An Empirical Study on the Effectiveness of Adversarial Examples in Malware Detection

Antivirus vendors and the research community employ Machine Learning(ML)or Deep Learning(DL)-based static analysis techniques for efficient identification of new threats,given the continual emergence of novel malware variants.On the other hand,numerous researchers have reported that Adversarial Examples(AEs),generated by manipulating previously detected malware,can successfully evade ML/DL-based classifiers.Commercial antivirus systems,in particular,have been identified as vulnerable to such AEs.This paper firstly focuses on conducting black-box attacks to circumvent ML/DL-based malware classifiers.Our attack method utilizes seven different perturbations,including Overlay Append,Section Append,and Break Checksum,capitalizing on the ambiguities present in the PE format,as previously employed in evasion attack research.By directly applying the perturbation techniques to PE binaries,our attack method eliminates the need to grapple with the problem-feature space dilemma,a persistent challenge in many evasion attack studies.Being a black-box attack,our method can generate AEs that successfully evade both DL-based and ML-based classifiers.Also,AEs generated by the attack method retain their executability and malicious behavior,eliminating the need for functionality verification.Through thorogh evaluations,we confirmed that the attack method achieves an evasion rate of 65.6%against well-known ML-based malware detectors and can reach a remarkable 99%evasion rate against well-known DL-based malware detectors.Furthermore,our AEs demonstrated the capability to bypass detection by 17%of vendors out of the 64 on VirusTotal(VT).In addition,we propose a defensive approach that utilizes Trend Locality Sensitive Hashing(TLSH)to construct a similarity-based defense model.Through several experiments on the approach,we verified that our defense model can effectively counter AEs generated by the perturbation techniques.In conclusion,our defense model alleviates the limitation of the most promising defense method,adversarial training,which is only effective against the AEs that are included in the training classifiers.

An Intelligent Secure Adversarial Examples Detection Scheme in Heterogeneous Complex Environments

Image-denoising techniques are widely used to defend against Adversarial Examples(AEs).However,denoising alone cannot completely eliminate adversarial perturbations.The remaining perturbations tend to amplify as they propagate through deeper layers of the network,leading to misclassifications.Moreover,image denoising compromises the classification accuracy of original examples.To address these challenges in AE defense through image denoising,this paper proposes a novel AE detection technique.The proposed technique combines multiple traditional image-denoising algorithms and Convolutional Neural Network(CNN)network structures.The used detector model integrates the classification results of different models as the input to the detector and calculates the final output of the detector based on a machine-learning voting algorithm.By analyzing the discrepancy between predictions made by the model on original examples and denoised examples,AEs are detected effectively.This technique reduces computational overhead without modifying the model structure or parameters,effectively avoiding the error amplification caused by denoising.The proposed approach demonstrates excellent detection performance against mainstream AE attacks.Experimental results show outstanding detection performance in well-known AE attacks,including Fast Gradient Sign Method(FGSM),Basic Iteration Method(BIM),DeepFool,and Carlini&Wagner(C&W),achieving a 94%success rate in FGSM detection,while only reducing the accuracy of clean examples by 4%.

A new method of constructing adversarial examplesfor quantum variational circuits

A quantum variational circuit is a quantum machine learning model similar to a neural network.A crafted adversarial example can lead to incorrect results for the model.Using adversarial examples to train the model will greatly improve its robustness.The existing method is to use automatic differentials or finite difference to obtain a gradient and use it to construct adversarial examples.This paper proposes an innovative method for constructing adversarial examples of quantum variational circuits.In this method,the gradient can be obtained by measuring the expected value of a quantum bit respectively in a series quantum circuit.This method can be used to construct the adversarial examples for a quantum variational circuit classifier.The implementation results prove the effectiveness of the proposed method.Compared with the existing method,our method requires fewer resources and is more efficient.

