Search Results for "forensic audio analysis"

An extensible network forensic analysis framework. Enables rapid development of plugins to support the dissection of network packet captures. This is a major framework update to Dshell. Plugins written for the previous version are not compatible with this version, and vice versa. By extension, dpkt and pypcap have been replaced with Python3-friendly pypacker and pcapy (respectively).

...The framework includes features such as antivirus evasion, privilege escalation, and system persistence, enabling it to maintain access on compromised systems. It also incorporates techniques to avoid forensic analysis, such as self-deletion and cleaning traces after execution. The generated executables are optimized to be small and efficient, improving their ability to bypass security controls.

MARF is a general cross-platform framework with a collection of algorithms for audio (voice, speech, and sound) and natural language text analysis and recognition along with sample applications (identification, NLP, etc.) of its use, implemented in Java.

CAMEL (Content-based Audio and Music Extraction Library) is an easy-to-use C++ framework developed for content-based audio and music analysis. The framework provides a set of tools for easy Segmentation, Feature Extraction, Domain Extraction, etc.

MidiWriter is a framework for creating and composing music based on algorithms. The project includes already several examples using these technics. The output of MidiWriter is in the midi-format.

OMEN (On-demand Metadata Extraction Network) is a tomcat based system that allows external users (music information researchers) to request from participating libraries the extraction of features from music archives without violating copyright.

The DataTime Process Framework is intended to support the processing of time-based data in a modular, concurrent, distributed and extensible manner. C++, using YARP, ACE, Qt and MUSCLE on Linux, OSX, Windows and Solaris.

Java framework based on jAudio feature extraction algorithms, but lightweight and easy for use. Support mp3, wav, aiff, aifc, au and snd files. Can extract 28 features.