Smart Anomaly Detection and Threat Analysis System

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@hotanloc

I saw your project description carefully. I can complete this task with high quality on time. I have expertise in ML/DL, and neural network, SVM, decision tree, and other all models.I I have full experiences in TensorFlow, PyTorch, Scikit-learn and other libraries. I I will provide you with the finest work that perfectly aligns with your time and budget constraints. Please send me your message to discuss your project detail more...I am waiting your reply now. Thanks.

@rakam26

Hello Just read your post and it seems you are looking for a skilled Python machine learning developer to build an academic-grade supervised learning system that detects SQL Injection, XSS, and DDoS, including full data preparation, feature engineering, model training, evaluation, and a reproducible CLI + Jupyter workflow. With my years of extensive experience and exceptional expertise in Python (pandas, scikit-learn, TensorFlow/PyTorch), multi-class classification for cybersecurity datasets, feature engineering and class-imbalance handling, and delivering well-documented, fully reproducible ML pipelines with clear metrics and step-by-step setup instructions, I am 100% confident that I can bring your vision to life in the shortest possible time. Let's connect and see how great value I can add to your business. Best Regards, Raka

@PremchandGat

Hi, I am an AI/ML and cybersecurity researcher in a Tier 1 institute and this is exactly the kind of academic, reproducible ML project I enjoy building. I have strong experience in cybersecurity-focused machine learning pipelines and can deliver a clean, examiner-ready solution for multi-class detection of SQLi, XSS, and DDoS attacks. I have worked on few research papers which are already published in some good conferences where we are trying to model Hacker's decisions through machine learning models like IBL and LLMs. Thus my experience makes me best fit for this project. My approach: • Systematic data cleaning and documented feature engineering (fully script-based for reproducibility) • Careful model selection (e.g., Random Forest or SVM baseline + optional lightweight DL comparison) with justification tailored to multi-class attack detection • Robust evaluation using accuracy, precision, recall, F1-score, and confusion matrices, including clear handling of class imbalance You will receive: Full source code + trained model Raw-to-processed dataset scripts Concise PDF explaining architecture and workflow My priority is clarity, transparency, and reproducibility—so any reviewer can install dependencies, run the pipeline, and immediately understand each stage. Thanks and regards

@mariamz24

Hello, We would like to grab this opportunity and will work till you get 100% satisfied with our work. We are an expert team which have many years of experience on Python, Linux, Statistics, Machine Learning (ML), Data Science, Documentation, Keras, Data Analysis, Deep Learning, Pandas Lets connect in chat so that We discuss further. Regards

@Shwet33

i got my Hands on the skills required i will make sure u will not get disappointed at all and will deliver the best results as expected looking forward to work for you

@justhivedata

Hi, I am an ML engineer specializing in cybersecurity analytics. I will build your academic-grade anomaly detection system using supervised learning to classify SQL Injection, XSS, and DDoS attacks from your custom dataset. I will implement multiple models (Random Forest, SVM, and a simple Neural Network) with full preprocessing pipeline, feature engineering, cross-validation, confusion matrices, ROC curves, and a detailed classification report. Code will be clean, well-documented Jupyter notebooks ready for academic submission. I will also include a brief write-up explaining the methodology and results.

@i91lyas

I will build your multi-class threat analysis pipeline in Python (using pandas and scikit-learn/Keras) to detect SQLi, XSS, and DDoS attacks, and I will gladly deliver the optional 10-page academic report and viva slide deck. My technical background sits directly at the intersection of AI anomaly detection and cybersecurity. I have hands-on experience building complex predictive models (including LSTM-based anomaly detection systems) and writing Python automation systems for cybersecurity environments. I know exactly how to handle multi-class data imbalances and extract the right evaluation metrics (precision, recall, confusion matrices) to impress examiners. I will deliver the complete academic-grade package: The fully commented Python source code and processed dataset. A packaged inference pipeline runnable via CLI and a clean Jupyter Notebook. The step-by-step PDF execution guide (with screenshots). The ~10-page final report and viva slide deck detailing the feature engineering and model logic. How large is the custom dataset you will be providing, and do you have a strict preference for a classical algorithm (like Random Forest) or a lightweight Deep Learning variant?

@amans0665

Can do it using RandomForest or XGBoost. Will prepare a complete jupyter notebook with steps explained in markdown. And a slide deck.