scholarly journals HAL-Based Resource Manipulation Monitoring on AOSP

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Thien-Phuc Doan ◽  
Jungsoo Park ◽  
Souhwan Jung
Keyword(s):  
Computational Effort ◽  
Coverage Rate ◽  
Malware Analysis ◽  
Rate System ◽  
High Coverage ◽  
Android Malware ◽  
Computational Overhead ◽  
Android Os ◽  
Low Coverage ◽  
High Coverage Rate

Nowadays, Android malware uses sensitive APIs to manipulate an Android device’s resources frequently. Conventional malware analysis uses hooking techniques to detect this harmful behavior. However, this approach is facing many problems, such as low coverage rate and computational overhead. To solve this problem, we proposed HALWatcher, an alternative technique to monitor resource manipulation on Android Open Source Project (AOSP). By modifying Hardware Abstract Layer (HAL) resource accessing interfaces and their implementation, we can embed more monitoring functions at critical methods that are in charge of transferring data between the Hardware Driver and the Framework Layer. Hence, HALWatcher provides a lightweight and high coverage rate system that can perform resource manipulation monitoring for Android OS. In this paper, we prove that the hooking technique is limited in detecting resource manipulation attacks. Besides that, HALWatcher shows an outperform detection rate with a low computational effort.

Research on Some Key Issues of Dynamic Simulation for Workflow Process

2011 ◽  
Vol 311-313 ◽  
pp. 1049-1055
Author(s):  
Li Na Fu ◽  
Ke Gang Hao
Keyword(s):  
Dynamic Simulation ◽  
Process Simulation ◽  
Black Box ◽  
Coverage Rate ◽  
Simulation Environment ◽  
High Coverage ◽  
Path Coverage ◽  
Key Issues ◽  
Simulation Results ◽  
High Coverage Rate

The method of analyzing capability and verifying correctness for workflow process is divided in static check and dynamic simulation. The focus of the paper is to test and analyze workflow process by means of dynamic simulation, further to confirm that a process will do appropriate things at appropriate time by appropriate resources. The paper will research some key issues in process simulation——setting up simulation environment, the algorithm for arranging events in a queue based on path coverage rule, analyzing simulation results. It adopts interactive and non-interactive means and makes use of white-box and black-box methods to test workflow process on the base of high coverage rate. At last the classification, distribution and trend of process defects will be presented by various simulation results.

scholarly journals AndroDFA: Android Malware Classification Based on Resource Consumption

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 326
Author(s):  
Luca Massarelli ◽  
Leonardo Aniello ◽  
Claudio Ciccotelli ◽  
Leonardo Querzoni ◽  
Daniele Ucci ◽  
...  
Keyword(s):  
Detrended Fluctuation Analysis ◽  
Resource Consumption ◽  
Support Vector ◽  
Fluctuation Analysis ◽  
Malware Analysis ◽  
Android Malware ◽  
Android Os ◽  
Mobile Malware ◽  
Key Factor ◽  
Detrended Fluctuation

The vast majority of today’s mobile malware targets Android devices. An important task of malware analysis is the classification of malicious samples into known families. In this paper, we propose AndroDFA (DFA, detrended fluctuation analysis): an approach to Android malware family classification based on dynamic analysis of resource consumption metrics available from the proc file system. These metrics can be easily measured during sample execution. From each malware, we extract features through detrended fluctuation analysis (DFA) and Pearson’s correlation, then a support vector machine is employed to classify malware into families. We provide an experimental evaluation based on malware samples from two datasets, namely Drebin and AMD. With the Drebin dataset, we obtained a classification accuracy of 82%, comparable with works from the state-of-the-art like DroidScribe. However, compared to DroidScribe, our approach is easier to reproduce because it is based on publicly available tools only, does not require any modification to the emulated environment or Android OS, and by design, can also be used on physical devices rather than exclusively on emulators. The latter is a key factor because modern mobile malware can detect the emulated environment and hide its malicious behavior. The experiments on the AMD dataset gave similar results, with an overall mean accuracy of 78%. Furthermore, we made the software we developed publicly available, to ease the reproducibility of our results.

scholarly journals Genotyping Strategies Using ddRAD Sequencing in Farmed Arctic Charr (Salvelinus alpinus)

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 899
Author(s):  
Fotis Pappas ◽  
Christos Palaiokostas
Keyword(s):  
Genetic Diversity ◽  
Salvelinus Alpinus ◽  
Arctic Charr ◽  
Cost Effective ◽  
Limiting Factors ◽  
Phenotypic Traits ◽  
Production Volume ◽  
High Coverage ◽  
Genomic Relationships ◽  
Low Coverage

