“…This mechanism restricts the correlation between an epidemic’s initial growth rate and its total reach, thus preventing the majority of epidemics, including initially fast-growing outbreaks, from reaching a macroscopic fraction of the population. The few pervasive malwares distinguish themselves early on via the following key trait: they avoid infecting the tail, while preferentially targeting computers unaffected by typical malware.…”
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“…Instead of blacklist-based models, our antivirus allows JAR malware detection preventively and not reactively as Oracle’s Java and traditional antivirus modus operandi.…”
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“…Machine learning with static-analysis features extracted from malware files has been adopted to detect malware variants, which is desirable for resource-constrained edge computing and Internet-of-Things devices with sensors; however, this learned model suffers from a misclassification problem because some malicious files have almost the same static-analysis features as benign ones. …”
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“…In this work, we provide a comprehensive evaluation of anti-malware tools to gauge the impact of complex hybrid code-obfuscations techniques on malware detection capabilities of the prominent anti-malware tools. …”
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“…With our ever-increasing reliance on computers comes an ever-growing risk of malware. Security professionals will find plenty of solutions in this book to the problems posed by viruses, Trojan horses, worms, spyware, rootkits, adware, and other invasive software. …”
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“…The Internet of Things (IoT) environment demands a malware detection (MD) framework for protecting sensitive data from unauthorized access. …”
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“…BACKGROUND: Malware, malicious software, is the major security concern of the digital realm. …”
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“…The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. …”
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“…Our approach uses malicious code crawling to rearrange websites in the order of their risk index by analyzing the centrality between malware sites and proactively eliminates the root of these sites by finding the core-hub node, thereby reducing unnecessary security policies. …”
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“…Based on the inherent characteristics of wireless sensor networks (WSN), the dynamic behavior of malware propagation in flat WSN is analyzed and investigated. …”
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“…Due to advancements in malware competencies, cyber-attacks have been broadly observed in the digital world. …”
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“…Despite the incessant efforts of cybersecurity research to defend against malware threats, malware developers discover new ways to evade these defense techniques. …”
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“…Although a few media reports mentioned the existence of coronavirus-themed mobile malware, the research community lacks the understanding of the landscape of the coronavirus-themed mobile malware. …”
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“…With the popularity of Android, malware detection and family classification have also become a research focus. …”
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“…As a result, IoT devices have easily become targets for cyber attackers, and malware attacks on IoT devices are increasing every year. …”
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“…A few studies proposed models for the detection of mobile malware. Nevertheless, improvements are required to achieve maximum efficiency and performance. …”
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“…As Android is a popular a mobile operating system, Android malware is on the rise, which poses a great threat to user privacy and security. …”
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