[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123789-en":3,"doc-seo-123789-105":30,"detail-sidebar-cat-0-en-105":83},{"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},123789,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",6,"Technology","Binary Arithmetic Optimization Algorithm - Machine Learning based Intrusion Detection System","Intrusion Detection Systems (IDS) support prevention and identification of malicious actions across computer networks. Machine Learning methods recognize intrusions by learning patterns from large volumes of network traffic, while effectiveness heavily depends on choosing relevant, discriminative features. Feature Selection (FS) extracts the most informative feature subset to separate normal behavior from attacks. A BAOA-MLIDS approach combines BAOA-based FS with an optimal ML classifier, uses data preprocessing, applies Extreme Learning Machine for intrusion detection, and leverages HGSO for ELM hyperparameter tuning. Results on benchmark data show improved IDS performance.","Binary Arithmetic Optimization Algorithm with Machine Learning based Intrusion Detection System  \n1,*S. P. Senthilkumar, 2Dr. Aranga Arivarasn  \n1Research Scholar, Department of Computer & Information Science, Annamalai University, Annamalai Nagar-608 002  \nE-Mail: [senthil.sp74@gmail.com](senthil.sp74@gmail.com)  \n2Assistant Professor/Programmer, Department of Computer & Information Science,  \nAnnamalai University, Annamalai Nagar-608 002  \n[E-Mail: profarivarasan@yahoo.com](E-Mail: profarivarasan@yahoo.com)  \nAbstract—Intrusion Detection Systems (IDS) are significant for preventing and identifying malicious actions in computer networks. Machine Learning (ML) approaches are extremely executed for recognizing intrusion since it is investigating huge volumes of network traffic data and recognize designs indicative of intrusions. But, the performance of these ML approaches is greatly dependent upon the choice of relevant features which efficiently represent the network traffic data. Feature Selection (FS) is the procedure of recognizing the most informative and discriminative aspects in a given database. As part of Intrusion Detection (ID) utilizing ML, FS purposes for identifying the subset of features that are efficiently differentiated between normal network behaviour and malicious activities. This article proposes a Binary Arithmetic Optimization Algorithm with Machine Learning based Intrusion Detection System (BAOA-MLIDS) technique. The BAOA-MLIDS technique employs FS with an optimal ML classifier for the ID process. To accomplish this, the BAOA-MLIDS technique performs data preprocessing to scale the input data. Besides, the BAOA-MLIDS technique comprises BAOA based FS approach to choose optimal features. Moreover, Extreme Learning Machine (ELM) approach is utilized for the identification of the intrusions. Furthermore, Hunger Games Search Optimization (HGSO) approach was employed for the hyperparameter optimization of the ELM approach. The performance assessment of the BAOA-MLIDS model was examined on a standard dataset and the outputs outperformed the advancement of the BAOA-MLIDS model in the ID process.  \nKeywords-Network security; Parameter tuning; Intrusion detection system; Feature selection; Machine learning.  \nI. INTRODUCTION  \nThe network safety system has become a serious worldwide problem which can affect governments, enterprises, and individuals. The attacks rate against network systems has increased significantly and the attackers are continuing their strategies, which are used for development. ID is one solution to the problems against these outbreaks [1] . The IDS is efficient for identifying potential cyber-attacks. It applies the techniques for the classification and detection of the attacks [2] . There are two classes of IDS, such as (i) Anomaly (ii) Signature based IDS, represented as Anom-IDS and Sig-IDS. The sig-IDS method is detected outbreaks dependent upon formerly identified sequences, patterns, or a group of principles determined for the attack [3] . In the meantime, the Anom-IDS method can identify something changed than normal traffic, for instance, anomalies. The development of Anom-IDS over SigIDS; could be able to identify new attacks in the network system. Furthermore, due to the data source, Host and Network based IDS, represented as HIDS and NIDS, are two categories  \nof IDS [4] . The algorithm of HIDS can identify the attacks across the system by analyzing the data from audits on apps or database logs, firewall logs, and the operating system [5] . The method of NIDS can identify outside attacks before it arrives in the computer networks. NIDS is monitoring the traffic data  \nextracted from various network data sources in the network for detecting some threats. A general and effectual technique to design the IDS is ML.  \nIDS researchers have used different approaches for ID [6] . One of these methods is based on ML. This technique can detect and predict threats before they outcome in the ","cbCaieG6B6M6Q1Bb","https://ap.wps.com/l/cbCaieG6B6M6Q1Bb","pdf",1006978,1,8,"English","en",105,"# Introduction\n## Intrusion detection background and IDS types\n## Machine learning for intrusion detection\n# Related works","[{\"question\":\"What roles do ELM and HGSO play in the system?\",\"answer\":\"Extreme Learning Machine (ELM) is used for intrusion identification, and Hunger Games Search Optimization (HGSO) is employed to optimize ELM hyperparameters.\"}]","Binary Arithmetic Optimization Algorithm - Machine Learning based Intrusion Detection System | PDF",1785818569,20,{"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":78,"head_meta":80,"extra_data":82,"updated_unix":28},"binary-arithmetic-optimization-algorithm-machine-learning-based-intrusion-detection-system","",{"@graph":36,"@context":77},[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/technology/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/binary-arithmetic-optimization-algorithm-machine-learning-based-intrusion-detection-system/123789/",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],{"name":72,"@type":73,"acceptedAnswer":74},"What roles do ELM and HGSO play in the system?","Question",{"text":75,"@type":76},"Extreme Learning Machine (ELM) is used for intrusion identification, and Hunger Games Search Optimization (HGSO) is employed to optimize ELM hyperparameters.","Answer","https://schema.org",{"og:url":52,"og:type":79,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":81,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":84},[85,89,93,97,102,105,110,114,118,121,125],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":86,"show_sort_weight":87,"slug":88},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":90,"show_sort_weight":91,"slug":92},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Exam",70,"exam",{"id":98,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},5,"Comic",60,"comic",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":103,"slug":104},50,"technology",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},"Research & Report",30,"research-report",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":29,"slug":117},9,"Religion & Spirituality","religion-spirituality",{"id":29,"doc_module":4,"doc_module_name":46,"category_name":119,"show_sort_weight":29,"slug":120},"World Cup","world-cup",{"id":122,"doc_module":4,"doc_module_name":46,"category_name":123,"show_sort_weight":122,"slug":124},10,"Lifestyle","lifestyle",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":127,"show_sort_weight":98,"slug":128},19,"General","general"]