Recording security management
Disclosed are various embodiments for preventing unauthorized access to materials and topics for meeting invitations and meeting recording. A meeting recording and other meeting data is received in association with a meeting identifier. The meeting recording and the meeting data is provided as input to a machine learning engine to generate labelled recording data. A user-specific recording package is generated to include data limited to the at least one meeting section corresponding to a set of security labels approved for a user account.
1 . A system, comprising:
at least one computing device comprising at least one processor and at least one memory; and
machine-readable instructions stored in the memory that, when executed by the at least one processor, cause the at least one computing device to at least:
identify meeting recording associated with a meeting identifier;
retrieve meeting data based on the meeting identifier;
provide the meeting recording and the meeting data as input to a machine learning engine of a meeting security service to generate labelled recording data comprising a plurality of meeting sections, wherein at least one security label is applied to at least one meeting section, and wherein the labelled recording data specifies a beginning timestamp and an ending timestamp for each meeting section;
generate, based at least in part on the labelled recording data from the machine learning engine of the meeting security service, a user-specific recording package for a user account, the user-specific recording package comprising a subset of the plurality of meeting sections, wherein generating the user-specific recording package comprises extracting, from the meeting recording, only those meeting sections whose security labels are included in a set of security labels approved for the user account and excluding at least one meeting section having a security label not included in the set of security labels approved for the user account; and
transmit the user-specific recording package to a client device associated with the user account.
2 . The system of claim 1 , wherein the meeting recording is associated with at least one of: an in-person meeting, and a network conferencing meeting.
3 . The system of claim 1 , wherein the meeting data comprises at least one of: a meeting topic, a meeting location, a user-selected security label, an attachment, and a network link.
4 . The system of claim 1 , wherein the instructions further cause the at least one computing device to at least:
generate, based at least in part on the labelled recording data from the machine learning engine of the meeting security service, a recording security assessment that shows associations between the at least one meeting section with the at least one security label.
5 . The system of claim 4 , wherein the instructions further cause the at least one computing device to at least:
receive security assessment feedback that accepts or modifies the labelled recording data.
6 . The system of claim 5 , wherein the instructions further cause the at least one computing device to at least:
update the machine learning engine of the meeting security service based at least in part on the security assessment feedback.
7 . The system of claim 1 , wherein the meeting data comprises expected data generated prior to the meeting, and updated data updated to reflect information confirmed during a meeting, the updated data comprising at least one of: an updated participant data, updated topic data, and updated timing data.
8 . A method, comprising:
receiving, by a meeting security service, a meeting recording associated with a meeting identifier and meeting data associated with the meeting identifier;
providing, by the meeting security service, the meeting recording and the meeting data as input to a machine learning engine to generate labelled recording data comprising a plurality of meeting sections, wherein at least one security label is applied to at least one meeting section, and wherein the labelled recording data specifies a beginning timestamp and an ending timestamp for each meeting section; and
generating, by the meeting security service, based at least in part on the labelled recording data from the machine learning engine of the meeting security service, a user-specific recording package for a user account, the user-specific recording package comprising a subset of the plurality of meeting sections, wherein generating the user-specific recording package comprises extracting, from the meeting recording, only those meeting sections whose security labels are included in a set of security labels approved for the user account and excluding at least one meeting section having a security label not included in the set of security labels approved for the user account,
wherein the meeting security service provides the user account with access to the user-specific recording package.
9 . The method of claim 8 , wherein the meeting recording is associated with at least one of: an in-person meeting, and a network conferencing meeting.
10 . The method of claim 8 , wherein the meeting data comprises at least one of: a meeting topic, a meeting location, a user-selected security label, an attachment, and a network link.
11 . The method of claim 8 , further comprising:
generating, based at least in part on the labelled recording data from the machine learning engine of the meeting security service, a recording security assessment that shows associations between the at least one meeting section with the at least one security label.
12 . The method of claim 11 , further comprising:
receiving, by the meeting security service, security assessment feedback that accepts or modifies the labelled recording data.
13 . The method of claim 12 , further comprising:
updating the machine learning engine of the meeting security service based at least in part on the security assessment feedback.
14 . The method of claim 8 , wherein the meeting data comprises expected data generated prior to the meeting, and updated data updated to reflect information confirmed during a meeting, the updated data comprising at least one of: an updated participant data, updated topic data, and updated timing data.
15 . A non-transitory, computer-readable medium, comprising machine-readable instructions that, when executed by at least one processor of at least one computing device, cause the at least one computing device to at least:
receive a meeting recording associated with a meeting identifier and meeting data associated with the meeting identifier;
provide the meeting recording and the meeting data as input to a machine learning engine of a meeting security service to generate labelled recording data comprising a plurality of meeting sections, wherein at least one security label is applied to at least one meeting section; and
generate, based at least in part on the labelled recording data from the machine learning engine of the meeting security service, a user-specific recording package for a user account, the user-specific recording package comprising a subset of the plurality of meeting sections, wherein generating the user-specific recording package comprises extracting, from the meeting recording, only those meeting sections whose security labels are included in a set of security labels approved for the user account and excluding at least one meeting section having a security label not included in the set of security labels approved for the user account, wherein the meeting security service provides the user account with access to the user-specific recording package.
16 . The non-transitory, computer-readable medium of claim 15 , wherein the meeting recording is associated with at least one of: an in-person meeting, and a network conferencing meeting.
17 . The non-transitory, computer-readable medium of claim 15 , wherein the instructions further cause the at least one computing device to at least:
generate, based at least in part on the labelled recording data from the machine learning engine of the meeting security service, a recording security assessment that shows associations between the at least one meeting section with the at least one security label.
18 . The non-transitory, computer-readable medium of claim 17 , wherein the instructions further cause the at least one computing device to at least:
receive security assessment feedback that accepts or modifies the labelled recording data.
19 . The non-transitory, computer-readable medium of claim 18 , wherein the instructions further cause the at least one computing device to at least:
update the machine learning engine of the meeting security service based at least in part on the security assessment feedback.
20 . The non-transitory, computer-readable medium of claim 15 , wherein the meeting data comprises expected data generated prior to the meeting, and updated data updated to reflect information confirmed during a meeting, the updated data comprising at least one of: an updated participant data, updated topic data, and updated timing data.