Digital Commons Network^™

Insider’S Misuse Detection: From Hidden Markov Model To Deep Learning, Ahmed Saaudi

Theses and Dissertations

Malicious insiders increasingly affect organizations by leaking classified data to unautho- rized entities. Detecting insiders’ misuses in computer systems is a challenging problem. In this dissertation, we propose two approaches to detect such threats: a probabilistic graph- ical model-based approach and a deep learning-based approach. We investigate the logs of computer-based activities to discover patterns of misuse. We model user’s behaviors as sequences of computer-based events.

For our probabilistic graphical model-based approach, we propose an unsupervised model for insider’s misuse detection. That is, we develop Stochastic Gradient Descent method to learn Hidden Markov Models (SGD-HMM) with the goal of analyzing …

Hydro-Geological Flow Analysis Using Hidden Markov Models, Chandrahas Raj Venkat Gurram

Theses and Dissertations

Hidden Markov Models a class of statistical models used in various disciplines for understanding speech, finding different types of genes responsible for cancer and much more. In this thesis, Hidden Markov Models are used to obtain hidden states that can correlate the flow changes in the Wakulla Spring Cave. Sensors installed in the tunnels of Wakulla Spring Cave have recorded huge correlated changes in the water flows at numerous tunnels. Assuming the correlated flow changes are a consequence of system being in a set of discrete states, a Hidden Markov Model is calculated. This model comprising all the sensors installed …