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XFedGraph-Hunter: An Interpretable Federated Learning Framework for Hunting Advanced Persistent Threat in Provenance Graph

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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A method of generating mutated Windows malware to evade ensemble learning

2 năm trước

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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A Deception and Continuous Training Approach for Web Attack Detection using Cyber Traps and MLOps

2 năm trước

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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A Consensus Protocol for Incentivizing Contribution from Decentralized Community for Machine Learning-based Scamming Website Detection

2 năm trước

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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Investigating on the Robustness of Flow-based Intrusion Detection System against Adversarial Samples using Generative Adversarial Networks  

2 năm trước

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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Leveraging Deep Reinforcement Learning for Automating Penetration Testing in Reconnaissance and Exploitation Phase

2 năm trước

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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A federated threat hunting system with big data analysis for SDN-enabled networks

2 năm trước

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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Cyber Threat Intelligence for Proactive Defense against Adversary in SDN-assisted IIoTs context

2 năm trước

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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DA-GAN: Domain Adaptation for Generative Adversarial Networks-assisted Cyber Threat Detection

2 năm trước

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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A Blockchain-based approach and Attribute-based Encryption for Healthcare Record Data Exchange

2 năm trước

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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