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An extensive study of the effects of different deep learning models on code vulnerability detection in Python code
Deep learning has achieved great progress in automated code vulnerability detection. Several code vulnerability detection approaches based on deep...
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A security vulnerability predictor based on source code metrics
Detecting security vulnerabilities in the source code of software systems is one of the most important challenges in the field of software security....
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IoTvulCode: AI-enabled vulnerability detection in software products designed for IoT applications
The proliferation of the Internet of Things (IoT) paradigm has ushered in a new era of connectivity and convenience. Consequently, rapid IoT...
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Identifying the systemic importance and systemic vulnerability of financial institutions based on portfolio similarity correlation network
The indirect correlation among financial institutions, stemming from similarities in their portfolios, is a primary driver of systemic risk. However,...
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BovdGFE: buffer overflow vulnerability detection based on graph feature extraction
Automatically detecting buffer overflow vulnerabilities is an important research topic in software security. Recent studies have shown that...
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Enhancing BERT-Based Language Model for Multi-label Vulnerability Detection of Smart Contract in Blockchain
Smart contracts are decentralized applications that hold a pivotal role in blockchain-based systems. Smart contracts are composed of error-prone...
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Cyber-Attack Analysis Using Vulnerability Assessment and Penetration Testing
Networks and systems like computers and mobile devices are not secure enough and are vulnerable to numerous types of cyber-threats. The frequency of...
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Vulnerability Analysis of an Electric Vehicle Charging Ecosystem
The increase of electric vehicles has exacerbated the need for adequate security measures in the electric vehicle charging ecosystem (EVCE)....
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Software Vulnerability Detection Using an Enhanced Generalization Strategy
Detecting vulnerabilities in software is crucial for preventing cybersecurity attacks, and current machine learning-based methods rely on large...
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Vulnerability Detection and Response: Current Status and New Approaches
The rapid evolution of industrial components, the paradigm of Industry 4.0, and the new connectivity features introduced by 5G technology all...
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SPVF: security property assisted vulnerability fixing via attention-based models
The past few years have witnessed the wide application of machine learning models to fix vulnerabilities automatically. However, existing approaches...
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Application of Vulnerability Detection Technology Based on Network Space Recognition
The rapid development of the Internet has brought great convenience to people, and the impact of network attacks caused by vulnerabilities has...
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Vulnerability Scanner
The proliferation of cloud providers enables organizations to deploy applications that are affordable at scale. Deploying applications at scale is...
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Learning from what we know: How to perform vulnerability prediction using noisy historical data
Vulnerability prediction refers to the problem of identifying system components that are most likely to be vulnerable. Typically, this problem is...
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Vulnerability discovery based on source code patch commit mining: a systematic literature review
In recent years, there has been a remarkable surge in the adoption of open-source software (OSS). However, with the growing usage of OSS components...
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The application of neural network for software vulnerability detection: a review
To date, being benefited from the ability of automated feature extraction and the performance of software vulnerability identification, deep learning...
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A novel approach for software vulnerability detection based on intelligent cognitive computing
Improving and enhancing the effectiveness of software vulnerability detection methods is urgently needed today. In this study, we propose a new...
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An automatic algorithm for software vulnerability classification based on CNN and GRU
In order to improve the management efficiency of software vulnerability classification, reduce the risk of system being attacked and destroyed, and...
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Database Security
This chapter starts with an overview on database security. Then, access control is introduced with hands-on examples in the Structured Query Language...
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VulMAE: Graph Masked Autoencoders for Vulnerability Detection from Source and Binary Codes
The first graph masked auto-encoder (GraphMAE) model for software vulnerability detection is designed and developed, with a comparative evaluation...