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Sharoug Alzaidy and Hamad Binsalleeh
In the field of behavioral detection, deep learning has been extensively utilized. For example, deep learning models have been utilized to detect and classify malware. Deep learning, however, has vulnerabilities that can be exploited with crafted inputs,...
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Catarina Palma, Artur Ferreira and Mário Figueiredo
The presence of malicious software (malware), for example, in Android applications (apps), has harmful or irreparable consequences to the user and/or the device. Despite the protections app stores provide to avoid malware, it keeps growing in sophisticat...
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Falah Amer Abdulazeez, Ismail Taha Ahmed and Baraa Tareq Hammad
A significant quantity of malware is created on purpose every day. Users of smartphones and computer networks now mostly worry about malware. These days, malware detection is a major concern in the cybersecurity area. Several factors can impact malware d...
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Jinting Zhu, Julian Jang-Jaccard, Amardeep Singh, Paul A. Watters and Seyit Camtepe
Malware authors apply different techniques of control flow obfuscation, in order to create new malware variants to avoid detection. Existing Siamese neural network (SNN)-based malware detection methods fail to correctly classify different malware familie...
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Zhiguo Chen and Xuanyu Ren
In previous years, cybercriminals have utilized various strategies to evade identification, including obfuscation, confusion, and polymorphism technology, resulting in an exponential increase in the amount of malware that poses a serious threat to comput...
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Ammar Yahya Daeef, Ali Al-Naji, Ali K. Nahar and Javaan Chahl
Malware is the primary attack vector against the modern enterprise. Therefore, it is crucial for businesses to exclude malware from their computer systems. The most responsive solution to this issue would operate in real time at the edge of the IT system...
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Nikola Andelic, Sandi Baressi ?egota and Zlatan Car
Malware detection using hybrid features, combining binary and hexadecimal analysis with DLL calls, is crucial for leveraging the strengths of both static and dynamic analysis methods. Artificial intelligence (AI) enhances this process by enabling automat...
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Abigail Copiaco, Leena El Neel, Tasnim Nazzal, Husameldin Mukhtar and Walid Obaid
This study introduces an innovative all-in-one malware identification model that significantly enhances convenience and resource efficiency in classifying malware across diverse file types. Traditional malware identification methods involve the extractio...
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Ibrahim Ba?abbad and Omar Batarfi
Several malware variants have attacked systems and data over time. Ransomware is among the most harmful malware since it causes huge losses. In order to get a ransom, ransomware is software that locks the victim?s machine or encrypts his personal informa...
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Sapna Sadhwani, Baranidharan Manibalan, Raja Muthalagu and Pranav Pawar
The study in this paper characterizes lightweight IoT networks as being established by devices with few computer resources, such as reduced battery life, processing power, memory, and, more critically, minimal security and protection, which are easily vu...
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