Mohammad A. Rahman

Mohammad Masum, Hossain Shahriar, Hisham Haddad et al.

Traditional network intrusion detection approaches encounter feasibility and sustainability issues to combat modern, sophisticated, and unpredictable security attacks. Deep neural networks (DNN) have been successfully applied for intrusion detection problems. The optimal use of DNN-based classifiers requires careful tuning of the hyper-parameters. Manually tuning the hyperparameters is tedious, time-consuming, and computationally expensive. Hence, there is a need for an automatic technique to find optimal hyperparameters for the best use of DNN in intrusion detection. This paper proposes a novel Bayesian optimization-based framework for the automatic optimization of hyperparameters, ensuring the best DNN architecture. We evaluated the performance of the proposed framework on NSL-KDD, a benchmark dataset for network intrusion detection. The experimental results show the framework's effectiveness as the resultant DNN architecture demonstrates significantly higher intrusion detection performance than the random search optimization-based approach in terms of accuracy, precision, recall, and f1-score.

Hisham A. Kholidy, Mohammad A. Rahman, Andrew Karam et al.

The 5G network would fuel next-gen, bandwidth-heavy technologies such as automation, IoT, and AI on the factory floor. It will improve efficiency by powering AR overlays in workflows, as well as ensure safer practices and reduce the number of defects through predictive analytics and real-time detection of damage. The Dynamic Spectrum Sharing (DSS) in 5G networks will permit 5G NR and 4G LTE to coexist and will provide cost-effective and efficient solutions that enable a smooth transition from 4G to 5G. However, this increases the attack surface in the 5G networks. To the best of our knowledge, none of the current works introduces a real-time secure spectrum-sharing mechanism for 5G networks to defend spectrum resources and applications. This paper aims to propose a Blockchain-based Decentralized Trusted Computing Platform (BTCP) to self-protect large-scale 5G spectrum resources against cyberattacks in a timely, dynamic, and accurate way. Furthermore, the platform provides a decentralized, trusted, and non-repudiating platform to enable secure spectrum sharing and data exchange between the 5G spectrum resources