March 27, 2023
Determine 1. Schematic of a streaming service platform: (a) illustrates machine varieties that can be utilized for streaming, (b) designates the set of authentication and authorization programs similar to license and manifest servers for offering encrypted contents in addition to decryption keys and manifests, and (c) exhibits the streaming service supplier, as a surrogate entity for digital content material suppliers, that interacts with the opposite two parts.

Knowledge Labeling

Desk 1. The record of streaming associated options with the suffixes pct and cnt respectively referring to share and rely
Determine 2. Variety of anomalous samples as a operate of (a) fraud classes and (b) variety of tagged classes.
Determine 3. Correlation matrix of the options introduced in Desk 1 for (a) clear and (b) anomalous knowledge samples.
Determine 4. Artificial Minority Over-sampling Method
Determine 5. Mannequin-based anomaly detection approaches: (a) semi-supervised and (b) supervised.
Desk 2. The values of the analysis metrics for a set of semi-supervised anomaly detection fashions.
Determine 6. For the deep auto-encoder mannequin: (a) distribution of the Imply Squared Error (MSE) values for anomalous and benign samples on the inference stage — (b) confusion matrix throughout benign and anomalous samples- (c) Imply Squared Error (MSE) values averaged throughout the anomalous and benign samples for every of the 23 options.
Desk 3. The values of the analysis metrics for a set of supervised binary anomaly detection classifiers.
Desk 4. The values of the analysis metrics for a set of supervised multi-class multi-label anomaly detection approaches. The values in parenthesis consult with the efficiency of the fashions skilled on the unique (not upsampled) dataset.
Determine 7. The normalized characteristic significance values (NFIV) for the multi-class multi-label anomaly detection activity utilizing the XGBoost method in Desk 4 throughout the three anomaly courses, i.e., (a) content material fraud, (b) service fraud, and (c) account fraud.