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Avinash Singh, Richard Adeyemi Ikuesan and Hein Venter
The growing sophistication of malware has resulted in diverse challenges, especially among security researchers who are expected to develop mechanisms to thwart these malicious attacks. While security researchers have turned to machine learning to combat...
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Abishek Manikandaraja, Peter Aaby and Nikolaos Pitropakis
Artificial intelligence and machine learning have become a necessary part of modern living along with the increased adoption of new computational devices. Because machine learning and artificial intelligence can detect malware better than traditional sig...
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Ehab Alkhateeb, Ali Ghorbani and Arash Habibi Lashkari
This research addresses a critical need in the ongoing battle against malware, particularly in the form of obfuscated malware, which presents a formidable challenge in the realm of cybersecurity. Developing effective antivirus (AV) solutions capable of c...
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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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Parvez Faruki, Rati Bhan, Vinesh Jain, Sajal Bhatia, Nour El Madhoun and Rajendra Pamula
Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware. Adversaries are constantly in charge of employing ...
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Xin Su, Lijun Xiao, Wenjia Li, Xuchong Liu, Kuan-Ching Li and Wei Liang
Recently, security incidents such as sensitive data leakage and video/audio hardware control caused by Android malware have raised severe security issues that threaten Android users, so thus behavior analysis and detection research researches of maliciou...
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Dong-Kyu Chae, Sung-Jun Park, Eujeanne Kim, Jiwon Hong and Sang-Wook Kim
Malware are developed for various types of malicious attacks, e.g., to gain access to a user?s private information or control of the computer system. The identification and classification of malware has been extensively studied in academic societies and ...
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Jeonggeun Jo, Jaeik Cho and Jongsub Moon
Artificial intelligence (AI) is increasingly being utilized in cybersecurity, particularly for detecting malicious applications. However, the black-box nature of AI models presents a significant challenge. This lack of transparency makes it difficult to ...
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Arthur Fournier, Franjieh El Khoury and Samuel Pierre
The rapid adoption of Android devices comes with the growing prevalence of mobile malware, which leads to serious threats to mobile phone security and attacks private information on mobile devices. In this paper, we designed and implemented a model for m...
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Vasileios Kouliaridis and Georgios Kambourakis
Year after year, mobile malware attacks grow in both sophistication and diffusion. As the open source Android platform continues to dominate the market, malware writers consider it as their preferred target. Almost strictly, state-of-the-art mobile malwa...
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Vassilios Moussas and Antonios Andreatos
Malware creators generate new malicious software samples by making minor changes in previously generated code, in order to reuse malicious code, as well as to go unnoticed from signature-based antivirus software. As a result, various families of variatio...
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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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Nureni Ayofe Azeez, Oluwanifise Ebunoluwa Odufuwa, Sanjay Misra, Jonathan Oluranti and Robertas Dama?evicius
In this Internet age, there are increasingly many threats to the security and safety of users daily. One of such threats is malicious software otherwise known as malware (ransomware, Trojans, viruses, etc.). The effect of this threat can lead to loss or ...
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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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Norah Abanmi, Heba Kurdi and Mai Alzamel
The prevalence of malware attacks that target IoT systems has raised an alarm and highlighted the need for efficient mechanisms to detect and defeat them. However, detecting malware is challenging, especially malware with new or unknown behaviors. The ma...
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Faulinda Ely Nastiti,Dedy Hariyadi,Fazlurrahman Bima
Pág. 51 - 54
Ancaman serangan siber masih didominasi oleh malware. Beberapa penyedia telah menyediakan peta dan analisis serangan malware berbasis agen yang telah ditempatkan pada beberapa infrastruktur. Namun, ada pihak lain yang menyediakan data serangan Malware ya...
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Ajit Kumar, Vinti Agarwal, Shishir Kumar Shandilya, Andrii Shalaginov, Saket Upadhyay and Bhawna Yadav
Android malware has become the topmost threat for the ubiquitous and useful Android ecosystem. Multiple solutions leveraging big data and machine-learning capabilities to detect Android malware are being constantly developed. Too often, these solutions a...
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Dohoon Kim
Most recent cyberattacks have employed new and diverse malware. Various static and dynamic analysis methods are being introduced to detect and defend against these attacks. The malware that is detected by these methods includes advanced present threat (A...
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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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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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