[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123244-en":3,"doc-seo-123244-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123244,1099514067415,"Rowan","https://ap-avatar.wpscdn.com/avatar/100002539d78ffe74a7?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779092875211072502",8,"Research & Report","A Review on Recent Approaches of Machine Learning, Deep Learning, and Explainable Artificial Intelligence in Intrusion Detection Systems - Abstract","Network security is increasingly vital, and intrusion detection systems (IDS) are central to defending networks by analyzing traffic and supporting confidentiality, integrity, and availability. Intrusion detection is treated as a classification task that separates benign activity from attacks using machine learning and deep learning models, aiming to improve detection capability while reducing false alarms. This paper reviews current ML, DL, and explainable artificial intelligence (XAI) techniques for intrusion detection, summarizes key guidance for researchers integrating these models, and concludes with open challenges in the field.","A Review on Recent Approaches of Machine Learning, Deep Learning, and Explainable Artificial Intelligence in Intrusion  \nDetection Systems  \nSeshu Bhavani Mallampati 1, Hari Seetha2*  \n1- VIT-AP University, School of Computer Science and Engineering, Near Vijayawada, Andhra Pradesh, India.  \n[Email: bhavani.20phd7017@vitap.ac.in](Email: bhavani.20phd7017@vitap.ac.in)  \n2- VIT-AP University, Center of Excellence, AI and Robotics, Near Vijayawada, Andhra Pradesh, India.  \nEmail: [seetha.hari@vitap.ac.in](seetha.hari@vitap.ac.in)(Corresponding author)  \nReceived: 25 September 2022 Revised: 12 November 2022 Accepted: 20 December 2022  \nABSTRACT:  \nIn recent decades, network security has become increasingly crucial, and intrusion detection systems play a critical role in securing it. An intrusion Detection System (IDS) is a mechanism that protects the network from various possible intrusions by analyzing network traffic. It provides confidentiality and ensures the integrity and availability of data. Intrusion detection is a classification task that classifies network data into benign and attack by using various machine learning and deep learning models. It further develops a better potential solution for detecting intrusions across the network and mitigating the false alarm rate efficiently. This paper presents an overview of current machine learning (ML), deep learning (DL), and Explainable Artificial intelligence (XAI) techniques. Our findings provide helpful advice to researchers who are thinking about integrating ML and DL models into network intrusion detection. At the conclusion of this work, we outline various open challenges.  \nKEYWORDS: Network Security, Intrusion Detection, IPS, Preprocessing, SMOTE, Datasets, Attacks, Feature Selection, XAI.  \n1. INTRODUCTION  \nIn the present era, the number of devices related to smart homes, transportation, manufacturing, and healthcare has grown, so the volume of confidential and crucial data traveling across the network has expanded significantly over the last decade. However, with the accelerated growth in technology, there was a momentous change in the network size. As an outcome, a large volume of information was generated and shared among the network nodes [1]. Providing security to such data has become challenging because every node present in the network is endangered due to several zero-day attacks. According to research, ransomware attackers targeted the financial, government, and transportation industries the most. For example, Fig. 1 shows the total number of ransomware attacks worldwide from 2016 to the first half of 2022 [2] .  \nTo address security issues, various measures such as firewalls and authentication protocols can be used. They serve as the first layer of defense against various external threats to edge devices. On the other hand, these security mechanisms have limitations and can be easily exploited  \nby attackers. In addition, Anderson Jim proposed an IDSin the year 1980 [3] . Since then, a number of monitoring solutions, including intrusion detection and prevention systems (IDS and IPS), have been suggested and subsequently implemented[4] .  \nFig. 1. Number of ransomware attacks.  \nThe IDS is classified based on Deployment and the Detection mechanism. The classification of IDS is illustrated in Fig. 2 [1] .  \nThe deployment-based IDS is further classified as host-based, network-based, and hybrid. Deploymentbased IDS depends on how events related to attacks are gathered, processed, and dealt with, and these systems can be distributed, centralized, or hybrid. Each method offers benefits and drawbacks regarding cost, performance, and other factors.  \nFig. 2. Classification of IDS.  \nThe detection-based IDS is categorized as signature-based and anomaly-based. While signaturebased IDS has been extensively used to detect known attacks accurately with a low false alarm rate, it still has been excoriated for its inability to mitigate unknown attacks [5]. One solution t","cbCaijRLdAbtJK1d","https://ap.wps.com/l/cbCaijRLdAbtJK1d","pdf",845139,1,26,"English","en",105,"# Introduction\n## IDS classification (deployment and detection mechanisms)\n## Signature-based vs anomaly-based detection\n## AI, ML, and DL foundations\n## Common ML and DL models for IDS","[{\"question\":\"What role do intrusion detection systems play in network security?\",\"answer\":\"They protect networks by analyzing traffic and help ensure confidentiality, integrity, and availability while identifying malicious activity.\"},{\"question\":\"How is intrusion detection typically formulated in this work?\",\"answer\":\"As a classification task that labels network data as benign or attack using machine learning and deep learning models.\"},{\"question\":\"What are the main differences between signature-based and anomaly-based IDS?\",\"answer\":\"Signature-based IDS accurately detects known attacks with low false alarms but struggles with unknown attacks, while anomaly-based IDS profiles normal behavior to raise alerts for novel threats, often with higher false positives.\"}]","A Review on Recent Approaches of Machine Learning, Deep Learning, and Explainable Artificial Intelligence in Intrusion Detection Systems - Abstract | PDF",1785815427,66,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-review-on-recent-approaches-of-machine-learning-deep-learning-and-explainable-artificial-intelligence-in-intrusion-detection-systems-abstract","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-review-on-recent-approaches-of-machine-learning-deep-learning-and-explainable-artificial-intelligence-in-intrusion-detection-systems-abstract/123244/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What role do intrusion detection systems play in network security?","Question",{"text":75,"@type":76},"They protect networks by analyzing traffic and help ensure confidentiality, integrity, and availability while identifying malicious activity.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is intrusion detection typically formulated in this work?",{"text":80,"@type":76},"As a classification task that labels network data as benign or attack using machine learning and deep learning models.",{"name":82,"@type":73,"acceptedAnswer":83},"What are the main differences between signature-based and anomaly-based IDS?",{"text":84,"@type":76},"Signature-based IDS accurately detects known attacks with low false alarms but struggles with unknown attacks, while anomaly-based IDS profiles normal behavior to raise alerts for novel threats, often with higher false positives.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]