Survey on Adversarial Attack for Malware Detection

Malicious software, commonly known as malware, refers to any type of intrusive software designed to perform harmful actions on a computer system. Recently, Machine Learning (ML) techniques have been used to create new malware variants, enabling attackers to generate thousands of previously unseen malware samples. Traditional detection methods, such as signature-based detection, rely on prior knowledge of malware and therefore often fail to identify new variants. This limitation has led cybersecurity experts to increasingly adopt ML techniques for malware detection. While ML-based approaches have shown promising results by generalizing malware signatures to detect previously unseen malware, they remain vulnerable to adversarial attacks. Adversarial attacks leverage carefully crafted malware samples designed to evade ML-based detectors by exploiting algorithmic vulnerabilities. To develop new defense methods against these attacks, a clear understanding of adversarial techniques is essential. This study compiles and categorizes the latest research on adversarial attacks in the field to support researchers in developing robust malware detection models. It expands on existing surveys by analyzing adversarial attacks based on attack settings, techniques, success rates, evaluation metrics, and future research directions. This study also proposes promising areas for future research, aiming to highlight gaps in the current body of knowledge

Enhancing Malware Analysis and Detection Using Adversarial Machine Learning Techniques

In the realm of modern technology, malware has become a paramount concern. Defined as any software designed with malicious intent, malware manifests in numerous types that infect computer systems and devices. As of 2023, executable files account for 53% of computer viruses\u27 spread. Compounded by the emergence of AI and polymorphic malware, attackers have intensified their efforts to obfuscate malicious code, rendering traditional defenses, such as signature-based detection systems, ineffective. To counter the evolving nature of modern malware, the adoption of machine learning (ML) models for detection has gained prominence. These models are able to continuously analyze memory and other data, identifying new patterns and features that aid in uncovering previously hidden malware variants. While ML-based detection systems demonstrate commendable performance, they still have vulnerabilities that necessitate further exploration. In this research proposal, we aim to address the aforementioned gaps and challenges by developing novel techniques to robustify ML-based malware detection systems. Specifically, we will focus on designing a testing framework that utilizes adversarial machine learning to generate AEs as variants of known modern malware datasets. These AEs will simulate real-world attack strategies, thereby enabling researchers to continuously update detection systems and enhance their resilience against emerging threats. Additionally, we will explore the development of comprehensive evaluation methods that incorporate robustness as a central metric to gauge the effectiveness of ML-based detection systems

Resonant alignment of microswimmer trajectories in oscillatory shear flows

Oscillatory flows are commonly experienced by swimming micro-organisms in the environment, industrial applications, and rheological investigations. We characterize experimentally the response of the alga Dunaliella salina to oscillatory shear flows and report the surprising discovery that algal swimming trajectories orient perpendicular to the flow-shear plane. The ordering has the characteristics of a resonance in the driving parameter space. The behavior is qualitatively reproduced by a simple model and simulations accounting for helical swimming, suggesting a mechanism for ordering and criteria for the resonant amplitude and frequency. The implications of this work for active oscillatory rheology and industrial algal processing are discussed.O.A.C., W.C.K.P., M.D.H., and M.A.B. acknowledge support from the Carnegie Trust for the Universities of Scotland. O.A.C. further acknowledges support from the Winton Programme for the Physics of Sustainability and a Royal Society Research Grant; M.D.H. support from the Leverhulme Trust. O.A.C. and M.A.B. also acknowledge an EPSRC Mobility Grant (No. EP/J004847/1) and W.C.K.P. acknowledges the Programme Grant (No. EP/J007404/1) and ERC Advanced Grant (No. ERC-2013-AdG 340877-PHYSAPS)

Green product preferences considering cultural influences: a comparison study between Malaysia and Indonesia

Purpose – There is an increasing awareness among manufacturers to make production more sustainable in Southeast Asian countries such as Malaysia and Indonesia. Manufacturers are now urged to not only focus on the business profit but also concern on environment protection by producing green products. However, issues may arise regarding the preferences of customers on green products, which will vary due to the influence of cultural values. This will give an impact on the marketing of green products. The aim of this study is to identify the influence of cultural values on the green products design in Malaysia and Indonesia. Design/methodology/approach – A pretest on the survey instruments was performed to ensure the reliability and validity of the questionnaire. The collected data were statistically analyzed based on the satisfaction level, confirmatory factor analysis and structural equation modeling. Findings – The results showed that customer preferences in Malaysia were mostly influenced by uncertainty avoidance, long-term orientation and power distance, excluding collectivism and masculinity. In Indonesia, the dimension of uncertainty avoidance and long-term orientation had significant influence, whereas power distance, masculinity and collectivism dimension had no influence. Eco-label was identified as the most important factor for green products in Malaysia and having product services characteristics factor for product lifetime extension in Indonesia. Practical implications – For practices, the cultural values and preferred characteristics identified in this study provide valuable information to policymakers and businesses on what draws customers toward green products in Malaysia and Indonesia. This finding can be used as supported data for the policymakers in order to achieve sustainable development goal (SDGs) in Malaysia and Indonesia. Originality/value – The findings of this study provide valuable information for designers to design products with green characteristics that cater to the consumer market in Malaysia and Indonesia, as well as other countries which may have similar cultural traits

