High accuracy android malware detection using ensemble learning

With over 50 billion downloads and more than 1.3 million apps in Google’s official market, Android has continued to gain popularity amongst smartphone users worldwide. At the same time there has been a rise in malware targeting the platform, with more recent strains employing highly sophisticated detection avoidance techniques. As traditional signature based methods become less potent in detecting unknown malware, alternatives are needed for timely zero-day discovery. Thus this paper proposes an approach that utilizes ensemble learning for Android malware detection. It combines advantages of static analysis with the efficiency and performance of ensemble machine learning to improve Android malware detection accuracy. The machine learning models are built using a large repository of malware samples and benign apps from a leading antivirus vendor. Experimental results and analysis presented shows that the proposed method which uses a large feature space to leverage the power of ensemble learning is capable of 97.3 % to 99% detection accuracy with very low false positive rates.

Android Malware Detection: an Eigenspace Analysis Approach

The battle to mitigate Android malware has become more critical with the emergence of new strains incorporating increasingly sophisticated evasion techniques, in turn necessitating more advanced detection capabilities. Hence, in this paper we propose and evaluate a machine learning based approach based on eigenspace analysis for Android malware detection using features derived from static analysis characterization of Android applications. Empirical evaluation with a dataset of real malware and benign samples show that detection rate of over 96% with a very low false positive rate is achievable using the proposed method.

A pre-embedding immunogold approach for detection of synaptic endocytic proteins in situ

During the past decade, many molecular components of clathrin-mediated endocytosis have been identified and proposed to play various hypothetical roles in the process [Nat. Rev. Neurosci. 1 (2000) 161; Nature 422 (2003) 37]. One limitation to the evaluation of these hypotheses is the efficiency and resolution of immunolocalization protocols currently in use. In order to facilitate the evaluation of these hypotheses and to understand more fully the molecular mechanisms of clathrin-mediated endocytosis, we have developed a protocol allowing enhanced and reliable subcellular immunolocalization of proteins in synaptic endocytic zones in situ. Synapses established by giant reticulospinal axons in lamprey are used as a model system for these experiments. These axons are unbranched and reach up to 80-100 microm in diameter. Synaptic active zones and surrounding endocytic zones are established on the surface of the axonal cylinder. To provide access for antibodies to the sites of synaptic vesicle recycling, axons are lightly fixed and cut along their longitudinal axis. To preserve the ultrastructure of the synaptic endocytic zone, antibodies are applied without the addition of detergents. Opened axons are incubated with primary antibodies, which are detected with secondary antibodies conjugated to gold particles. Specimens are then post-fixed and processed for electron microscopy. This approach allows preservation of the ultrastructure of the endocytic sites during immunolabeling procedures, while simultaneously achieving reliable immunogold detection of proteins on endocytic intermediates. To explore the utility of this approach, we have investigated the localization of a GTPase, dynamin, on clathrin-coated intermediates in the endocytic zone of the lamprey giant synapse. Using the present immunogold protocol, we confirm the presence of dynamin on late stage coated pits [Nature 422 (2003) 37] and also demonstrate that dynamin is recruited to the coat of endocytic intermediates from the very early stages of the clathrin coat formation. Thus, our experiments show that the current pre-embedding immunogold method is a useful experimental tool to study the molecular mechanisms of synaptic vesicle recycling.

Endoscopic tri-modal imaging improves detection of gastric intestinal metaplasia among a high-risk patient population in Singapore

BACKGROUND: Detection of pre-neoplastic gastric mucosal changes and early gastric cancer (EGC) by white-light endoscopy (WLE) is often difficult. In this study we investigated whether combined autofluorescence imaging (AFI) and narrow band imaging (NBI) can improve detection of pre-neoplastic lesions and early gastric cancer in high-risk patients.

PATIENTS AND METHODS: Chinese patients who were 50-years-old or above with dyspepsia were examined by both high-resolution WLE and combined AFI followed by NBI (AFI-NBI), consecutively in a prospective randomized cross-over setting, by two experienced endoscopists. The primary outcome was diagnostic ability of the two methods for patients with pre-neoplastic lesions such as intestinal metaplasia (IM) and mucosal atrophy.

RESULTS: Sixty-five patients were recruited. One patient with large advanced gastric cancer was found and excluded from the analysis. Among the remaining 64 patients, 38 (59%) had IM; of these, 26 (68%) were correctly identified by AFI-NBI (sensitivity 68%, specificity 23%) and only 13 (34%) by WLE (sensitivity 34%, specificity 65%). AFI-NBI detected more patients with IM than did WLE (p=0.011). Thirty-one patients (48%) had mucosal atrophy. Ten patients (32%) were identified by AFI-NBI (sensitivity 32%, specificity 79%) and four patients (13%) by WLE (sensitivity 13%, specificity 88%) (p=0.100). No dysplasia or EGC was found.

CONCLUSION: AFI-NBI identified significantly more patients with IM than did WLE. Our result warrants further studies to define the role of combined AFI-NBI endoscopy for detection of precancerous conditions.

