Công bố khoa học

A Method of Mutating Windows Malwares using Reinforcement Learning with Functionality Preservation

2 năm trước

Recently, the development in both quantity and complication of malware has raised a need of powerful malware detection solution. The outstanding characteristics of machine learning (ML) and deep learning (DL) techniques has been leveraged in the fight against malware. However, they are proved to be vulnerable against adversarial attacks, where…

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A Privacy-Preserving Approach For Building Learning Models in Smart Healthcare using Blockchain and Federated Learning

2 năm trước

Nowadays, the amount of data generated from Internet of Things (IoT) devices is increasing, paving the way for the development of artificial intelligence (AI) applications. However, with the traditional AI approach, users sharing their raw data causes many concerns in terms of privacy leakage. There have been reports that there…

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Leveraging Deep Learning Image Classifiers for Visual Similarity-based Phishing Website Detection

2 năm trước

Phishing is a major cybersecurity threat that is increasingly dangerous and complicated, especially during a global pandemic when there is a great need for remote work and communication between Internet users. Moreover, the challenge is even greater when the crime of using high technology increase with the speed of development…

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Adversarial AutoEncoder and Generative Adversarial Networks for Semi-Supervised Learning Intrusion Detection System

2 năm trước

As one of the defensive solutions against cyberattacks, Intrusion Detection System (IDS) plays an important role in observing the network state, alerting suspicious actions that can break down the system. There are many attempts of adopting Machine Learning (ML) in IDS to achieve the high performance in intrusion detection. However,…

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A Method for Flexible Definition and Automatic Implementation of Laboratory Environment in Online Training Platforms

2 năm trước

Cloud infrastructure enables individuals, organizations, and enterprises to offer scalable and elastic resources to support business operations remotely. The demand for digital transformation encourages communities and technical professionals to adopt cloud computing and automation platforms for facilitating their resource capacity, including operating systems, networks, and applications. Of cloud-based applications for…

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A Blockchain-Based Authentication and Access Control for Smart Devices in SDN-Enabled Networks for Metaverse

2 năm trước

Emerging with outstanding features in network management, Software Defined Networking (SDN) is considered as a flexible and efficient paradigm in the context of smart city including a massive number of heterogeneous devices. In the vision of Metaverse towards, SDN plays important roles for network orchestration to support interactive experience through…

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Fool your enemies: Enable Cyber Deception and Moving Target Defense for Intrusion Detection in SDN

2 năm trước

The adoption of deception technology constructed to throw off stealthy attackers from real assets and gather intelligence about how they operate is gaining ground in the network system. Also, some static honeypots are deployed in the network system to attract adversaries for avoiding them accessing the real targets. This leads…

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Federated learning-based cyber threat hunting for APT attack detection in SDN-enabled networks

2 năm trước

Threat hunting is the action of seeking harmful actors lurking in the network or the system in the early stage with the assumption of attackers already broke the cy-ber defense solution. This defense solution requires collecting more knowledge inside and outside to search potential threats in each organization. To leverage…

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Federated Intrusion Detection on Non-IID Data for IIoT networks using Generative Adversarial Networks and Reinforcement Learning

2 năm trước

Federated learning has become the promising approach for building collaborative intrusion detection systems (IDS) as providing privacy guaranteeing among data holders. Nevertheless, the non-independent and identically distributed (Non-IID) data in real-world scenarios negatively impacts the performance of aggregated models from training client updates. To this end, in this paper, we…

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A case study for evaluating learners’ behaviors from online cybersecurity training platform on digital forensics subject

2 năm trước

Virtual cybersecurity training platforms play an important role in developing the knowledge and practice skills for students in educational institution and universities. It helps learners can access to virtual laboratory through web-interface without any geolocation restriction, especially in the Covid-19 pandemic. Furthermore, instructors can monitor and understand learners’ behaviors in…

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