Adversarial Examples Protect Your Privacy on Speech Enhancement System

Speech is easily leaked imperceptibly.When people use their phones,the personal voice assistant is constantly listening and waiting to be activated.Private content in speech may be maliciously extracted through automatic speech recognition(ASR)technology by some applications on phone devices.To guarantee that the recognized speech content is accurate,speech enhancement technology is used to denoise the input speech.Speech enhancement technology has developed rapidly along with deep neural networks(DNNs),but adversarial examples can cause DNNs to fail.Considering that the vulnerability of DNN can be used to protect the privacy in speech.In this work,we propose an adversarial method to degrade speech enhancement systems,which can prevent the malicious extraction of private information in speech.Experimental results show that the generated enhanced adversarial examples can be removed most content of the target speech or replaced with target speech content by speech enhancement.The word error rate(WER)between the enhanced original example and enhanced adversarial example recognition result can reach 89.0%.WER of target attack between enhanced adversarial example and target example is low at 33.75%.The adversarial perturbation in the adversarial example can bring much more change than itself.The rate of difference between two enhanced examples and adversarial perturbation can reach more than 1.4430.Meanwhile,the transferability between different speech enhancement models is also investigated.The low transferability of the method can be used to ensure the content in the adversarial example is not damaged,the useful information can be extracted by the friendly ASR.This work can prevent the malicious extraction of speech.

Defending Adversarial Examples by a Clipped Residual U-Net Model

Deep learning-based systems have succeeded in many computer vision tasks.However,it is found that the latest study indicates that these systems are in danger in the presence of adversarial attacks.These attacks can quickly spoil deep learning models,e.g.,different convolutional neural networks(CNNs),used in various computer vision tasks from image classification to object detection.The adversarial examples are carefully designed by injecting a slight perturbation into the clean images.The proposed CRU-Net defense model is inspired by state-of-the-art defense mechanisms such as MagNet defense,Generative Adversarial Net-work Defense,Deep Regret Analytic Generative Adversarial Networks Defense,Deep Denoising Sparse Autoencoder Defense,and Condtional Generattive Adversarial Network Defense.We have experimentally proved that our approach is better than previous defensive techniques.Our proposed CRU-Net model maps the adversarial image examples into clean images by eliminating the adversarial perturbation.The proposed defensive approach is based on residual and U-Net learning.Many experiments are done on the datasets MNIST and CIFAR10 to prove that our proposed CRU-Net defense model prevents adversarial example attacks in WhiteBox and BlackBox settings and improves the robustness of the deep learning algorithms especially in the computer visionfield.We have also reported similarity(SSIM and PSNR)between the original and restored clean image examples by the proposed CRU-Net defense model.

Eye Movement Modeling Examples as a Teaching Tool for Epidural Block

Introduction: Video examples with task demonstrations by experts, with the expert’s eye movements superimposed on the task, are known as “eye movement modeling examples” (EMME). We performed this study to evaluate if there were improvements in the performance of anesthesia novice trainees when executing the epidural technique after an EMME of epidural block procedure. Methods: We developed an eye movement modeling example (EMME) from eye tracking recordings made by experienced anesthesiologists with more than 20 years of experience. Forty-two PGY3 anesthesia trainees who had never previously performed an epidural block were randomized to receive (study group) or not receive (control group) the EMME video before their institutional training. All the trainees were evaluated every 10 epidural blocks until the end of the rotation period, by an independent, blinded observer using the Global Rating Scale for Epidural Anesthesia (GRS). Results: Trainees who received the EMME training exhibited more respect for the patient’s tissues (P Discussion: This is the first study that has used the EMME for a practical, clinical teaching purpose on real patients and that has used it as an aid in teaching epidural anesthesia. We demonstrated that inexperienced trainees who received the EMME training improved their proficiency at epidural blocks as compared to those who had no EMME training beforehand. Given this result, we welcome further studies to investigate the impact and the role of EMME on clinical teaching in the field of anesthesia.