Incorporation of genomic technologies into fish breeding programs is a modern reality, promising substantial advances regarding the accuracy of selection, monitoring the genetic diversity and pedigree record verification. Single nucleotide polymorphism (SNP) arrays are the most commonly used genomic tool, but the investments required make them unsustainable for emerging species, such as Arctic charr (Salvelinus alpinus), where production volume is low. The requirement to genotype a large number of animals for breeding practices necessitates cost effective genotyping approaches. In the current study, we used double digest restriction site-associated DNA (ddRAD) sequencing of either high or low coverage to genotype Arctic charr from the Swedish national breeding program and performed analytical procedures to assess their utility in a range of tasks. SNPs were identified and used for deciphering the genetic structure of the studied population, estimating genomic relationships and implementing an association study for growth-related traits. Missing information and underestimation of heterozygosity in the low coverage set were limiting factors in genetic diversity and genomic relationship analyses, where high coverage performed notably better. On the other hand, the high coverage dataset proved to be valuable when it comes to identifying loci that are associated with phenotypic traits of interest. In general, both genotyping strategies offer sustainable alternatives to hybridization-based genotyping platforms and show potential for applications in aquaculture selective breeding.

High throughput crop genome genotyping by a combination of pool next generation sequencing and haplotype-based data processing

2021 ◽  
Author(s):  
Michael Schneider ◽  
Asis Shrestha ◽  
Agim Ballvora ◽  
Jens Leon
Keyword(s):  
Next Generation Sequencing ◽  
Allele Frequency ◽  
Frequency Estimation ◽  
Whole Genome ◽  
Next Generation ◽  
Conservation Genomics ◽  
High Coverage ◽  
Allele Frequency Estimation ◽  
Low Coverage ◽  
Generation Sequencing

Abstract BackgroundThe identification of environmentally specific alleles and the observation of evolutional processes is a goal of conservation genomics. By generational changes of allele frequencies in populations, questions regarding effective population size, gene flow, drift, and selection can be addressed. The observation of such effects often is a trade-off of costs and resolution, when a decent sample of genotypes should be genotyped for many loci. Pool genotyping approaches can derive a high resolution and precision in allele frequency estimation, when high coverage sequencing is utilized. Still, pool high coverage pool sequencing of big genomes comes along with high costs.ResultsHere we present a reliable method to estimate a barley population’s allele frequency at low coverage sequencing. Three hundred genotypes were sampled from a barley backcross population to estimate the entire population’s allele frequency. The allele frequency estimation accuracy and yield were compared for three next generation sequencing methods. To reveal accurate allele frequency estimates on a low coverage sequencing level, a haplotyping approach was performed. Low coverage allele frequency of positional connected single polymorphisms were aggregated to a single haplotype allele frequency, resulting in two to 271 times higher depth and increased precision. We compared different haplotyping tactics, showing that gene and chip marker-based haplotypes perform on par or better than simple contig haplotype windows. The comparison of multiple pool samples and the referencing against an individual sequencing approach revealed whole genome pool resequencing having the highest correlation to individual genotyping (up to 0.97), while transcriptomics and genotyping by sequencing indicated higher error rates and lower correlations.ConclusionUsing the proposed method allows to identify the allele frequency of populations with high accuracy at low cost. This is particularly interesting for conservation genomics in species with big genomes, like barley or wheat. Whole genome low coverage resequencing at 10x coverage can deliver a highly accurate estimation of the allele frequency, when a loci-based haplotyping approach is applied. Using annotated haplotypes allows to capitalize from biological background and statistical robustness.

Effect of Chlorine Atoms for Development of Aluminum Corrosion

2016 ◽  
Vol 879 ◽  
pp. 2170-2174 ◽  
Author(s):  
Junko Yamashita ◽  
Norio Nunomura
Keyword(s):  
Density Functional ◽  
Charge Density Distribution ◽  
High Coverage ◽  
Functional Theory ◽  
Chlorine Atoms ◽  
Structural And Electronic Properties ◽  
Aluminum Corrosion ◽  
Dft Model ◽  
Low Coverage ◽  
Effect Of Chlorine

Computational density functional theory (DFT) model of the adsorption of chlorine atoms onto the perfect Al (111) surface has been performed. The structural and electronic properties of chlorine atoms adsorbed on the surface are investigated within a supercell approach for chlorine coverages of 0.25, 0.33, 0.5 and 1 ML respectively. It is found that the adsorbates prefer on-top sites over bridge, hcp and fcc sites in low coverage while fcc sites in high coverage, and the binding energy decrease with increase of coverage due to the interactions of chlorine atoms. The discussion of geometrical and electronic analysis by plotting differential charge density distribution and projected density of states (PDOS) are presented.

