摘要
由一位新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-关于智能系统的新研究结果已经公布。根据NewsRx Journalis TS在伊拉克巴格达的新闻报道，研究表明，“机器学习(ML)和深度学习(DL)技术已经证明了在开发有效的入侵检测系统方面的巨大潜力。”新闻记者从伊拉克大学的研究中获得了一句话：“这项研究对2018年至2023年入侵检测研究中ML、DL、优化算法和数据集的利用进行了系统回顾。我们设计了一个综合的搜索策略，从科学数据库中识别相关研究。在筛选了393篇符合纳入标准的论文后，我们利用文献计量分析技术提取和分析关键信息。根据新闻编辑的说法，这项研究得出的结论是：“研究结果揭示了这一研究领域的出版趋势，并确定了常用的算法，其中卷积神经网络、支持向量机、决策树和遗传算法是最常用的方法。综述还讨论了当前技术的挑战和局限性。”"综合了当前入侵检测技术的研究现状,以指导未来的入侵检测研究."
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New study results on intelligent systems have bee n published. According to news reporting from Baghdad, Iraq, by NewsRx journalis ts, research stated, "Machine learning (ML) and deep learning (DL) techniques ha ve demonstrated significant potential in the development of effective intrusion detection systems." The news reporters obtained a quote from the research from Al-Iraqia University: "This study presents a systematic review of the utilization of ML, DL, optimiza tion algorithms, and datasets in intrusion detection research from 2018 to 2023. We devised a comprehensive search strategy to identify relevant studies from sc ientific databases. After screening 393 papers meeting the inclusion criteria, w e extracted and analyzed key information using bibliometric analysis techniques. " According to the news editors, the research concluded: "The findings reveal incr easing publication trends in this research domain and identify frequently used a lgorithms, with convolutional neural networks, support vector machines, decision trees, and genetic algorithms emerging as the top methods. The review also disc usses the challenges and limitations of current techniques, providing a structur ed synthesis of the state-of-the-art to guide future intrusion detection researc h."
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