基于语料库的学习者例证词“for example”对比研究

基于英美大学生作文语料库(LOCNESS)和中国英语学习者语料库(CLEC)调查中国英语学习者在写作中使用例证词"for example"的特点,研究发现,中国英语学习者无论在使用频数还是在用法上都具有明显区别于本族语者的特征。

A New Example of Retrograde Solubility Model for Carbonate Rocks

Objective The dissolution and precipitation of carbonate during burial diagenetic process controls the reservoir property in deep buried strata.The geological process related with it has become a research focus during recent years.The most important dissolution fluids to carbonates are probably H_2S and CO_2 as byproducts of sulfate reduction in deep-buried setting with sulfate minerals,but carbonates are more soluble in relatively low temperature,which is the so-called retrograde solubility.Several geological processes can result in the decrease of temperature,including the upward migration of thermal fluids and tectonic uplift.The Ordovician strata in the Tahe oilfield of the Tarim

Patterns of Clay Minerals Transformation in Clay Gouge, with Examples from Revers Fault Rocks in Devonina Niqiuhe Formation in The Dayangshu Basin

The role of authigenic clay growth in clay gouge is increasingly recognized as a key to understanding the mechanics of berittle faulting and fault zone processes,including creep and seismogenesis,and providing new insights into the ongoing debate about the frictional strength of brittle fault(Haines and van der Pluijm,2012).However,neither the conditions nor the processes

for example还是such as

高中学生写英语作文时，常需列举事物，如：

DroidEnemy: Battling adversarial example attacks for Android malware detection

In recent years,we have witnessed a surge in mobile devices such as smartphones,tablets,smart watches,etc.,most of which are based on the Android operating system.However,because these Android-based mobile devices are becoming increasingly popular,they are now the primary target of mobile malware,which could lead to both privacy leakage and property loss.To address the rapidly deteriorating security issues caused by mobile malware,various research efforts have been made to develop novel and effective detection mechanisms to identify and combat them.Nevertheless,in order to avoid being caught by these malware detection mechanisms,malware authors are inclined to initiate adversarial example attacks by tampering with mobile applications.In this paper,several types of adversarial example attacks are investigated and a feasible approach is proposed to fight against them.First,we look at adversarial example attacks on the Android system and prior solutions that have been proposed to address these attacks.Then,we specifically focus on the data poisoning attack and evasion attack models,which may mutate various application features,such as API calls,permissions and the class label,to produce adversarial examples.Then,we propose and design a malware detection approach that is resistant to adversarial examples.To observe and investigate how the malware detection system is influenced by the adversarial example attacks,we conduct experiments on some real Android application datasets which are composed of both malware and benign applications.Experimental results clearly indicate that the performance of Android malware detection is severely degraded when facing adversarial example attacks.

Relic Oceanic Crust at Sub-arc Depth: an Example from UHP Eclogites Enclosed in Serpentinites from the Southwestern Tianshan Mountains, China

Ultra-high pressure(UHP)eclogites that derive from subducted oceanic crust are rarely found at the Earth’s surface because they need to be enclosed in a buoyant host rock such as serpentinites that facilitate

Relic Oceanic Crust at Sub-Arc Depth: An Example from UHP Eclogites Enclosed in Serpentinites from the Southwestern Tianshan, China