Howard Goldblattâs translation practice and translation thoughts

With the cultural turn of translation studies, the subject status of translators has gradually been highlighted, and translator studies have become increasingly important. However, the current research on translators is mostly confined to certain aspects such as the translator’s translation thoughts, translation strategies or translation styles, which lacks comprehensive and detailed research. This article aims to study the translator Howard Goldblatt from the four aspects of his life experience, namely translation practice, translation motivation, translation thoughts and translation strategies, in an attempt to present a detailed and comprehensive translator. The results demonstrate that Howard Goldblatt’s translation is based on cross-cultural communication as the ultimate goal, comprehensively using translation strategies that combine domestication and foreignization to spread the Chinese culture. This study contributes to the diversification of research methods and the dissemination of Chinese culture

Fracture analysis of a corner crack in a pinhole of a solid cylinder under torsion loading

Fatigue crack growths of a corner crack emanating from a pinhole of a solid cylinder subjected to cyclic torsion loading were simulated using a Dual-Boundary Element Method (DBEM) based software. For a given crack aspect ratio a/c, larger Mode I stress intensity factor (SIF) was observed at a larger pinhole diameter. Any given initial crack aspect ratio a/c would evolve towards unity. The final evolving crack aspect ratio a/c was shown to be larger than 1. For the same given initial crack length a, a smaller crack depth c was found to result in a shorter fatigue life. A shorter fatigue life yielded a larger orientation angle of the crack growth path

Frequency Shift of Carbon-Nanotube-Based Mass Sensor Using Nonlocal Elasticity Theory

The frequency equation of carbon-nanotube-based cantilever sensor with an attached mass is derived analytically using nonlocal elasticity theory. According to the equation, the relationship between the frequency shift of the sensor and the attached mass can be obtained. When the nonlocal effect is not taken into account, the variation of frequency shift with the attached mass on the sensor is compared with the previous study. According to this study, the result shows that the frequency shift of the sensor increases with increasing the attached mass. When the attached mass is small compared with that of the sensor, the nonlocal effect is obvious and increasing nonlocal parameter decreases the frequency shift of the sensor. In addition, when the location of the attached mass is closer to the free end, the frequency shift is more significant and that makes the sensor reveal more sensitive. When the attached mass is small, a high sensitivity is obtained

Quantitative imaging of concentrated suspensions under flow

We review recent advances in imaging the flow of concentrated suspensions, focussing on the use of confocal microscopy to obtain time-resolved information on the single-particle level in these systems. After motivating the need for quantitative (confocal) imaging in suspension rheology, we briefly describe the particles, sample environments, microscopy tools and analysis algorithms needed to perform this kind of experiments. The second part of the review focusses on microscopic aspects of the flow of concentrated model hard-sphere-like suspensions, and the relation to non-linear rheological phenomena such as yielding, shear localization, wall slip and shear-induced ordering. Both Brownian and non-Brownian systems will be described. We show how quantitative imaging can improve our understanding of the connection between microscopic dynamics and bulk flow.Comment: Review on imaging hard-sphere suspensions, incl summary of methodology. Submitted for special volume 'High Solid Dispersions' ed. M. Cloitre, Vol. xx of 'Advances and Polymer Science' (Springer, Berlin, 2009); 22 pages, 16 fig

Can We Really Prevent Suicide?

Every year, suicide is among the top 20 leading causes of death globally for all ages. Unfortunately, suicide is difficult to prevent, in large part because the prevalence of risk factors is high among the general population. In this review, clinical and psychological risk factors are examined and methods for suicide prevention are discussed. Prevention strategies found to be effective in suicide prevention include means restriction, responsible media coverage, and general public education, as well identification methods such as screening, gatekeeper training, and primary care physician education. Although the treatment for preventing suicide is difficult, follow-up that includes pharmacotherapy, psychotherapy, or both may be useful. However, prevention methods cannot be restricted to the individual. Community, social, and policy interventions will also be essentia

The relationship between workers' self-reported changes in health and their attitudes towards a workplace intervention: lessons from smoke-free legislation across the UK hospitality industry

Background: The evaluation of smoke-free legislation (SFL) in the UK examined the impacts on exposure to second-hand smoke, workers’ attitudes and changes in respiratory health. Studies that investigate changes in the health of groups of people often use self-reported symptoms. Due to the subjective nature it is of interest to determine whether workers’ attitudes towards the change in their working conditions may be linked to the change in health they report. Methods: Bar workers were recruited before the introduction of the SFL in Scotland and England with the aim of investigating their changes to health, attitudes and exposure as a result of the SFL. They were asked about their attitudes towards SFL and the presence of respiratory and sensory symptoms both before SFL and one year later. Here we examine the possibility of a relationship between initial attitudes and changes in reported symptoms, through the use of regression analyses. Results: There was no difference in the initial attitudes towards SFL between those working in Scotland and England. Bar workers who were educated to a higher level tended to be more positive towards SFL. Attitude towards SFL was not found to be related to change in reported symptoms for bar workers in England (Respiratory, p = 0.755; Sensory, p = 0.910). In Scotland there was suggestion of a relationship with reporting of respiratory symptoms (p = 0.042), where those who were initially more negative to SFL experienced a greater improvement in self-reported health. Conclusions: There was no evidence that workers who were more positive towards SFL reported greater improvements in respiratory and sensory symptoms. This may not be the case in all interventions and we recommend examining subjects’ attitudes towards the proposed intervention when evaluating possible health benefits using self-reported methods. Keywords: ‘Self-Reported Health’, Attitudes, ‘Workplace Intervention’, ‘Public Health Intervention