R2-D2: ColoR-inspired Convolutional NeuRal Network (CNN)-based AndroiD Malware Detections

The influence of Deep Learning on image identification and natural language processing has attracted enormous attention globally. The convolution neural network that can learn without prior extraction of features fits well in response to the rapid iteration of Android malware. The traditional solution for detecting Android malware requires continuous learning through pre-extracted features to maintain high performance of identifying the malware. In order to reduce the manpower of feature engineering prior to the condition of not to extract pre-selected features, we have developed a coloR-inspired convolutional neuRal networks (CNN)-based AndroiD malware Detection (R2-D2) system. The system can convert the bytecode of classes.dex from Android archive file to rgb color code and store it as a color image with fixed size. The color image is input to the convolutional neural network for automatic feature extraction and training. The data was collected from Jan. 2017 to Aug 2017. During the period of time, we have collected approximately 2 million of benign and malicious Android apps for our experiments with the help from our research partner Leopard Mobile Inc. Our experiment results demonstrate that the proposed system has accurate security analysis on contracts. Furthermore, we keep our research results and experiment materials on http://R2D2.TWMAN.ORG.Comment: Verison 2018/11/15, IEEE BigData 2018, Seattle, WA, USA, Dec 10-13, 2018. (Accepted

Data-Driven and Deep Learning Methodology for Deceptive Advertising and Phone Scams Detection

The advance of smartphones and cellular networks boosts the need of mobile advertising and targeted marketing. However, it also triggers the unseen security threats. We found that the phone scams with fake calling numbers of very short lifetime are increasingly popular and have been used to trick the users. The harm is worldwide. On the other hand, deceptive advertising (deceptive ads), the fake ads that tricks users to install unnecessary apps via either alluring or daunting texts and pictures, is an emerging threat that seriously harms the reputation of the advertiser. To counter against these two new threats, the conventional blacklist (or whitelist) approach and the machine learning approach with predefined features have been proven useless. Nevertheless, due to the success of deep learning in developing the highly intelligent program, our system can efficiently and effectively detect phone scams and deceptive ads by taking advantage of our unified framework on deep neural network (DNN) and convolutional neural network (CNN). The proposed system has been deployed for operational use and the experimental results proved the effectiveness of our proposed system. Furthermore, we keep our research results and release experiment material on http://DeceptiveAds.TWMAN.ORG and http://PhoneScams.TWMAN.ORG if there is any update.Comment: 6 pages, TAAI 2017 versio

Tailored design of NKT-stimulatory glycolipids for polarization of immune responses.

Natural killer T (NKT) cell is a distinct population of T lymphocytes that can rapidly release massive amount of Th1 and Th2 cytokines upon the engagement of their T cell receptor with glycolipids presented by CD1d. The secreted cytokines can promote cell-mediated immunity to kill tumor cells and intracellular pathogens, or suppress autoreactive immune cells in autoimmune diseases. Thus, NKT cell is an attractive target for developing new therapeutics to manipulate immune system. The best-known glycolipid to activate NKT cells is α-galactosylceramide (α-GalCer), which has been used as a prototype for designing new NKT stimulatory glycolipids. Many analogues have been generated by modification of the galactosyl moiety, the acyl chain or the phytosphingosine chain of α-GalCer. Some of the analogues showed greater abilities than α-GalCer in polarizing immune responses toward Th1 or Th2 dominance. Among them, several analogues containing phenyl groups in the lipid tails were more potent in inducing Th1-skewed cytokines and exhibited greater anticancer efficacy than α-GalCer. Analyses of the correlation between structure and activity of various α-GalCer analogues on the activation of iNKT cell revealed that CD1d-glycolipid complexes interacted with the same population of iNKT cell expressing similar T-cell receptor Vβ as α-GalCer. On the other hand, those phenyl glycolipids with propensity for Th1 dominant responses showed greater binding avidity and stability than α-GalCer for iNKT T-cell receptor when complexed with CD1d. Thus, it is the avidity and stability of the ternary complexes of CD1d-glycolipid-iNKT TCR that dictate the polarity and potency of immune responses. These findings provide a key to the rationale design of immune modulating glycolipids with desirable Th1/Th2 polarity for clinical application. In addition, elucidation of α-GalCer-induced anergy, liver damage and accumulation of myeloid derived suppressor cells has offered explanation for its lacklustre anti-cancer activities in clinical trials. On other hand, the lack of such drawbacks in glycolipid analogues containing phenyl groups in the lipid tails of α-GalCer coupled with the greater binding avidity and stability of CD1d-glycolipid complex for iNKT T-cell receptor, account for their superior anti-cancer efficacy in tumor bearing mice. Further clinical development of these phenyl glycolipids is warranted

High-Mobility Pentacene-Based Thin-Film Transistors With a Solution-Processed Barium Titanate Insulator

Abstract—Pentacene-based organic thin-film transistors (OTFTs) with solution-processed barium titanate (Ba1.2Ti0.8O3) as a gate insulator are demonstrated. The electrical properties of pentacene-based TFTs show a high field-effect mobility of 8.85 cm2 · V−1 · s−1, a low threshold voltage of −1.89 V, and a low subthreshold slope swing of 310 mV/decade. The chemical composition and binding energy of solution-processed barium titanate thin films are analyzed through X-ray photoelectron spectroscopy. The matching surface energy on the surface of the barium titanate thin film is 43.12 mJ · m−2, which leads to Stranski–Krastanov mode growth, and thus, high mobility is exhibited in pentacene-based TFTs. Index Terms—Barium titanate, high field-effect mobility, high permittivity, organic thin-filmtransistor (OTFT), solution process

Complementary Therapy with Traditional Chinese Medicine for Ischemic Stroke

Stroke has remained the leading cause of morbidity or mortality worldwide over the past decade. Stroke survivors suffer various degrees of disability and also contribute to the large socioeconomic disease burden. Traditional Chinese medicine (TCM) serves as an important alternative or complementary therapy in many countries. This chapter aims to explore the utility of TCM for ischemic stroke, including a review of recent literature on the mechanisms of herbal medicine and acupuncture therapy on ischemic stroke, a summary of clinical trial results for the safety and efficacy of acupuncture, and finally a discussion of acupuncture as a preventive therapy for ischemic stroke in clinical practice. On the basis of these reports, more and more scientific evidences suggest that TCM use was safe for ischemic stroke at acute and subacute stages. Moreover, TCM has benefit for stroke recovery as well as it reduces the likelihood of hospital readmission for cardiovascular or subsequent stroke events