scholarly journals Accurate allele frequencies from ultra-low coverage pool-seq samples in evolve-and-resequence experiments

2018 ◽  
Author(s):  
Susanne Tilk ◽  
Alan Bergland ◽  
Aaron Goodman ◽  
Paul Schmidt ◽  
Dmitri Petrov ◽  
...  
Keyword(s):  
Allele Frequency ◽  
Model Organism ◽  
Software Tool ◽  
Allele Frequencies ◽  
Model Organisms ◽  
Sequencing Data ◽  
High Coverage ◽  
Next Generation Sequencing Technology ◽  
Low Coverage ◽  
Pooled Samples

AbstractEvolve-and-resequence (E+R) experiments leverage next-generation sequencing technology to track the allele frequency dynamics of populations as they evolve. While previous work has shown that adaptive alleles can be detected by comparing frequency trajectories from many replicate populations, this power comes at the expense of high-coverage (>100x) sequencing of many pooled samples, which can be cost-prohibitive. Here, we show that accurate estimates of allele frequencies can be achieved with very shallow sequencing depths (<5x) via inference of known founder haplotypes in small genomic windows. This technique can be used to efficiently estimate frequencies for any number of bi-allelic SNPs in populations of any model organism founded with sequenced homozygous strains. Using both experimentally-pooled and simulated samples of Drosophila melanogaster, we show that haplotype inference can improve allele frequency accuracy by orders of magnitude for up to 50 generations of recombination, and is robust to moderate levels of missing data, as well as different selection regimes. Finally, we show that a simple linear model generated from these simulations can predict the accuracy of haplotype-derived allele frequencies in other model organisms and experimental designs. To make these results broadly accessible for use in E+R experiments, we introduce HAF-pipe, an open-source software tool for calculating haplotype-derived allele frequencies from raw sequencing data. Ultimately, by reducing sequencing costs without sacrificing accuracy, our method facilitates E+R designs with higher replication and resolution, and thereby, increased power to detect adaptive alleles.

Path coverage enhancement in wireless sensor networks based on CVT model

2021 ◽  
pp. 1-13
Author(s):  
Guangxu Yu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Detection Probability ◽  
Coverage Rate ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Current Path ◽  
Coverage Model ◽  
Path Coverage ◽  
Low Coverage

In order to overcome the problems of low detection probability, low coverage uniformity and low coverage of current path coverage enhancement methods in wireless sensor networks, a new path coverage enhancement method based on CVT model is proposed in this paper. Firstly, the node perception model and network coverage model are constructed. On the basis of the node awareness model and network coverage model, CVT model is used to adjust the connection mode, density and location of nodes in wireless sensor networks, so as to improve the coverage performance of nodes in the detection area in wireless sensor networks, and realize the effective enhancement of path coverage in wireless sensor networks. Experimental results show that, compared with the traditional methods, the proposed method has high detection probability, high coverage uniformity and coverage rate, and the highest coverage rate reaches 97%, which has higher practical application performance.

scholarly journals MobiSentry: Towards Easy and Effective Detection of Android Malware on Smartphones

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Bingfei Ren ◽  
Chuanchang Liu ◽  
Bo Cheng ◽  
Jie Guo ◽  
Junliang Chen
Keyword(s):  
State Of The Art ◽  
Classification Algorithms ◽  
Defense System ◽  
Android Malware ◽  
Malware Classification ◽  
Android Os ◽  
Comprehensive Performance ◽  
Supervised Classifiers ◽  
Expert Analysis ◽  
Time Overhead

Android platform is increasingly targeted by attackers due to its popularity and openness. Traditional defenses to malware are largely reliant on expert analysis to design the discriminative features manually, which are easy to bypass with the use of sophisticated detection avoidance techniques. Therefore, more effective and easy-to-use approaches for detection of Android malware are in demand. In this paper, we present MobiSentry, a novel lightweight defense system for malware classification and categorization on smartphones. Besides conventional static features such as permissions and API calls, MobiSentry also employs the N-gram features of operation codes (n-opcode). We present two comprehensive performance comparisons among several state-of-the-art classification algorithms with multiple evaluation metrics: (1) malware detection on 184,486 benign applications and 21,306 malware samples, and (2) malware categorization on DREBIN, the largest labeled Android malware datasets. We utilize the ensemble of these supervised classifiers to design MobiSentry, which outperforms several related approaches and gives a satisfying performance in the evaluation. Furthermore, we integrate MobiSentry with Android OS that enables smartphones with Android to extract features and to predict whether the application is benign or malicious. Experimental results on real smartphones show that users can easily and effectively protect their devices against malware through this system with a small run-time overhead.

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