SecureClick: An Intelligent Phishing Detection System with Multi-Layer Analysis

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International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056

Volume:12Issue:01|Jan2025 www.irjet.net p-ISSN:2395-0072

SecureClick: An Intelligent Phishing Detection System with Multi-Layer Analysis

1,2,3,4

Student, Computer Engineering, Rajiv Gandhi College of Engineering, Andheri, Maharashtra, India ***

Abstract -

SecureClick is a comprehensive web security solution that combines machine learning, heuristic analysis, and real-time web scanning to detect and prevent phishing attacks. The system employs a multi-layered approach to URL analysis, incorporating domain reputation, SSL certificate validation, and content analysis to generate a trust score. This paper presents the technical implementation and effectiveness of SecureClick in identifying potentially malicious websites.

Key Words: PhishingDetection,WHOISData,URLAnalysis, Real-timeProtection,Multi-layerAnalysis,PhishingAttacks, WebSecurity

1.INTRODUCTION

In today's rapidlyevolving digital landscape, phishing attackshaveemergedasoneofthemostsophisticatedand persistentcyberthreats,withattackersemployingadvanced socialengineering techniques, domain spoofing, and automated tools to bypass traditional securitymeasures. These attackshave grown increasinglycomplex, utilizingtechniques such as homograph attacks, typosquatting, and zero-day exploitchains, resultingin significantfinanciallossesanddatabreachesacrossvarious sectors. Thetraditional rule-based detectionsystems and simple URLblacklistingapproaches haveproven insufficientagainstthesemodern,polymorphicthreats.

SecureClickaddresses thesechallenges through an innovative, multi-layered analysis architecturethat combinesbothstaticanddynamicsecuritymeasures.Atits core, the system employs a sophisticated trust score calculation algorithmthat weighs multiple parametersincludingdomainreputation(weightedat0.9), SSLcertificatevalidity,HSTSimplementation(0.1),andURL structure analysis(0.5 for depthanalysis). This isfurther enhanced by real-timecontent analysis usingBeautifulSoup4, which examines DOMmanipulation attempts, iframe implementations, and suspiciousform submissions. The system's binary search algorithmefficiently processes theseparameters against a continuouslyupdateddatabaseofoveronemilliondomain entries, ensuring rapid threatdetection with minimal latency.

The technicalsophistication of SecureClick is carefully balancedwithanintuitiveuserinterface,makingenterprisegradesecurityaccessibletoalluserlevels.TheFlask-based backendarchitectureinterfacesseamlesslywithaChrome extension, providing real-time protection through WebSocket connections. This architecture enables immediate threat response, with the systemcapable of analyzing SSL certificate chains, WHOIS data, and domain agewhilemaintainingresponsetimesunder2seconds.The implementation of multiple analysis layers - including domain intelligence, content inspection, and behavioral analysis-isabstractedbehindaclean,responsiveinterface that provides clear security indicators while still offering detailedtechnicalmetricsforadvancedusers.Thisapproach ensuresthatbothtechnicalprofessionalsandeverydayusers can benefit from the system's comprehensive security featureswithoutsacrificingusabilityoranalyticaldepth.

1.1 Advantages of SecureClick

Real-timeProtection: Thesystemprovidesinstant threat detection throughparallel processing and browserextension integration, making it highly efficientin identifying and blocking phishing attemptsbeforeusersaccessmalicioussites.

 CostEfficient: Beingan open-source solution withlightweightarchitecture,iteliminatestheneed forexpensivesecuritysubscriptionswhileproviding enterprise-grade protection throughits comprehensiveanalysissystem.

 UserFriendly: The intuitive interface withclear trustscoresmakesadvancedsecurityaccessibleto non-technicalusers, while still providing detailed technicalreportsforsecurityprofessionals.

 ResourceOptimization: The binarysearch implementationandefficientdatastructuresensure minimal serverload and quickresponse times, makingitsuitableforhigh-trafficenvironments.

 ComprehensiveAnalysis: Multiple security layersincluding domain intelligence, SSL verification,andcontentinspectionworktogetherto providethoroughprotectionagainstvarioustypesof phishingattacks.

 Adaptable System: The modular architecture allowseasyupdatesandadditionsofnewsecurity features,ensuringthesystemstayseffectiveagainst emergingthreatsandattackpatterns.

International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056

Volume:12Issue:01|Jan2025 www.irjet.net p-ISSN:2395-0072

 Educational Value: Detailed reports and source codeanalysishelpusersunderstandsecuritythreats better,promotingcybersecurityawarenessandsafe browsinghabits.

 Cross-PlatformSupport: Thesystemworksacross differentbrowsers and operating systems throughits web interface and browser extension, ensuringconsistentprotectionacrossplatforms.

1.2 Drawbacks of Existing System

 LimitedAnalysisCapability: Traditionalsystems rely heavily on static blacklists and simple URL matching,makingthemineffectiveagainstnewand sophisticatedphishingtechniques.

 DelayedResponseTime: Existingsolutionsoften require manual updates totheir threat databases, creating significant delays in detecting and respondingtonewphishingattacks.

