“…This paper presents SmartMal—a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. …”
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“…The data includes a reference for all running processes as well as a mapping for the designated malware running inside the memory. The datasets are available in the article, for advancing research towards the detection of obfuscated malware from volatile computer memory during a forensic analysis.…”
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“…A new kind of malware called Mirai is spreading like wildfire. Mirai is characterized by targeting Internet of Things (IoT) devices. …”
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“…Malware detection of non-executables has recently been drawing much attention because ordinary users are vulnerable to such malware. …”
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“…Due to limited resources, wireless sensor network (WSN) nodes generally possess weak defense capabilities and are often the target of malware attacks. Attackers can capture or infect specific sensor nodes and propagate malware to other sensor nodes in WSNs through node communication. …”
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“…How to effectively detect malware is a research trend; in order to tackle the new needs and problems arising from the development of malware, this paper proposes to guide machine learning algorithms to implement malware detection in a distributed environment: firstly, each detection node in the distributed network performs anomaly detection on the captured software information and data, then performs feature analysis to discover unknown malware and obtain its samples, updates the new malware features to all feature detection nodes in the whole distributed network, and trains the random forest-based machine learning algorithm for malware classification and detection, thus completing the global response processing capability for malware. …”
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“…Malware has grown in popularity as a method of conducting cyber assaults in former decades as a result of numerous new deception methods employed by malware. …”
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“…With the rapid growth in the number of malware, developing of an efficient and reliable method for classifying malware has become one of the research priorities. …”
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“…Traditional signature-based malware detection methods are not adaptable to the current large-scale malware detection. …”
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“…This study addresses the challenge of malware detection in IoT devices by proposing a new CNN-based IoT malware detection architecture (iMDA). …”
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“…Research has spawned in various directions to yield effective malware detection mechanisms. Since malware can adopt different ways to attack and hide, accurate analysis is the key to detecting them. …”
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“…The rapid growth of malware has become a serious problem that threatens the security of the mobile ecosystem and needs to be studied and resolved. …”
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“…In this study, the methodology of cyber-resilience in small and medium-sized organizations (SMEs) is investigated, and a comprehensive solution utilizing prescriptive malware analysis, detection and response using open-source solutions is proposed for detecting new emerging threats. …”
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“…Also, a method is proposed for the effective detection of malware infection systems triggering IP-spoofed DDoS attacks on an edge network. …”
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“…Malware allegedly developed by nation-states, also known as advanced persistent threats (APT), are becoming more common. …”
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“…Malware development has seen diversity in terms of architecture and features. …”
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“…Notably, most Android malware detection tools depend on conventional machine-learning algorithms; hence, they lose the benefits of metaheuristic optimization. …”
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“…Owing to the nature of developed Zero-Day malware, distinct evasion tactics are used to remain stealth. …”
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“…With the popularity of Android and its open source, the Android platform has become an attractive target for hackers, and the detection and classification of malware has become a research hotspot. Existing malware classification methods rely on complex manual operation or large-volume high-quality training data. …”
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