Enhancing Cyber security Frameworks: Integrating Pigeon-Inspired Optimization and Dense Neural Networks for Advanced Intrusion Detection Using the CIC-IDS-2017 Dataset.
Keywords:
Intrusion Detection Systems, zero-day attacks, Convolutional Neural Networks, Pigeon Inspired Optimization(PIO), Deep Neural Networks, Dense Neural Networks, operational efficiency, network security enhancementAbstract
This paper presents a novel approach to bolster network intrusion detection systems through the synergy of Dense Neural Networks (DNN) and Pigeon-Inspired Optimization (PIO). Leveraging the principles of bio-inspired swarm intelligence, this methodology significantly augments the execution of intrusion recognition on the widely recognized CIC-IDS-2017 dataset. The core of this research revolves around utilizing PIO for the meticulous optimization of hyper parameters and features in a DNN architecture tailored for intrusion detection. The effectiveness of PIO is meticulously analyzed, with a focus on its role in feature selection and hyper parameter adjustment to enhance model efficiency. The optimized DNN structure demonstrates exceptional precision, evidenced by a minimal loss of 0.005 and an impressive accuracy rate of 99.91%. The model's prowess is further assessed through a system of measurement such as recall, accuracy and F1-score across various classes, providing a comprehensive evaluation of its performance. Despite the model's overall efficacy, challenges about memory consumption are acknowledged. A significant outcome of this research is the validation of the impact of biologically influenced optimization and feature selection in enhancing intrusion detection systems. The model's high accuracy with a reduced feature set underscores the value of streamlined models in practical applications. Furthermore, the paper proposes adjustments to the model architecture and other refinement techniques aimed at addressing existing limitations and boosting performance. The findings and methodologies introduced in this research offer cyber security experts innovative tools and strategies in network security, particularly in optimizing intrusion detection systems. This advancement marks a significant contribution to the field, promising more effective and efficient cyber security solutions.
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