Thinking (CPST) space. However, the easy access, the lack of governance, and excessive use has generated a raft of new behaviors within CPST, which affects users' physical, social, and mental states. In this paper, we conceive the Cyber-Syndrome concept to denote the collection of cyber disorders due to excessive or problematic Cyberspace interactions based on CPST theories. Then we characterize the Cyber-Syndrome concept in terms of Maslow's theory of Needs, from which we establish an in-depth theoretical understanding of Cyber-Syndrome from its etiology, formation, symptoms, and manifestations. Finally, we propose an entropy-based Cyber-Syndrome control mechanism for its computation and management. The goal of this study is to give new insights into this rising phenomenon and offer guidance for further research and development.<br/

Secure Mobile Agents in Electronic Commerce by Using Undetachable Signatures from Pairings

It is expect that mobile agents technology will bring significant benefits to electronic commerce. But security issues, especially threats from malicious hosts, become a great obstacle of widespread deployment of applications in electronic commerce based on mobile agents technology. Undetachable digital signature is a category of digital signatures to secure mobile agents against malicious hosts. An undetachable signature scheme by using encrypted functions from bilinear pairings was proposed in this paper. The security of this scheme base on the computational intractability of discrete logarithm problem and computational Diffe-Hellman problem on gap Diffle-Hellman group. Furthermore, the scheme satisfies all the requirements of a strong non-designated proxy signature i.e. verifiability, strong unforgeability, strong identifiability, strong undeniability and preventions of misuse. An undetachable threshold signature scheme that enable the customer to provide n mobile agents with ‘shares’ of the undetachable signature function is also provided. It is able to provide more reliability than classical undetachable signatures