Ultra-high pressure(UHP)eclogites that derive from subducted oceanic crust are rarely found at the Earth’s surface because they need to be enclosed in a buoyant host rock such as serpentinites that facilitate exhumation(Hermann et al.,2000;Guillot et al.,2001).Under normal subduction geotherms,serpentinites break down just before UHP conditions are reached and therefore most of the exhumed eclogites representing subducted oceanic crust formed under fore-arc conditions.We investigated eclogite blocks enclosed into serpentinites that occur in the southwestern Tianshan oceanic subduction,China.A previous study proved that the serpentinites derive from altered oceanic crust and experienced UHP metamorphism at low temperatures of 510-530°C(Shen et al.,2015).Three relatively fresh eclogite samples were studied in detail.Sample 129-7 shows the retrograde mineral assemblage of amphibole+biotite+albite+chlorite+minor titanite and peak metamorphic relics of omphacite+garnet±chlorite.Sample C107-23 is mainly composed of amphibole+albite+chlorite+zoisite+muscovite+minor titanite as a retrograde assemblage and garnet+phengite as the peak metamorphic relics with omphacite only found as inclusions in garnet.Similar to sample C107-23,sample C11066 preserves large-grained euhedral to subhedral garnet relics with omphacite inclusions,and epidote,diopside,amphibole,muscovite,chlorite,albite and biotite are in the matrix belong to the retrograde assemblage.These three retrograde eclogite samples were modelled using thermodynamic calculations in the Mn NCKFMSHO(Mn O-Na_2O-Ca O-K_2O-FeO-Mg O-Al_2O_3-SiO_2-H_2O-Fe_2O_3)system.Based on the peak assemblage of omphacite+garnet and the crossing of the grossular and pyrope isopleths in garnet,peak P-T conditions of^460-470oC,28-29 kbar(129-7),450-500oC,28-35 kbar(C107-23),~475-505oC,26-29 kbar(C11066)were calculated.The retrograde assemblages indicate near isothermal decompression resulting in a clockwise P-T evolution of these eclogites.The peak metamorphic pressures at 500°C are well within UHP conditions(coesite stability field)and are within error the same as peak conditions of the host serpentinites(Shen et al.,2015).This provides evidence that eclogites and serpentinites shared the same evolution.We infer that the subducted low-density serpentinites were assembled with the high-density eclogites during subdution and helped the latter to exhume back to the surface.The studied eclogites thus represent rare examples of relics of oceanic crust that was subducted to sub-arc depth.

Fluidizate-Explosive Occurrences in Ophiolites as Indicator of the Subduction Zone Activity: The Urals Example

