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A smart contract vulnerability detection method based on deep learning with opcode sequences
Ethereum is a blockchain network that allows developers to create smart contracts and programs that run on the blockchain. Smart contracts contain...
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An Efficient Hybrid Approach for Malware Detection Using Frequent Opcodes and API Call Sequences
Malicious software attacks are increasing every day despite so many preventive measures, and many detection mechanisms are available in the...
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Malware Detection Based on Opcode Sequence and ResNet
Nowadays, it is challenging for traditional static malware detection method to keep pace with the rapid development of malware variants, therefore...
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Instruction-Level Power Side-Channel Leakage Evaluation of Soft-Core CPUs on Shared FPGAs
Side-channel disassembly attacks recover CPU instructions from power or electromagnetic side-channel traces measured during code execution. These...
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An Efficient Cross-Contract Vulnerability Detection Model Integrating Machine Learning and Fuzz Testing
Due to the lengthy processing time associated with traditional fuzz testing methods for identifying vulnerable contracts, we have integrated machine...
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Static Signature-Based Malware Detection Using Opcode and Binary Information
Internet continues to evolve and touches every aspect of our daily life thus communications through internet is becoming inevitable. Computer...
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Android Rogue Application Detection Using Image Resemblance and Reduced LDA
Nowadays, the expanding diffusion ofAcharya, Saket AndroidRawat, Umashankar phonesBhatnagar, Roheet along with the substantial usage of mobile...
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IoT-Malware Classification Model Using Byte Sequences and Supervised Learning Techniques
Internet of things (IoT) provides us a way of interconnecting various mobile devices, handheld devices to accomplish tasks in diversified sectors....
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Deep Learning Based Malware Detection for IoT Devices
Internet of Things (IoT) in military environment for the most part comprises of a different scope of Internet-associated gadgets and hubs (for...
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Ensemble Model Ransomware Classification: A Static Analysis-based Approach
Johnson, Shanoop Gowtham, R. Nair, Anand R.The growth of malware attacks has been phenomenal in the recent past. The COVID-19 pandemic has...
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Malware Detection Using Machine Learning Approach
These days, Malware has become a significant andMuppalaneni, Babu develo** warning to safety, identification of malware has become tough. Numerous...
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Malware Detection and Classification Using Ensemble of BiLSTMs with Huffman Feature Optimization
Context: Malware attacks are responsible for data breaches and financial losses across the globe. Traditional signature-based malware detection...
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Deep Learning for Windows Malware Analysis
Malwares, such as ransomware, Trojans, spyware, and botnets, are the most common cyber-threats that can cause significant damages for organizations,...
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Machine learning aided malware detection for secure and smart manufacturing: a comprehensive analysis of the state of the art
In the last decade, the number of computer malware has grown rapidly. Currently, cybercriminals typically use malicious software (malware) as a means...
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Hybrid Deep Learning Approach Based on LSTM and CNN for Malware Detection
Malware analysis is essential for detecting and mitigating the effects of malicious software. This study introduces a novel hybrid approach using a...
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Ransomware Detection Service: Execution and Analysis Using Machine Learning Techniques
Network security faces an escalating threat from hacker attacks due to the proliferation and extensive adoption of computer and internet technology....
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Generation of Control Flow Graph on Self-Modification Viruses
A computer virus is a well-known program that has the ability to self-replicate. When executed, a virus can copy itself into other files and perform...
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DockerWatch: a two-phase hybrid detection of malware using various static features in container cloud
As an emerging virtualization technology, the Linux container provides a more lightweight, flexible, and high-performance operating-system-level...
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On the Detection Limitations of the Re-entrancy Attacks on Ethereum
In recent years, the emergence of Ethereum has brought people a new way of life. Many users tend to deposit funds into different smart contracts, but...
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Comparative Analysis of Malware Classification Using Supervised Machine Learning Algorithms
Privacy is a myth, a statement persistently encountered when talking about the world of Internet. Malwares are a constant, ominous threat to data...