AI-Powered login anomaly detection (catching malicious attempts)

Hello. I hope you are doing well. I am a PYTHON expert and have years of experiences in ML & DL, I can provide you the perfect result on time. Please contact me so that we can discuss about the details of the project. Thank you for your time

I have done a python function that detects the min likelyhood and max likelihood in cybersecurity in my professional work , I will be able to help you

Hello, Could you share with me the malicious attempt sample to detect model ? Looking forward to your response.

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As an AI developer with a focus on Python, I am confident that I possess the necessary skills to tackle your project. My expertise lies in developing sophisticated machine learning models, which is crucial to identifying any potential security threats via login anomalies. Throughout my career in both website and mobile app development, I've always prioritized the integrity of a system's security infrastructure. That's why I turned to AI in order to find innovative solutions like the one you're looking for. My deep understanding of machine-learning techniques combined with my proficiency in Python will help me handle your varied data sources intelligently and sensitively. Additionally, I pride myself on my adaptability, always willing to learn and grow. My extensive portfolio showcases a diverse array of clients and projects, giving me insights into different industries’ unique security challenges. Let me bring both my data analytics skills and industry experience to the table for your business. Let's collaborate to build a secure future together.

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I can assist in developing models to identify malicious login attempts and anomaly detection using Autoencoders AI Models or Transfomers-based models. With AI models we will train deep autoencoder models to identify these behaviours. Since perpetrators need to deviate from the ”regular”. Such deviating behavior will be recorded by a very limited number of transactions and their respective attribute values. My proposal is as follows: 1. pre-processing login data in order to learn a model of its characteristics, 2. the application of autoencoder neural networks to detect anomalies 3. Interpret results, use Questions: 1: Do you want results to be forwarded to SOC in real-time? 2: Are thresholds based on policy 3: are logs being streamed or dumped in flat files for analysis Looking forward to your response.

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