Detecting phishing websites is essential for making sure the network privacy. We develop a well-defined framework that prevents users from fraudulent websites aiming to steal their personal information. So, hurry up and book yours lots now to get expertise solution for all your research work. Research Proposal will be framed under experts care a detailed plan flow will be explained of the methodology we will be using, further if you are not satisfied, we can remodel it as per your customized requirement. We serve as an one point solution for all your research needs.
Here are the steps to be followed to setup a phishing website detection project using machine learning (ML):
- Objective Definition:
- We detect when a website URL and its attributes are symbolizing of a phishing threat.
- Data Collection:
- Various datasets for phishing URLs and legitimate URLs which we can access from the environments such as Kaggle and UCI ML repository.
- Features that we include URL length, IP address, domain registration length, special symbols, etc.
- Data Pre-processing:
- Feature Extraction from URLs: When we begin with open URLs for retrieving informative features like domain name, path length, number of subdomains, etc.
- Encoding: We change categorical features into numerical approach using one-hot encoding and label encoding.
- Handling Missing Values: To maintain the lost data we use suggestion approaches and remove records with missing values.
- Feature Measuring: Making sure that the feature has relevant scales we normalize for distance-based methods like KNN.
- Feature Engineering:
- We design latest features that used to indicate phishing such as a feature finds usual phishing terms in the URL.
- Model Selection and Training:
- Logistic Regression: This can be assisting us in simplicity and understandability.
- Decision Trees & Random Forest: For capturing non-linear formats we utilize this framework.
- Gradient Boosting Machine (e.g. XGBoost): To enhance the accuracy we implement boosted trees.
- Neural Networks: When there is a huge volume of data we ensure that the deep learning is an excess model for our issue.
- Evaluation:
- Accuracy: We test how often the framework is appropriate.
- Precision: For better precision we evaluate proportion of positive findings that were actually perfect.
- Recall: To validate the proportion of real positives detected properly in our work.
- F1-Score: Balancing the precision and recall.
- ROC Curve & AUC: When the classes are imbalance we make use of this method.
- Deployment:
- Integrate our project into browser extensions, firewall outcomes and as a separate service to check URLs.
- To retrieve fast outcomes from we ensure low latency.
- Monitoring:
- Routinely we update the framework with recent data to handle its accuracy.
- We figure out false positives and false negatives to retrain out model.
Challenges:
- Dynamic Nature of Phishing Sites: Phishing websites continuously alter to avoid detection so we make some alternative for this.
- Feature Redundancy: When we extract the features not entire feature will provide information to us.
- Class Imbalance: There are several more legitimate URLs which we come across than phishing ones.
Extensions & Advanced Methods:
- Deep Learning on Raw URLs: To alter URLs into dense vectors and for training our model in neural network we implement embedding.
- Active Learning: When a user marks a site as phishing, we learn from the user review which model is missed from that instance.
- Integrate with Other Data: We collaborate with data from website content, SSL certificates and WHOIS database for richer features.
Combining with cybersecurity professionals can provide domain-specific understandings to us and makes the framework more powerful. We focus for a high recall while balancing accuracy in the real-time scenario, because the consequences of false negatives (not identifying a phishing website) are remarkable.
Detecting Phishing Websites using Machine Learning Project Thesis Ideas
The best thesis topics that we have built are described below get inspired by our professional’s work. As per your specifications we work out your research activities or we do take care and undertake your entire research work.
- Phishing Website Detection Using Machine Learning
Keywords
Phishing, Personal Information, Machine Learning, Malicious Links, Phishing Domain Characteristics
An implementation of features and ML techniques are suggested in our paper to detect the phishing attempts. Here we described the differentiation of phishing domains or illegitimate domains from the legitimate domains. We also explained about the significance of detecting phishing content. We investigated about the utilization of ML techniques and natural language processing approaches in our study.