It is known that the formation of oceanic crust occurs in different geodynamic settings,accompanying by the emergence of mantle-magmatic ophiolite complexes having a distinctive properties.In the process of mantle-crustal evolution of the ophiolites are undergoing significant changes with the formation of peculiar(on structure and composition)rocks,sometimes with unusual mineral paragenesis.The presence of such rocks in mélange tectonic zones greatly complicates to determine their origin.In the Ural folded belt(length more than 2,000 km)separating the East European Platform and the West Siberian sedimentary basin,ophiolites are widespread forming a chain of mafic-ultramafic massifs(Fig.1)located in the allochthonous position with mélange at the bottom(Puchkov,2013).With the Urals ophiolites are associated occurrences of eclogites,jadeites,ruby and other rocks of unclear nature,sometimes regarded as potentially diamondiferous.Such formations of unclear genesis include the associating with ophiolites metabasites of higher alkalinity composing the body in the mantle peridotites of the mélange Main Uralian Fault(MUF)zone(Shmelev,2005).By this time they are determined in different parts of the fault zone,but most completely are known in the Sub Polar Urals,where are distinguished under the name of Sertynya alkaline-ultramafic complex,which is located just 25 km east of Hartes kimberlitic complex(Fig.1).Formally,its affiliation to diamond-bearing associations is confirmed by finding of grains and fragments of natural diamond in the weathering crust.A detailed study of the rock complexes shows that in reality they have a polygenic nature,combine theelements of proper magmatic and fluidizate-explosive formations,the appearance of which was interfaced with the processes at the slab-mantle wedge boundary in subduction zones.Polygenic nature of the rocks is reflected in the existence of three interrelated structural-geological units:(1)bodies and dikes of uniformmetadiabasesanddensefine-grainedmetadolerites(lamprophyres),(2)fluidal-brecciated dolerites("tuff breccias")and(3)structural weathering crust with angular or rounded fragments(blocks)of metadolerites and serpentinites.The rocks have experienced rodingitization and permeated with net of veins a vesuvianite composition.The host peridotite matrix(harzburgites and dunites)has undergone serpentinizationandchloritization.Structural relationships give grounds for distinguishing in the history of the complex formation the magmatic proper(dolerite dyke and lamprophyre intrusion)and infiltration fluidizate-explosive(metasomatic transformation of dolerite)stages.Peculiarities of petrography and mineralogy of rock complexes does not allow to compare them with lamproites and kimberlites.Metadiabases demonstrate relics of ophitic structure,as primary paragenesis is completely replaced by aggregate of chlorite,zoisite and leucoxene.Dolerites(lamprophyres)have a uniform fine-grained or porphyry structure with phenocrysts of clinopyroxene,brown amphibole and leucoxene(sphene),which are immersed in a fine-scaly aggregate of light green mica.In the rocks amphibole,garnet and vesuvian are present.Clinopyroxene corresponds to augite with moderate content of titanium and alumina(up to 3.5wt.%),showing a normal magmatic zonation in composition.Mica previously wrongly called as phlogopite,actually has an extremely ferrous composition and corresponds to biotite(annite).Amphibole is presented by magmatic titaniferous tschermakite hornblende and metamorphic(bluish)variety of sodium-calcium composition(taramite).Garnet is presented by exceptionally grossular of rodingite type.Mineralogy of weathering crust reveals similar features,but in the samples it is marked the presence of muscovite,orthoclase and weakly ferrous diopside.An important feature of the weathering crust is the presence of shear surfaces on minerals,resulting in fracturing due to internal stress,confirming the explosive nature of protolith.The bulk chemical composition of rocks is characterized by significant variations in the content of silica(30-46 wt.%)and alkalis(0-6.5 wt.%).These metabasites have consistently a low magnesia number and high titanium oxide content(1.5-3.0 wt.%).Side by side with these are been established the uniform slope REE distribution trends similar to the trend of oceanic basalts N-MORB type(Fig.2).The level of trace element compositions does not depend on variations in the alkalinity of the rocks,but clearly correlates with the titanium content.Unlike them the Hartes kimberlites demonstrate the distribution with deficit of HREE,andthe level of the elements content is correlated with the alkalinity of rocks(Mahotkin et al.,1998).Another important geochemical feature of the Sertynya complex rocks is a regular behavior of the mobile LILE elements(Cs,Rb,Ba,K).In the varieties of rocks with mica enriched by alkalis,it is recorded extremely high level of LILE,exceeding the level of contents in N-MORB basalts at 10-10000 times!In the metabasites varieties with low level of alkalinity,LILE content is sharply(except Cs)reduced to minimum values(Fig.2).The observed pattern of the element distribution is undoubtedly the result of postmagmatic fluid-metasomatic alteration of the original rocks.Tectonic position and the primary composition characteristics of the metadolerites give reason to consider them as fragments of the ophiolite sheeted dike complex(Shmelev,2005).The famous dike complexes in the ophiolite massifs of the MUF zone(east of mélange)belong to suprasubduction formations of Paleozoic age.However the obtained mainly ancient U-Pb zircon dating(up to Archean inclusive)for metadolerites of the Sertynya complex,make it possible to assume its Vendian-Early Cambrian(530-617 Ma)age.It permits to compare the Sertynya metabasites with the Vendian metaophiolites of the MUF zone in the Middle Urals(Petrov et al.,2010).It is noteworthy that similar age datings(520-550 Ma)are also established for kimberlites of the Hartes complex located to the west of ophiolites.Therefore,thepresenceofthe Vendian-Cambrian ophiolite of MOR-type in the MUF mélange zone,"changing"to the east of Ordovician ophiolites SSZ-type,seems quite possible.The obtained data allow to suggest an original interpretation of nature of the Urals fluidizate-explosive formations considering the process specifics in the subduction zones(Bebout and Barton,2002).Accordingto this model,the pre-Ordovician(?)oceanic crust has undergone transformations and deformations on the slab-mantle wedge boundary during the subduction.As a result of slab dehydration it occurred a flow of aqueous fluids,which were enriched with the extracted from sedimentary rocks the LILE elements and percolated through the mantle substrate with dolerite dyke complex.Interaction with them led to the formation of chlorite-zoisite and/or mica(biotite-bearing)fluidizates and in the presence of a gas phase-fluidizate-explosive breccias with subsequent development of weathering crust.In the surrounding peridotites an explosive process is marked by the formation of pseudokimberlite breccias.Fluidized-explosive occurrences in mantle peridotites of mélange zones should be considered as indicators of the subduction slab-mantle interaction at relatively shallow levels involving enriched LILE fluids(without melts participation),rising as the front from the subduction zone.In this interpretation,there is no need toappealtothealkaline-ultramaficor lamproit-kimberlite hypothesis of the genesis of these formations,however,the question of their potential diamondiferous remains to be open.The proposed interpretation of the fluidizate-explosive occurrences makes it possible to comprehendthat in reality the mélange is a complex formation with signs of not onlycollisional(as usually is considered),but also of earlier subduction events.

