Abstract: A system for automatic collection and analysis of digital forensic evidence by a cloud service provider is disclosed. The system utilizes machine learning models to identify and store digital forensic evidence relating to cybercrimes committed using a cloud service. Particularly, if an image or video file uploaded to the cloud service provider is determined to relate to illicit, illegal, or malicious activity, relevant digital forensic evidence is extracted and stored for later provision to law enforcement. The digital forensic evidence that is collected may be used to assist law enforcement in their investigations of criminal activity, as well as aid in the successful prosecution of criminals in court proceedings.

Abstract: Many mobile devices are used for documenting different scenarios that are encountered by the users as they go about their daily lives. In many situations, a mobile device may be used to document the scenario. This data may be of significant forensic interest to an investigator. In many situations, the owner of the phone may be willing to provide the investigator access to this data (through a documented consent agreement). Such consent is usually contingent upon the fact that not all the data available on the phone may be extracted for analysis, either due to privacy concerns or due to personal reasons. Courts have also opined in several cases that investigators must limit data extracted, so as to focus on only “relevant information” for the investigation at hand. Thus, only selective (or filtered) data should be extracted as per the consent available from the witness/victim (user). Described herein is the design and implementation of such a targeted data extraction system (TDES) for mobile devices.

Abstract: A system for automatic collection and analysis of digital forensic evidence by a cloud service provider is disclosed. The system utilizes machine learning models to identify and store digital forensic evidence relating to cybercrimes committed using a cloud service. Particularly, if an image or video file uploaded to the cloud service provider is determined to relate to illicit, illegal, or malicious activity, relevant digital forensic evidence is extracted and stored for later provision to law enforcement. The digital forensic evidence that is collected may be used to assist law enforcement in their investigations of criminal activity, as well as aid in the successful prosecution of criminals in court proceedings.

Abstract: Many mobile devices are used for documenting different scenarios that are encountered by the users as they go about their daily lives. In many situations, a mobile device may be used to document the scenario. This data may be of significant forensic interest to an investigator. In many situations, the owner of the phone may be willing to provide the investigator access to this data (through a documented consent agreement). Such consent is usually contingent upon the fact that not all the data available on the phone may be extracted for analysis, either due to privacy concerns or due to personal reasons. Courts have also opined in several cases that investigators must limit data extracted, so as to focus on only “relevant information” for the investigation at hand. Thus, only selective (or filtered) data should be extracted as per the consent available from the witness/victim (user). Described herein is the design and implementation of such a targeted data extraction system (TDES) for mobile devices.