基于混合人工原生动物的攻击检测 JADE

Q1 Mathematics Applied Sciences Pub Date : 2024-09-13 DOI:10.3390/app14188280
Ahmad k. Al Hwaitat, Hussam N. Fakhouri
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引用次数: 0

摘要

本文提出了一种新颖的混合优化算法,它将 JADE 自适应差分进化算法与人工原生动物优化器 (APO) 相结合,用于解决复杂的优化问题和检测攻击。所提出的 APO-JADE 混合算法充分利用了 JADE 的自适应探索能力和 APO 的密集开发策略,确保了搜索过程的稳健性,并兼顾了全局和局部优化。最初,该算法在自适应控制参数的指导下,利用 JADE 的突变和交叉操作来探索搜索空间,防止过早收敛。随着优化进程的推进,算法会动态过渡到 APO 机制,利用列维飞行和自适应变化因素来完善探索阶段确定的最佳解决方案。这种探索和利用阶段的整合增强了算法高效收敛到高质量解决方案的能力。通过实验模拟验证了 APO-JADE 的性能,并使用 2022 年和 2021 年 IEEE 进化计算大会基准(CEC)与最先进的算法进行了比较。结果表明,APO-JADE 取得了优于其他算法的结果。考虑到实用性,提议的 APO-JADE 被用于解决攻击检测中的实际应用,并在 DS2OS、UNSW-NB15 和 ToNIoT 数据集上进行了测试,证明了其稳健的性能。
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Hybrid Artificial Protozoa-Based JADE for Attack Detection
This paper presents a novel hybrid optimization algorithm that combines JADE Adaptive Differential Evolution with Artificial Protozoa Optimizer (APO) to solve complex optimization problems and detect attacks. The proposed Hybrid APO-JADE Algorithm leverages JADE’s adaptive exploration capabilities and APO’s intensive exploitation strategies, ensuring a robust search process that balances global and local optimization. Initially, the algorithm employs JADE’s mutation and crossover operations, guided by adaptive control parameters, to explore the search space and prevent premature convergence. As the optimization progresses, a dynamic transition to the APO mechanism is implemented, where Levy flights and adaptive change factors are utilized to refine the best solutions identified during the exploration phase. This integration of exploration and exploitation phases enhances the algorithm’s ability to converge to high-quality solutions efficiently. The performance of the APO-JADE was verified via experimental simulations and compared with state-of-the-art algorithms using the 2022 IEEE Congress on Evolutionary Computation benchmark (CEC) 2022 and 2021. Results indicate that APO-JADE achieved outperforming results compared with the other algorithms. Considering practicality, the proposed APO-JADE was used to solve a real-world application in attack detection and tested on DS2OS, UNSW-NB15, and ToNIoT datasets, demonstrating its robust performance.
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来源期刊
Applied Sciences
Applied Sciences Mathematics-Applied Mathematics
CiteScore
6.40
自引率
0.00%
发文量
0
审稿时长
11 weeks
期刊介绍: APPS is an international journal. APPS covers a wide spectrum of pure and applied mathematics in science and technology, promoting especially papers presented at Carpato-Balkan meetings. The Editorial Board of APPS takes a very active role in selecting and refereeing papers, ensuring the best quality of contemporary mathematics and its applications. APPS is abstracted in Zentralblatt für Mathematik. The APPS journal uses Double blind peer review.
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