2 năm trước
Advanced persistent threats (APT) are increasingly sophisticated and pose a significant threat to organizations’ cybersecurity. Detecting APT attacks in a timely manner is crucial to prevent significant damage. However, hunting for APT attacks requires access to large amounts of sensitive data, which is typically spread across different organizations. This makes…
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Recently, the application of machine learning (ML) in the field of cybersecurity, particularly in the detection and prevention of malware, has received significant attention and interest. Numerous research works on malware analysis have been proposed, showing promising results for practical applications. In such works, the use of Generative Adversarial Networks…
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With the growth and expansion of the internet, web attacks have become more powerful and pose a significant threat in the cyber world. In response to this, this paper presents a deceptive approach for gathering malicious behavior to understand the strategies used by web attackers. The harmful requests collected through…
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The increasing proliferation of phishing and scamming websites has become a significant threat to the safety and security of internet users. Accurately detecting such websites is crucial in mitigating their negative impact. While various techniques for detecting phishing and scamming websites exist, machine learning-based approaches have gained significant attention in…
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Recently, Software Defined Networking (SDN) has emerged as the key technology in programming and orchestrating security policy in the security operations centers (SOCs) for heterogeneous networks. Typically, machine learning-based intrusion detection systems (ML-IDS) have been deployed and associated with SDN to leverage the features of a programmable network to defend…
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Penetration testing is one of the most common methods for assessing the security of a system, application, or network. Although there are different support tools with great efficiency in this field, penetration testing is done mostly manually and relies heavily on the experience of the ethical hackers who are doing…
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Software-defined networking (SDN) is a potential approach for modern network architecture, which has received great attention recently. SDN-based networks also face security issues, and they can become targets of cyberattacks. Cyber threat hunting is one of the security solutions proposed for early attack detection in SDN. Developing machine learning-based IDS…
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In large-scale networks like the Industrial Internet of Things (IIoT), it is more important to monitor and enforce the security policy within an appropriate time due to the continuous widespread of cyberattacks. This is a tough challenge in traditional network architecture; thus, each network element’s network management is unsuitable for…
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The rising development of machine learning (ML) techniques has become the motivation for research in applying their outstanding features to facilitate intelligent intrusion detection systems (IDSs). However, ML-based solutions also have drawbacks of high false positive rates and vulnerability to sophisticated attacks such as adversarial ones. Therefore, continuous evaluation and…
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Sharing medical data can help doctors to give a more rapid and accurate diagnosis of a patient’s health problems. However, electronic healthcare records (EHRs) are also considered sensitive data, whose sharing may raise issues of security and privacy. Most current healthcare systems not only manage their data in centralized databases…
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