Evading Classifiers by Morphing in the Dark

Learning-based systems have been shown to be vulnerable to evasion through adversarial data manipulation. These attacks have been studied under assumptions that the adversary has certain knowledge of either the target model internals, its training dataset or at least classification scores it assigns to input samples. In this paper, we investigate a much more constrained and realistic attack scenario wherein the target classifier is minimally exposed to the adversary, revealing on its final classification decision (e.g., reject or accept an input sample). Moreover, the adversary can only manipulate malicious samples using a blackbox morpher. That is, the adversary has to evade the target classifier by morphing malicious samples "in the dark". We present a scoring mechanism that can assign a real-value score which reflects evasion progress to each sample based on the limited information available. Leveraging on such scoring mechanism, we propose an evasion method -- EvadeHC -- and evaluate it against two PDF malware detectors, namely PDFRate and Hidost. The experimental evaluation demonstrates that the proposed evasion attacks are effective, attaining $100\%$ evasion rate on the evaluation dataset. Interestingly, EvadeHC outperforms the known classifier evasion technique that operates based on classification scores output by the classifiers. Although our evaluations are conducted on PDF malware classifier, the proposed approaches are domain-agnostic and is of wider application to other learning-based systems

An Application of the Moving Frame Method to Integral Geometry in the Heisenberg Group

We show the fundamental theorems of curves and surfaces in the 3-dimensional Heisenberg group and find a complete set of invariants for curves and surfaces respectively. The proofs are based on Cartan's method of moving frames and Lie group theory. As an application of the main theorems, a Crofton-type formula is proved in terms of p-area which naturally arises from the variation of volume. The application makes a connection between CR geometry and integral geometry

Effects of Light Quality on the Chlorophyll Degradation Pathway in Rice Seedling Leaves

The objective of this study was to investigate the dynamics of chlorophyll (Chl), biosynthetic intermediates (protoporphyrin IX, magnesium protoporphyrin IX, and protochlorophyllide), degradation intermediates [chlorophyllide (Chlide), pheophytin (Phe), and pheophorbide (Pho)], and carotenoids (Car) in leaves of rice seedlings. Two rice varieties, 'Taichung Shen 10' ('TCS10') and 'IR1552', were grown under different light quality conditions controlled by light emitting diodes (LED). Lighting treatments for rice seedlings were included by red (R), blue (B), green (G), and red + blue (RB), with fluorescent lighting (FL) as the control and photosynthetic photon flux density being set at 105 µmol m-2 s-1. The results show that lower levels of Chl and Car in leaves were detected under G lighting, and light quality did not mediate porphyrins in biosynthetic pathways. Rice seedling leaves took Chl→Phe→Pho and Chl→Chlide→Pho as the major and minor degradation routes, respectively. Furthermore, higher Phe/Chlide ratios were observed under G and FL lighting conditions, indicating that green-enriched environments can up-regulate the minor degradation route in leaves

Technical aspects of single-port thoracoscopic surgery for lobectomy

Thoracoscopic Surgery is in common use in routine surgical practice. With the advancement of the various techniques and instruments required, mini wounds and fewer thoracoports become practical in recent years. Here, we report our experience of performing lobectomy with radical lymph node dissection in 3 patients using regular straight endoscopic instruments. We demonstrate the feasibility of such techniques and discuss the key points of effectively performing the procedures. Because of the favorable outcomes, we encourage such procedures to be widely applied in surgical operations of various types