- Phishing Website Detection with and Without Proper Feature Selection Techniques: Machine Learning Approach
Keywords
Cat-Boost, Phishing website detection, PCA, UFS, RFE, MI, PCC, Feature selection technique
An investigation on various ML methods before and after utilizing several Feature Selection (FS) approaches is carried out in our research. We demonstrated that, the Cat-Boost method achieved better results after utilizing UFS approach for FS. But when utilizing PCA approach for FS, methods like Cat-Boost, Gradient-Boost, and RF are unable to improve the accuracy. We conclude that, in future, utilization of integrated FS approach, DL technique and hyper parameters assist to attain successful outcomes in phishing website identification.
- Detection of Phishing Website Using Support Vector Machine and Light Gradient Boosting Machine Learning Algorithms
Keywords
ELM, SVM, Light GBM algorithm
An innovative technique is proposed by utilizing extreme learning machine (ELM) in our article to categorize the phishing websites. To identify the phishing websites by considering the size of the URL and the existence of capital letters and HTML attributes, we employed SVM, and light GBM techniques. Results illustrates that, ELM method provides greater efficiency in phishing websites categorization and also enhance the user’s security.
- Intelligent phishing website detection using machine learning
Keywords
Logistic regression, MultinomialNB, Phishing websites, Classification
A development of approach to distinguish and identify the phishing websites from the legitimate websites is the major aim of our study. Apart from Random Forest, Artificial Neural Network and SVM methods, we utilized Linear Regression and MultinomialNB as main techniques for categorization. Development of real time working framework is the main goal of our study. As a consequence, Linear Regression offers highest end results.
- A Novel Phishing Website Detection Model Based on LightGBM and Domain Name Features
Keywords
Domain name feature, symmetry, feature engineering
A ML related technique is suggested in our research for phishing website detection and to handle the smart system’s safety by utilizing LightGBM and features of domain name. We extracted the features from domain name of acquired website. We filtered the features to enhance the precision of framework and to ease the categorization process. We conclude that, our suggested framework with combination of two features provides efficient outcomes.
- Detecting Phishing Websites Using Machine Learning
Keywords
Phishing detection, Random Forest
An ultimate goal of our study is to discover whether the URL is secured or not by employing ML techniques. We utilized various methods like Logistic Regression, Support Vector Machine (SVM), and Random Forest. We examined and compared these methods in terms of various metrics to find out the optimal one that can identify and categorize the secured and phishing websites.
- Determining the Most Effective Machine Learning Techniques for Detecting Phishing Websites
Keywords
Web security, Decision tree, Gradient boost classifiers
Several ML approaches are analyzed and evaluated in our paper to discover the best method for the detection of phishing websites. We utilized various methods including RF, GB, DT, LR, KNN and SVM for phishing website identification. From the analysis, we demonstrate that, RF method achieved better performance than others and DT and GB provide somewhat identical results.
- Website Phishing Detection Using Machine Learning Classification Algorithms
Keywords
URL features, Data mining, Classification algorithms
A URL feature related website phishing identification methodology is recommended in our study to forecast the illegitimate websites. For identifying fake websites, we investigated several ML techniques such as extreme gradient boosting, random forest, AdaBoost, decision trees, K-nearest neighbors, support vector machines, logistic regression and naïve bayes. As a consequence, extreme gradient boosting method efficiently categorizes websites than others.
- Modeling Hybrid Feature-Based Phishing Websites Detection Using Machine Learning Techniques
Keywords
Cybersecurity, Hyperlink feature, Anti-phishing, XG Boost, Hybrid feature
A real time phishing websites identification framework is proposed in our article by considering URL and hyperlink related integrated features through the utilization of ML methods. Here, by utilizing an integrated feature related anti-phishing concept, we extracted features from URL and hyperlink data. We performed experimental analysis by employing various ML methods. In that, XGBoost achieved better end results than other conventional methods.
