An Innovative Simulation Environment for Cross-Domain Policy Enforcement

Policy-based management is necessary for cross-domain organization collaborations and system integrations. In reality different systems from different organizations or domains have very different high-level policy representations and low-level enforcement mechanisms. To ensure the compatibility and enforceability of one policy set in another domain, a simulation environment is needed prior to actual policy deployment and enforcement code development. The goal of this paper is to propose an enforcement architecture and develop a simulation framework for cross-domain policy enforcement. The entire environment is used to simulate the problem of enforcing policies across domain boundaries when permanent or temporary collaborations have to span multiple domains. The middleware derived from this simulation environment can also be used to generate policy enforcement components directly for permanent integration or temporary interaction

Policy Enforcement for Enterprise System Integration and Interoperability

A poster on a piece of middleware software to assist with enterprise system integration and interoperability

Tracking certificate misissuance in the wild

Certificate Authorities (CAs) are responsible for delegating trust in the TLS Public Key Infrastructure (PKI). Unfortunately, there is a long history of CAs abusing this responsibility, either due to negligence or in some cases, falling victim to attacks. As a result, the PKI community has established standards that define the correctness of certificates and how a well managed CA should operate. In this work, we evaluate a systematic approach to identifying whether certificates issued by CAs are compliant with community standards. To this end, we present ZLint, a system that determines whether a certificate is not conformant to standards, i.e., misissued. We find that while misissuance has decreased over time, there is still a long tail of non-conformant CAs in the ecosystem. Further, our results show that certificate misissuance serves as a reasonable indicator for mismanagement and untrustworthiness, suggesting that CAs that misissue more frequently pose a greater threat to security of the PKI. Community efforts thus far to curb these threats have been moderately successful, but the lack of a systematic approach to identifying these problems lets some classes of problems slip through the cracks. We argue that an automated and systematic approach to measuring misissuance in the ecosystem is a necessary first step in solving the problems that lie ahead

Faster Projected GAN: Towards Faster Few-Shot Image Generation

In order to solve the problems of long training time, large consumption of computing resources and huge parameter amount of GAN network in image generation, this paper proposes an improved GAN network model, which is named Faster Projected GAN, based on Projected GAN. The proposed network is mainly focuses on the improvement of generator of Projected GAN. By introducing depth separable convolution (DSC), the number of parameters of the Projected GAN is reduced, the training speed is accelerated, and memory is saved. Experimental results show that on ffhq-1k, art-painting, Landscape and other few-shot image datasets, a 20% speed increase and a 15% memory saving are achieved. At the same time, FID loss is less or no loss, and the amount of model parameters is better controlled. At the same time, significant training speed improvement has been achieved in the small sample image generation task of special scenes such as earthquake scenes with few public datasets.Comment: 9 pages,7 figures,4 table

Bis[4,5-dimethyl-2-(2-pyrid­yl)-1H-imidazole-κ2 N 2,N 3](1H-imidazole-κN 3)copper(II) bis­(perchlorate)

In the title complex, [Cu(C3H4N2)(C10H11N3)2](ClO4)2, the CuII cation has a distorted trigonal-bipyramidal geometry defined by a CuN2N′2N′′ donor set. The imidazole ligand is disordered over two orientations of equal occupancy. Two of the perchlorate ion sites are located on a twofold rotation axis, and one of is disordered over two sites of equal occupancy. In the crystal structure there is a two-dimensional infinite network of hydrogen-bonded mol­ecules parallel to the ab plane

Development of helium turbine loss model based on knowledge transfer with Neural Network and its application on aerodynamic design

Helium turbines are widely used in the Closed Brayton Cycle for power generation and aerospace applications. The primary concerns of designing highly loaded helium turbines include choosing between conventional and contra-rotating designs and the guidelines for selecting design parameters. A loss model serving as an evaluation means is the key to addressing this issue. Due to the property disparities between helium and air, turbines utilizing either as working fluid experience distinct loss mechanisms. Consequently, directly applying gas turbine experience to the design of helium turbines leads to inherent inaccuracies. A helium turbine loss model is developed by combining knowledge transfer and the Neural Network method to accurately predict performance at design and off-design points. By utilizing the loss model, design parameter selection guidelines for helium turbines are obtained. A comparative analysis is conducted of conventional and contra-rotating helium turbine designs. Results show that the prediction errors of the loss model are below 0.5% at over 90% of test samples, surpassing the accuracy achieved by the gas turbine loss model. Design parameter selection guidelines for helium turbines differ significantly from those based on gas turbine experience. The contra-rotating helium turbine design exhibits advantages in size, weight, and aerodynamic performance