A semantic backdoor attack against Graph Convolutional Networks

Graph convolutional networks (GCNs) have been very effective in addressing the issue of various graph-structured related tasks, such as node classification and graph classification. However, recent research has shown that GCNs are vulnerable to a new type of threat called a backdoor attack, where the adversary can inject a hidden backdoor into GCNs so that the attacked model performs well on benign samples, but its prediction will be maliciously changed to the attacker-specified target label if the hidden backdoor is activated by the attacker-defined trigger. In this paper, we investigate whether such semantic backdoor attacks are possible for GCNs and propose a semantic backdoor attack against GCNs (SBAG) under the context of graph classification to reveal the existence of this security vulnerability in GCNs. SBAG uses a certain type of node in the samples as a backdoor trigger and injects a hidden backdoor into GCN models by poisoning training data. The backdoor will be activated, and the GCN models will give malicious classification results specified by the attacker even on unmodified samples as long as the samples contain enough trigger nodes. We evaluate SBAG on four graph datasets. The experimental results indicate that SBAG can achieve attack success rates of approximately 99.9% and over 82% for two kinds of attack samples, respectively, with poisoning rates of less than 5%

Band-to-Band Misregistration of the Images of MODIS On-Board Calibrators and Its Impact to Calibration

The MODIS instruments aboard Terra and Aqua satellites are radiometrically calibrated on-orbit with a set of onboard calibrators (OBC) including a solar diffuser (SD), a blackbody (BB) and a space view (SV) port through which the detectors can view the dark space. As a whisk-broom scanning spectroradiometer, thirty-six MODIS spectral bands are assembled in the along-scan direction on four focal plane assemblies (FPA). These bands capture images of the same target sequentially with the motion of a scan mirror. Then the images are co-registered on board by delaying appropriate band dependent amount of time depending on the band locations on the FPA. While this co-registration mechanism is functioning well for the "far field" remote targets such as Earth view (EV) scenes or the Moon, noticeable band-to-band misregistration in the along-scan direction has been observed for near field targets, in particular the OBCs. In this paper, the misregistration phenomenon is presented and analyzed. It is concluded that the root cause of the misregistration is that the rotating element of the instrument, the scan mirror, is displaced from the focus of the telescope primary mirror. The amount of the misregistration is proportional to the band location on the FPA and is inversely proportional to the distance between the target and the scan mirror. The impact of this misregistration to the calibration of MODIS bands is discussed. In particular, the calculation of the detector gain coefficient m1 of bands 8-16 (412 nm 870 nm) is improved by up to 1.5% for Aqua MODIS

Determination of interfacial heat transfer coefficient and its application in high pressure die casting process

In this paper, the research progress of the interfacial heat transfer in high pressure die casting (HPDC) is reviewed. Results including determination of the interfacial heat transfer coefficient (IHTC), influence of casting thickness, process parameters and casting alloys on the IHTC are summarized and discussed. A thermal boundary condition model was developed based on the two correlations: (a) IHTC and casting solid fraction and (b) IHTC peak value and initial die surface temperature. The boundary model was then applied during the determination of the temperature field in HPDC and excellent agreement was found

On-Orbit Lunar Modulation Transfer Function Measurements for the Moderate Resolution Imaging Spectroradiometer

Spatial quality of an imaging sensor can be estimated by evaluating its modulation transfer function (MTF) from many different sources such as a sharp edge, a pulse target, or bar patterns with different spatial frequencies. These well-defined targets are frequently used for prelaunch laboratory tests, providing very reliable and accurate MTF measurements. A laboratory-quality edge input source was included in the spatial-mode operation of the Spectroradiometric Calibration Assembly (SRCA), which is one of the onboard calibrators of the Moderate Resolution Imaging Spectroradiometer (MODIS). Since not all imaging satellites have such an instrument, SRCA MTF estimations can be used as a reference for an on-orbit lunar MTF algorithm and results. In this paper, the prelaunch spatial quality characterization process from the Integrated Alignment Collimator and SRCA is briefly discussed. Based on prelaunch MTF calibration using the SRCA, a lunar MTF algorithm is developed and applied to the lifetime on-orbit Terra and Aqua MODIS lunar collections. In each lunar collection, multiple scan-directionMoon-to-background transition profiles are aligned by the subpixel edge locations from a parametric Fermi function fit. Corresponding accumulated edge profiles are filtered and interpolated to obtain the edge spread function (ESF). The MTF is calculated by applying a Fourier transformation on the line spread function through a simple differentiation of the ESF. The lifetime lunar MTF results are analyzed and filtered by a relationship with the Sun-Earth-MODIS angle. Finally, the filtered lunarMTF values are compared to the SRCA MTF results. This comparison provides the level of accuracy for on-orbit MTF estimations validated through prelaunch SRCA measurements. The lunar MTF values had larger uncertainty than the SRCA MTF results; however, the ratio mean of lunarMTF fit and SRCA MTF values is within 2% in the 250- and 500-m bands. Based on the MTF measurement uncertainty range, the suggested lunar MTF algorithm can be applied to any on-orbit imaging sensor with lunar calibration capability