- Detecting Phishing Websites Using Machine Learning
Keywords
Legitimate websites, features, detection
A main objective of our research is to identify phishing or illegitimate websites through the employment of ML techniques. We applied various approaches such as Decision Tree (DT), Random Forest (RF), XGBoost, Multilayer Perceptron, K-Nearest Neighbors, Naive Bayes, AdaBoost, and Gradient Boosting on the dataset comprises of equal amount of safe and fake URLs. As a result, XGBoost outperformed the others.
Milestones
MILESTONE 1: Research Proposal
Finalize Journal (Indexing)
Before sit down to research proposal writing, we need to decide exact journals. For e.g. SCI, SCI-E, ISI, SCOPUS.
Research Subject Selection
As a doctoral student, subject selection is a big problem. Phdservices.org has the team of world class experts who experience in assisting all subjects. When you decide to work in networking, we assign our experts in your specific area for assistance.
Research Topic Selection
We helping you with right and perfect topic selection, which sound interesting to the other fellows of your committee. For e.g. if your interest in networking, the research topic is VANET / MANET / any other
Literature Survey Writing
To ensure the novelty of research, we find research gaps in 50+ latest benchmark papers (IEEE, Springer, Elsevier, MDPI, Hindawi, etc.)
Case Study Writing
After literature survey, we get the main issue/problem that your research topic will aim to resolve and elegant writing support to identify relevance of the issue.
Problem Statement
Based on the research gaps finding and importance of your research, we conclude the appropriate and specific problem statement.
Writing Research Proposal
Writing a good research proposal has need of lot of time. We only span a few to cover all major aspects (reference papers collection, deficiency finding, drawing system architecture, highlights novelty)
MILESTONE 2: System Development
Fix Implementation Plan
We prepare a clear project implementation plan that narrates your proposal in step-by step and it contains Software and OS specification. We recommend you very suitable tools/software that fit for your concept.
Tools/Plan Approval
We get the approval for implementation tool, software, programing language and finally implementation plan to start development process.
Pseudocode Description
Our source code is original since we write the code after pseudocodes, algorithm writing and mathematical equation derivations.
Develop Proposal Idea
We implement our novel idea in step-by-step process that given in implementation plan. We can help scholars in implementation.
Comparison/Experiments
We perform the comparison between proposed and existing schemes in both quantitative and qualitative manner since it is most crucial part of any journal paper.
Graphs, Results, Analysis Table
We evaluate and analyze the project results by plotting graphs, numerical results computation, and broader discussion of quantitative results in table.
Project Deliverables
For every project order, we deliver the following: reference papers, source codes screenshots, project video, installation and running procedures.
MILESTONE 3: Paper Writing
Choosing Right Format
We intend to write a paper in customized layout. If you are interesting in any specific journal, we ready to support you. Otherwise we prepare in IEEE transaction level.
Collecting Reliable Resources
Before paper writing, we collect reliable resources such as 50+ journal papers, magazines, news, encyclopedia (books), benchmark datasets, and online resources.
Writing Rough Draft
We create an outline of a paper at first and then writing under each heading and sub-headings. It consists of novel idea and resources
Proofreading & Formatting
We must proofread and formatting a paper to fix typesetting errors, and avoiding misspelled words, misplaced punctuation marks, and so on
Native English Writing
We check the communication of a paper by rewriting with native English writers who accomplish their English literature in University of Oxford.
Scrutinizing Paper Quality
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Plagiarism Checking
We at phdservices.org is 100% guarantee for original journal paper writing. We never use previously published works.
MILESTONE 4: Paper Publication
Finding Apt Journal
We play crucial role in this step since this is very important for scholar’s future. Our experts will help you in choosing high Impact Factor (SJR) journals for publishing.
Lay Paper to Submit
We organize your paper for journal submission, which covers the preparation of Authors Biography, Cover Letter, Highlights of Novelty, and Suggested Reviewers.
Paper Submission
We upload paper with submit all prerequisites that are required in journal. We completely remove frustration in paper publishing.
