Aniyah Hall

At Bowie State University, I spearheaded IoT security research, enhancing data integrity in healthcare through advanced cryptographic techniques. Expert in Python and team management, I published significant findings, demonstrating a knack for applying critical security policies and leading projects to safeguard sensitive information effectively.

• CompTIA Security+, In Progress
• Python for Cybersecurity, Hands-on experience in scripting security solutions
• Ethical Hacking & Penetration Testing, Training in network security assessment

Available Upon Request

• Machine Learning for Biometric Authentication, Python, Scikit-learn, Random Forests, Convolutional Neural Networks (CNNs), Autoencoders, Support Vector Machines (SVM), AdaBoost, Recurrent Neural Networks (RNNs), Jupyter Notebook, Kaggle datasets, The team project focused on enhancing biometric and behavioral authentication systems using machine learning to improve security and accuracy for sensitive applications in healthcare and finance.
• Network Traffic Anomaly Detection, Python, Scikit-learn, TensorFlow, Pandas, NumPy, Matplotlib, ROC Curve Analysis, The group project focused on developing a machine-learning model to detect anomalies in network traffic by classifying traffic as normal or anomalous.
• Protection of Sensitive Data with Zero Trust Model and Machine Learning, Python, Scikit-learn, Splunk, Wireshark, Snort, Zero Trust Model, User Behavior Analytics (UBA), Natural Language Processing (NLP), The team project focused on protecting sensitive data using a Zero Trust model combined with machine learning algorithms to enhance cybersecurity defenses.

Intrusion detection, Firewalls, Network monitoring, Wireshark, Snort, Splunk, Python, Java, Bash scripting for automation, Windows (10 & 11), Linux (Ubuntu, Kali), Server Administration, Threat detection, Encryption (Fernet, AES), Risk assessment, Security policies, HIPAA, Zero Trust security models, Project coordination, Conflict resolution, Team management