Two-Stream Architecture as a Defense against Adversarial Example

The performance of deep learning on many tasks has been impressive.However,recent studies have shown that deep learning systems are vulnerable to small specifically crafted perturbations imperceptible to humans.Images with such perturbations are called adversarial examples.They have been proven to be an indisputable threat to deep neural networks(DNNs)based applications,but DNNs have yet to be fully elucidated,consequently preventing the development of efficient defenses against adversarial examples.This study proposes a two-stream architecture to protect convolutional neural networks(CNNs)from attacks by adversarial examples.Our model applies the idea of“two-stream”used in the security field.Thus,it successfully defends different kinds of attack methods because of differences in“high-resolution”and“low-resolution”networks in feature extraction.This study experimentally demonstrates that our two-stream architecture is difficult to be defeated with state-of-the-art attacks.Our two-stream architecture is also robust to adversarial examples built by currently known attacking algorithms.

Examples for Clinical Use of Ma Zi Ren Wan

Ma Zi Ren Wan (麻子仁丸), originally recorded in Treatise on Febrile Diseases (伤寒论), is composed of Ma Zi Ren (麻子仁Fructus Cannabis), Bai Shao (白芍Radix Paeoniae Alba), Zhi Shi (枳实Fructus Aurantii Immaturus), Da Huang (大黄Radix etRhizoma Rhei), Hou Po (厚朴cortex Magnoliae Officinalis) and Xing Ren (杏仁Semen Armeniacae Amarum). Good therapeutic results have been achieved by using Ma ZiRen Wan in treatment of febrile disease at the restoring stage, chronic consumptive diseases, hemorrhoid, disorders in women after delivery, chronic kidney disease, senile constipation, pulmonary heart disease, diabetes, coronary heart disease and hypertension. Some illustrative cases are introduced below. ……

Environmental Implication of Subaqueous Lava Flows from A Continental Large Igneous Province: Examples from the Moroccan Central Atlantic Magmatic Province(CAMP)

The Early Jurassic volcanic sequence of the Central Atlantic Magmatic Province(CAMP)of Morocco is classically subdivided into four stratigraphic units:the Lower,Middle,Upper and Recurrent Formations

The Phenomenon of Intertextuality in 19th Century Italian Opera Libretti:The Example of G.Donizetti’s“Lucia di Lammermoor”

The purpose of this study is to identify the specifics of opera libretto in the context of intertextual relationships.The implementation of this goal involves the following tasks:ŸDetermining the intertextual nature of the opera libretto;ŸAnalyzing the structural laws of the text of the literary source and how they are transformed in the opera libretto.Libretto as the phenomenon of musical culture requires a multidimensional knowledge of the modern humanities.This requires overcoming a highly specialized approach,be it musicological or literary,and a transition to a comprehensive cultural analysis.To solve the problems posed in the work,this study employs the following methods:ŸIntegrative,enabling application of the knowledge gained through various sciences to the solution of the tasks posed in this study.