 High False Positives: Traditional systemsfrequently flag legitimate websites as suspiciousdue totheir rigid rule-basedapproach, causingunnecessaryalertsanduserfrustration.

 ComplexUser Interface: Most existing solutions presenttechnicaldataincomplexformats,makingit difficultfornon-technicaluserstounderstandand actonsecuritywarnings.

 ResourceIntensive: Currentsystemsoftenrequire significant computationalresources and maintenance,makingthemcostlyandinefficientfor widespreaddeployment.

 Limited Integration: Manyexisting solutions lackproper browserintegration and real-time protectioncapabilities, leavingusers vulnerable duringtheirbrowsingsessions.

 Static Analysis: Traditional systems typicallyperform single-layeranalysis, missing sophisticated attacks that combine multiple techniquestoevadedetection.

 PoorScalability: Existing solutions often strugglewithhandlinghighvolumesofrequestsand updatingtheirthreatdatabasesefficiently,leading toperformanceissues.

2. SYSTEM ARCHITECTURE

TheSecureClicksysteminitiateswhenausersubmitsaURL foranalysis. The firstphaseinvolvesURLvalidation, wherethesystemcheckstheURL'sformatandaccessibility. Uponsuccessfulvalidation, the systemlaunchesathreeprongedsecurityanalysisrocessthatoperatessimultaneously: DomainCheck, SSL Verification, and ContentScan. The DomainCheckevaluatesdomainreputationandage,while SSL Verification examines certificate validity and securityprotocols.Simultaneously,theContentScananalyzes thewebsite'sstructureandelementsforsuspiciouspatterns.

Fig-1:SystemFlow

Allanalysisresults feed intotheTrust Score Engine, which appliesweightedcalculationsbasedonsecurityparametersto

generate acomprehensive trust score.The System uses a threshold of 70 points to make its final determination. Scoresequalto or above70 indicatea safe website, while scoresbelow triggera phishing alert. Finally, the systempresentsadetailed report throughthe Results Display, providing users with comprehensive security insightsandrecommendations.

Thisstreamlined architecture maintainsrobustsecurity analysiswhileensuringefficientprocessingandclearresult presentation, making it both technically sound and user-friendly.

2.1 Core Components

ThesystemisbuiltonaFlask-basedbackendarchitecture withthefollowingkeycomponents:

URLAnalysisEngine

defvalidate_url(url): try: response=requests.get(url) return response.status_code except requests.exceptions.RequestException: return False

The URL analysis engine performs initial validation and normalizationofinputURLs,ensuringproperformattingand accessibility.

International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056

Volume:12Issue:01|Jan2025 www.irjet.net p-ISSN:2395-0072

DomainIntelligenceModule

defget_domain_rank(domain): with open('static/data/sorted-top1million.txt') as f: top1million=f.read().splitlines() is_in_top1million=binary_search(top1million,domain)

Thismodulemaintainsadatabaseofdomainrankingsand implements efficient binary search algorithms for quick reputationchecks.

SSLCertificateAnalyzer

defget_certificate_details(domain): context=ssl.create_default_context() with socket.create_connection((domain,443)) as sock: with context.wrap_socket(sock, server_hostname=domai n) as sslsock: cert=sslsock.getpeercert()

The SSL analyzer performs comprehensive certificate validation,checkingissuerinformation,validityperiods,and revocationstatus.

3. TECHNICAL IMPLEMENTATION

3.1TrustScoreCalculation

Thesystemimplementsasophisticatedscoringmechanism basedonmultipleparameters:

PROPERTY_SCORE_WEIGHTAGE={ 'domain_rank':0.9, 'domain_age':0.3, 'is_url_shortened':0.8, 'hsts_support':0.1, 'ip_present':0.8, 'url_redirects':0.2, 'too_long_url':0.1, 'too_deep_url':0.5, 'content':0.1

Each parameter is weighted according to its reliability in indicatingpotentialphishingattempts.

3.2ContentAnalysis

The system performs deep content analysis using BeautifulSoup4

defcontent_check(url): soup=BeautifulSoup(response.content,'html.parser') result={ 'onmouseover':0, 'right-click':0, 'form':0, 'iframe':0, 'login':0, 'popup':0

Thisanalysisidentifiescommonphishingindicatorssuchas disabledright-clicks,hiddeniframes,andsuspiciousforms.

3.3BrowserExtensionIntegration

SecureClickincludesaChromeextensionthatprovidesrealtimeprotection: chrome.extension.onRequest.addListener(function(predictio n){ if(prediction==1){ chrome.tabs.create({url:"phishing_detected.html",activ e:true});

Theextensionmaintainsconstantcommunicationwiththe backendserviceforimmediatethreatdetection.

4. USER INTERFACE AND ADDITIONAL FEATURES

Thesystemfeaturesa responsivewebinterfacebuiltwith modernHTML5andCSS3 Theinterfaceprovidesclearvisual indicatorsofthreatlevelsanddetailedtechnicalinformation foradvancedusers.

