[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120846-en":3,"doc-seo-120846-105":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},120846,1649267921044,"Ava Thompson","https://us-avatar.wpscdn.com/avatar/1800007509477c92dfb?_k=1782875107921204101",8,"Research & Report","BSCSML - Design of an Efficient Bioinspired Security & Privacy Model for Cyber Physical System using Machine Learning - Abstract","With the increasing prevalence of Smart Grid Cyber Physical Systems with Advanced Metering Infrastructure (SG CPS AMI), securing internal components has become a paramount concern. Traditional mechanisms are insufficient against sophisticated threats, motivating bioinspired security and privacy models. This paper proposes a machine-learning based bio-inspired model inspired by the hybrid Grey Wolf Teacher Learner based Optimizer (GWTLbO), enabling real-time threat detection and adaptive privacy using k-privacy, t-closeness, and l-diversity. Supervised and unsupervised learning train recognition of known and unknown attacks, evaluated on real-time IoT data.","BSCSML: Design of an Efficient Bioinspired Security &Privacy Model for Cyber Physical System  \nusing Machine Learning  \nMegha Sanjay Wankhade1*, Suhasini Vijaykumar kottur2  \n1Assistant Professor: MCA Department,  \nNCRD’s Sterling Institute of Management Studies,  \nNerul, Navi Mumbai, India  \n[e-mail: meghasw@gmail.com](e-mail: meghasw@gmail.com)  \n2Principal: MCA Department  \nBharati Vidyapeeth's Institute of Management Studies and Research  \nBelapur, Navi Mumbai, India  \ne-mail: [suhasini.kottur12@gmail.com](suhasini.kottur12@gmail.com)  \nAbstract: With the increasing prevalence of Smart Grid Cyber Physical Systems with Advanced Metering Infrastructure (SG CPS AMI), securing their internal components has become one of the paramount concerns. Traditional security mechanisms have proven to be insufficient in defending against sophisticated attacks. Bioinspired security and privacy models have emerged as promising solutions due to their stochastic solutions. This paper proposes a novel bio-inspired security and privacy model for SG CPS AMI that utilizes machine learning to strengthen their security levels. The proposed model is inspired by the hybrid Grey Wolf Teacher Learner based Optimizer (GWTLbO) Method’s ability to detect and respond to threats in real-time deployments. The GWTLbO Model also ensures higher privacy by selecting optimal methods between k-privacy, t-closeness & l-diversity depending upon contextual requirements. This study improves system accuracy and efficiency under diverse attacks using machine learning techniques. The method uses supervised learning to teach the model to recognize known attack trends and uncontrolled learning to spot unknown attacks. Our model was tested using real-time IoT device data samples. The model identified Zero-Day Attacks, Meter Bypass, Flash Image Manipulation, and Buffer-level attacks. The proposed model detects and responds to attacks with high accuracy and low false-positive rates. In real-time operations, the proposed model can handle huge volumes of data efficiently. The bioinspired security and privacy model secures CPS efficiently and is scalable for various cases. Machine learning techniques can improve the security and secrecy of these systems and revolutionize defense against different attacks.  \nKeywords: Cyber Physical, Attacks, Security, Privacy, Bioinspired, Accuracy, Rates, Scenarios.  \nI. INTRODUCTION  \nBecause cyber-Physical systems are becoming more and more pervasive in our everyday lives, concerns regarding their privacy and security have become increasingly important for real-time scenarios via Privacy-aware Reconfigurable SecureFirmware Updating Framework (PRSUF) [1, 2, 3] . These systems, which combine the real and virtual worlds, have been implemented in a variety of fields, including healthcare, transportation, and energy production levels [4, 5, 6] . Because of the critical nature of these systems, cybercriminals are likely to target them under different attacks. As a result, it is imperative that robust security and privacy mechanisms be developed in order to protect these systems.  \nSmart Grid Cyber Physical Systems with Advanced Metering Infrastructure (SG CPS AMI) have been protected with the help of conventional security mechanisms such as firewalls, intrusion detection systems, and antivirus software. However,  \nin light of the increasingly sophisticated attacks that can be launched against these systems, they are no longer adequate asa line of defence. As a direct result of this, new approaches have emerged, such as models of security and privacy that are bioinspired and provide stochastic solutions [7, 8, 9] via use of Physically Unclonable Functions (PuFs) .  \nModels of security and privacy that are bio-inspired are an innovative approach to cybersecurity that draws inspiration from the ways in which nature detects and responds to threats. Bio-inspired security and privacy models [10, 11, 12] . These types of models draw a significant amount o","cbCaikb6Bx4p88XB","https://ap.wps.com/l/cbCaikb6Bx4p88XB","pdf",553802,1,12,"English","en",105,"# Abstract\n# I. Introduction\n## Smart Grid CPS AMI and limitations of conventional security\n## Bio-inspired security and privacy models\n## Integration with secure data storage and machine learning\n## Proposed model and learning strategy","[{\"question\":\"Why are conventional security mechanisms insufficient for SG CPS AMI?\",\"answer\":\"Conventional tools like firewalls and intrusion detection systems fail to defend against increasingly sophisticated attacks, making them inadequate as a line of defense.\"},{\"question\":\"What key idea does the proposed model use for bioinspired security and privacy?\",\"answer\":\"It leverages a hybrid Grey Wolf Teacher Learner based Optimizer (GWTLbO) to detect and respond to threats in real time, while improving privacy by selecting among k-privacy, t-closeness, and l-diversity based on context.\"},{\"question\":\"How does the model detect both known and unknown attacks?\",\"answer\":\"It applies supervised learning to recognize known attack trends and uses uncontrolled/unsupervised learning to identify unknown attack patterns.\"}]","BSCSML - Design of an Efficient Bioinspired Security & Privacy Model for Cyber Physical System using Machine Learning - Abstract | PDF",1785732319,30,{"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},"bscsml-design-of-an-efficient-bioinspired-security-privacy-model-for-cyber-physical-system-using-machine-learning-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/bscsml-design-of-an-efficient-bioinspired-security-privacy-model-for-cyber-physical-system-using-machine-learning-abstract/120846/",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","2026-08-03",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},"Why are conventional security mechanisms insufficient for SG CPS AMI?","Question",{"text":75,"@type":76},"Conventional tools like firewalls and intrusion detection systems fail to defend against increasingly sophisticated attacks, making them inadequate as a line of defense.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What key idea does the proposed model use for bioinspired security and privacy?",{"text":80,"@type":76},"It leverages a hybrid Grey Wolf Teacher Learner based Optimizer (GWTLbO) to detect and respond to threats in real time, while improving privacy by selecting among k-privacy, t-closeness, and l-diversity based on context.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the model detect both known and unknown attacks?",{"text":84,"@type":76},"It applies supervised learning to recognize known attack trends and uses uncontrolled/unsupervised learning to identify unknown attack patterns.","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},[93,97,101,105,110,115,120,122,127,130,134],{"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":29,"slug":121},"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]