Results 51 to 60 of about 31,501 (227)
An Efficient Boosting-Based Windows Malware Family Classification System Using Multi-Features Fusion
Applied Sciences, 2023 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 ...
Zhiguo Chen, Xuanyu Ren
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Graph neural network‐based attack prediction for communication‐based train control systems
CAAI Transactions on Intelligence Technology, EarlyView.Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao +3 more
wiley +1 more source
Malware Classification Using LSTMs
, 2021 Signature and anomaly based detection have long been quintessential techniques used in malware detection. However, these techniques have become increasingly ineffective as malware becomes more complex. Researchers have therefore turned to deep learning to construct better performing models.
openaire +2 more sources
Not so Crisp, Malware! Fuzzy Classification of Android Malware Classes
2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2018 Mobile devices have been spreading at great rate in recent years. Not only smartphone, but also tablets and IoT devices, are gaining an increasingly place in our everyday lives. This is the reason why attackers are developing more and more aggressive techniques with the aim to exfiltrate our sensitive and private information.
Mercaldo F., Saracino A.
openaire +4 more sources
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
wiley +1 more source
Malware Detection using Machine Learning and Deep Learning
, 2019 Research shows that over the last decade, malware has been growing exponentially, causing substantial financial losses to various organizations. Different anti-malware companies have been proposing solutions to defend attacks from these malware.
A Nappa +6 more
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Applications of Machine Learning to Threat Intelligence, Intrusion Detection and Malware [PDF]
, 2020 Artificial Intelligence (AI) and Machine Learning (ML) are emerging technologies with applications to many fields. This paper is a survey of use cases of ML for threat intelligence, intrusion detection, and malware analysis and detection.
Barker, Charity
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The Journal of World Intellectual Property, EarlyView.Abstract Understanding the role of information communication technologies (ICTs) in development, especially in relation to marginalized populations, has been the focus of many related disciplinary categories within the broader ecosystem of information sciences.
Chidi Oguamanam
wiley +1 more source
Evading Classifiers by Morphing in the Dark
, 2017 Learning-based systems have been shown to be vulnerable to evasion through adversarial data manipulation. These attacks have been studied under assumptions that the adversary has certain knowledge of either the target model internals, its training ...
Chang, Ee-Chien, Dang, Hung, Huang, Yue
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Exploring network-based malware classification [PDF]
2011 6th International Conference on Malicious and Unwanted Software, 2011 Over the last years, dynamic and static malware analysis techniques have made significant progress. Majority of the existing analysis systems primarily focus on internal host activity. In spite of the importance of network activity, only a limited set of analysis tools have recently started taking it into account.
Natalia Stakhanova +2 more
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