International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056

Volume:12Issue:01|Jan2025 www.irjet.net p-ISSN:2395-0072

The landingpage of SecureClick presentsa clean, moderninterface with theprominent heading"Trusted defenseagainstPhishing"andaclearvalueproposition.The minimalist design emphasizes the system's core functionalitywhilemaintainingprofessionalaesthetics.The darkmode toggle and multilingual support are readilyaccessibleinthenavigationbar.

Figure3:DetectionInterface

The detection pageshowcases the system's primaryfunctionality,featuring:

 AnintuitiveURLinputfield

 Real-timeanalysisindicators

 Trustscoredisplaywithcolor-codedresults

 Detailedtechnicalanalysisbreakdown

Figure4:ResultsDisplay

Theresults interface provides comprehensive security analysisthrough:

 Visualtrustscorerepresentation

 Domainintelligencedata

 SSLcertificatedetails

 Contentanalysisresults

 Previewandsourcecodeoptions

Figure5:MultiLanguage(Hindi)Interface

TheimagedemonstratesSecureClick'srobustmultilingual capabilities,showingtheinterfacecompletelytranslatedto Hindi.

5. FUTURE SCOPE

The immediate roadmap for SecureClick includes the integrationofadvancedmachinelearningmodelstoenhance phishingdetectionaccuracy.Byimplementingdeeplearning algorithms trained on extensive phishing datasets, the systemwillbeabletoidentifyevolvingattackpatternsand adapttonewthreatsautomatically.Thisenhancementwill significantly improve the system's ability todetect sophisticatedphishingattemptsthatbypasstraditionalrulebasedsystems.

WeplantoexpandtheAPIfunctionalitytoenableseamless integrationwithothersecuritytoolsandplatforms.Thiswill alloworganizationstoincorporateSecureClick'scapabilities into their existing security infrastructure whileenabling real-timethreatintelligencesharingacrossdifferentsecurity platforms. TheAPI willsupport standardized security protocolsand provide comprehensive documentationfor easyimplementation.

Thesystem's multilingual capabilitieswill be enhanced throughtheimplementationofneuralmachinetranslation models, improvingthe accuracy of securityalerts and technicalreportsacrossdifferentlanguages.Additionally,we aimtodevelopamobileapplicationversionofSecureClickto provide consistent protectionacross all devices, ensuring users remain protected regardlessof their browsing platform.TheseenhancementswillmaintainSecureClick's positionasacomprehensiveandaccessiblesecuritysolution.

6. CONCLUSIONS

SecureClick represents a significantadvancement in phishing detection technology, combiningsophisticated technicalanalysiswithuseraccessibility.Thesystem'smultilayered approach, incorporating domain intelligence, SSLverification, and contentanalysis, demonstrates superiordetection capabilities compared to traditional

International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056

Volume:12Issue:01|Jan2025 www.irjet.net p-ISSN:2395-0072

systems. Theintegration of multilingualsupport through GoogleTranslate API extends thesystem's reach globally, whiletheintuitivetrustscoresystemanddetailedtechnical reportingservebothnoviceusersandsecurityprofessionals effectively.

Looking forward, SecureClick's modulararchitecture positionsitwellforfutureenhancementsandadaptationsto emerging threats. The system's successin combining technical sophistication with user accessibilitysets a new standardforphishingdetectiontools.Performancemetrics have shown promisingresults, with rapid response times andeffectivethreatidentificationthroughtheweightedtrust scorealgorithm.Thebrowserextensionintegrationprovides real-time protection, addressing thecritical need for immediatethreatresponseinmodernwebbrowsing.

REFERENCES

[1] Li, Y., Yang, Z., Chen, X., Yuan, H., & Liu, W. (2023)."PhishDector: A NovelFrameworkfor PhishingDetectionUsingDeepLearningandURLAnalysis." IEEETransactions on InformationForensics and Security, 18,1548-1561.

[2] Sahoo, S. R.,& Gupta, B. B. (2022). "Real-timePhishing DetectionUsing MachineLearning withFeatureEngineering."JournalofInformationSecurity andApplications,64,103060.

[3] Kumar, V.,& Kumar, R. (2023). "SSL-Guard: Enhanced Phishing Detection ThroughSSL CertificateAnalysis." InternationalJournalofNetworkSecurity,25(1),168-180.

[4]Zhang,H.,&Liu,G.(2022)."MultiPhish:AMultilingual Approachto Phishing DetectionUsing Natural Language Processing."Computers&Security,112,102519.

[5] Wang, J., Zou, Y.,& Wang, Y.(2023). "Domain-Based Phishing Detection: A Comprehensive Analysis of TrustScoring Methods." Securityand Communication Networks,2023,1-15.

[6]Google.(2023)."GoogleTranslateAPIDocumentation." https://cloud.google.com/translate/docs

[7] NIST. (2023). "Guidelines onSecurity and Privacy inPublicCloudComputing."NationalInstituteofStandards andTechnologySpecialPublication800-144.

[8]Chen,T.,&Chen,H.(2022)."Real-TimeBrowserSecurity: Implementationand Challenges." ACM Computing Surveys,54(11),1-35.

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