Paper Status Tracking
We track your paper status and answering the questions raise before review process and also we giving you frequent updates for your paper received from journal.
Revising Paper Precisely
When we receive decision for revising paper, we get ready to prepare the point-point response to address all reviewers query and resubmit it to catch final acceptance.
Get Accept & e-Proofing
We receive final mail for acceptance confirmation letter and editors send e-proofing and licensing to ensure the originality.
Publishing Paper
Paper published in online and we inform you with paper title, authors information, journal name volume, issue number, page number, and DOI link
MILESTONE 5: Thesis Writing
Identifying University Format
We pay special attention for your thesis writing and our 100+ thesis writers are proficient and clear in writing thesis for all university formats.
Gathering Adequate Resources
We collect primary and adequate resources for writing well-structured thesis using published research articles, 150+ reputed reference papers, writing plan, and so on.
Writing Thesis (Preliminary)
We write thesis in chapter-by-chapter without any empirical mistakes and we completely provide plagiarism-free thesis.
Skimming & Reading
Skimming involve reading the thesis and looking abstract, conclusions, sections, & sub-sections, paragraphs, sentences & words and writing thesis chorological order of papers.
Fixing Crosscutting Issues
This step is tricky when write thesis by amateurs. Proofreading and formatting is made by our world class thesis writers who avoid verbose, and brainstorming for significant writing.
Organize Thesis Chapters
We organize thesis chapters by completing the following: elaborate chapter, structuring chapters, flow of writing, citations correction, etc.
Writing Thesis (Final Version)
We attention to details of importance of thesis contribution, well-illustrated literature review, sharp and broad results and discussion and relevant applications study.
How PhDservices.org deal with significant issues ?
1. Novel Ideas
Novelty is essential for a PhD degree. Our experts are bringing quality of being novel ideas in the particular research area. It can be only determined by after thorough literature search (state-of-the-art works published in IEEE, Springer, Elsevier, ACM, ScienceDirect, Inderscience, and so on). SCI and SCOPUS journals reviewers and editors will always demand “Novelty” for each publishing work. Our experts have in-depth knowledge in all major and sub-research fields to introduce New Methods and Ideas. MAKING NOVEL IDEAS IS THE ONLY WAY OF WINNING PHD.
2. Plagiarism-Free
To improve the quality and originality of works, we are strictly avoiding plagiarism since plagiarism is not allowed and acceptable for any type journals (SCI, SCI-E, or Scopus) in editorial and reviewer point of view. We have software named as “Anti-Plagiarism Software” that examines the similarity score for documents with good accuracy. We consist of various plagiarism tools like Viper, Turnitin, Students and scholars can get your work in Zero Tolerance to Plagiarism. DONT WORRY ABOUT PHD, WE WILL TAKE CARE OF EVERYTHING.
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- Technical Info: We never share your technical details to any other scholar since we know the importance of time and resources that are giving us by scholars.
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Most of the PhD consultancy services will end their services in Paper Writing, but our PhDservices.org is different from others by giving guarantee for both paper writing and publication in reputed journals. With our 18+ year of experience in delivering PhD services, we meet all requirements of journals (reviewers, editors, and editor-in-chief) for rapid publications. From the beginning of paper writing, we lay our smart works. PUBLICATION IS A ROOT FOR PHD DEGREE. WE LIKE A FRUIT FOR GIVING SWEET FEELING FOR ALL SCHOLARS.
5. No Duplication
After completion of your work, it does not available in our library i.e. we erased after completion of your PhD work so we avoid of giving duplicate contents for scholars. This step makes our experts to bringing new ideas, applications, methodologies and algorithms. Our work is more standard, quality and universal. Everything we make it as a new for all scholars. INNOVATION IS THE ABILITY TO SEE THE ORIGINALITY. EXPLORATION IS OUR ENGINE THAT DRIVES INNOVATION SO LET’S ALL GO EXPLORING.
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