Validation of a high-throughput immunobead array technique for multiplex detection of three foodborne pathogens in chicken products

This study rigorously evaluated a previously developed immunobead array method to simultaneously detect three important foodborne pathogens, Campylobacter jejuni, Listeria monocytogenes, and Salmonella spp., for its actual application in routine food testing. Due to the limitation of the detection limit of the developed method, an enrichment step was included in this study by using Campylobacter Enrichment Broth for C. jejuni and Universal Pre-enrichment Broth for L. monocytogenes and Salmonella spp.. The findings show that the immunobead array method was capable of detecting as low as 1 CFU of the pathogens spiked in the culture media after being cultured for 24 hours for all three pathogens. The immunobead array method was further evaluated for its pathogen detection capabilities in ready-to-eat (RTE) and ready-to-cook (RTC) chicken samples and proven to be able to detect as low as 1 CFU of the pathogens spiked in the food samples after being cultured for 24 hours in the case of Salmonella spp., and L. monocytogenes and 48 hours in the case of C. jejuni. The method was subsequently validated with three types of chicken products (RTE, n=30; RTC, n=20; raw chicken, n=20) and was found to give the same results as the conventional plating method. Our findings demonstrated that the previously developed immunobead array method could be used for actual food testing with minimal enrichment period of only 52 hours, whereas the conventional ISO protocols for the same pathogens take 90-144 hours. The immunobead array was therefore an inexpensive, rapid and simple method for the food testing.

A validated UPLC–MS/MS method for the surveillance of ten aquatic biotoxins in European brackish and freshwater systems

Over the past few decades, there has been an increased frequency and duration of cyanobacterial Harmful Algal Blooms (HABs) in freshwater systems globally. These can produce secondary metabolites called cyanotoxins, many of which are hepatotoxins, raising concerns about repeated exposure through ingestion of contaminated drinking water or food or through recreational activities such as bathing/ swimming. An ultra-performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS) multi-toxin method has been developed and validated for freshwater cyanotoxins; microcystins-LR, -YR, -RR, -LA, -LY and -LF, nodularin, cylindrospermopsin, anatoxin-a and the marine diatom toxin domoic acid. Separation was achieved in around 9 min and dual SPE was incorporated providing detection limits of between 0.3 and 5.6 ng/L of original sample. Intra- and inter-day precision analysis showed relative
standard deviations (RSD) of 1.2–9.6% and 1.3–12.0% respectively. The method was applied to the analysis of aquatic samples (n = 206) from six European countries. The main class detected were the hepatotoxins; microcystin-YR (n = 22), cylindrospermopsin (n = 25), microcystin-RR (n = 17), microcystin-LR (n = 12), microcystin-LY (n = 1), microcystin-LF (n = 1) and nodularin (n = 5). For microcystins, the levels detected ranged from 0.001 to 1.51 mg/L, with two samples showing combined levels above the guideline set by the WHO of 1 mg/L for microcystin-LR. Several samples presented with multiple toxins indicating the potential for synergistic effects and possibly enhanced toxicity. This is the first published pan European survey of freshwater bodies for multiple biotoxins, including two identified for the first time; cylindrospermopsin in Ireland and nodularin in Germany, presenting further incentives for improved monitoring and development of strategies to mitigate human exposure.

Patterns and predictors of help-seeking contacts with health services and general practitioner detection of suicidality prior to suicide: a cohort analysis of suicides occurring over a two-year period

Background: Contact with primary care and psychiatric services prior to suicide may be considerable, presenting
opportunities for intervention. However, there is scant knowledge on the frequency, nature and determinants of
contact.
Method: Retrospective cohort study-an analysis of deaths recorded as suicide by the Northern Ireland Coroner’s
Office linked with data from General Practice patient records over a 2 year period
Results: Eighty-seven per cent of suicides were in contact with General Practice services in the 12 months before
suicide. The frequency of contact with services was considerable, particularly among patients with a common
mental disorder or substance misuse problems. A diagnosis of psychiatric problems was absent in 40 % of suicides.
Excluding suicide attempts, the main predictors of a noted general practitioner concern for patient suicidality are
male gender, frequency of consultations, diagnosis of mental illness and substance misuse.
Conclusions: Despite widespread and frequent contact, a substantial proportion of suicidal people were
undiagnosed and untreated for mental health problems. General Practitioner alertness to suicidality may be too
narrowly focused.

Real-Time Multiple Event Detection and Classification Using Moving Window PCA

This paper proposes a method for the detection and classification of multiple events in an electrical power system in real-time, namely; islanding, high frequency events (loss of load) and low frequency events (loss of generation). This method is based on principal component analysis of frequency measurements and employs a moving window approach to combat the time-varying nature of power systems, thereby increasing overall situational awareness of the power system. Numerical case studies using both real data, collected from the UK power system, and simulated case studies, constructed using DigSilent PowerFactory, for islanding events, as well as both loss of load and generation dip events, are used to demonstrate the reliability of the proposed method.