2002 to 2000ALTRUM TECHNOLOGIES, LLC Chicago, IL 1998 to 2001 Chairman and Chief Executive OfficerMONSANTO COMPANY St. Louis, MO 1993 to 1995 Corporate Vice President, Information Technology & CIOMONSANTO COMPANY St. Louis, MO 1967 to 1995MONSANTO COMPANY St. Louis, MO 1992 to 1992 President & COOMONSANTO COMPANY So Paulo, SP 1988 to 1991 PresidentMONSANTO COMPANY St. Louis, MO 1987 to 1987 General ManagerMONSANTO COMPANY St. Louis, MO 1986 to 1986 Director - CommercialMONSANTO COMPANY
1968 to 1985 Director, and Management rolesFORD MOTOR COMPANY Lansing, MI 1967 to 1967 Sales Trainee
Education:
Hillsdale College Hillsdale, MI 1993 to 1995 Bachelor of Arts in Business AdministrationSt. Louis 1982 to 1987Stanford University Stanford, CA 1984 Executive Program
Name / Title
Company / Classification
Phones & Addresses
James Nisbet
Nisbet Family Partnership, A California Limited Partnership, The
320 Santa Margarita Ave, Menlo Park, CA 94025
James R. Nisbet Incorporator
SUNSET ADDITION PROPERTY OWNERS ASSOCIATION, INC
James Nisbet President
NISBET MANAGEMENT, INC
PO Box 153, Moss Beach, CA 94038
James Nisbet
Vencraft, LLC Investment Holding Company
1 Smt Way, Redwood City, CA 94062
Us Patents
Inferring Content Sensitivity From Partial Content Matching
James Donald Nisbet - Menlo Park CA, US James Christopher Wiese - Dublin CA, US David Alexander Reizes - Menlo Park CA, US Stephen Crosby Hoyt - Palo Alto CA, US
Monitored content is analyzed to determine full and partial matches to previously classified content. Monitored content matching previously classified public content is classified as public, even if the monitored content is also found to match previously classified private content. In other words, public classification “overrides” potentially private classification. Monitored content matching only previously classified private content is classified as private. All remaining otherwise unclassified monitored content is classified as unknown. Monitored content is analyzed with respect to a session. If any content in a session is private, then the session is classified as private. If all content in a session is public, then the session is classified as public. Otherwise, the session is classified as unknown. In a related aspect, a set of policies are searched for a first match in part according to the classification, and a designated action taken if the first match is found.
Partial Document Content Matching Using Sectional Analysis
James Donald Nisbet - Menlo Park CA, US James Christopher Wiese - Dublin CA, US David Alexander Reizes - Menlo Park CA, US Stephen Crosby Hoyt - Palo Alto CA, US
Assignee:
EMC Corporation - Hopkinton MA
International Classification:
G06F 11/00
US Classification:
726 22, 713154
Abstract:
Monitored content is classified to determine partial matches with fragments of documents. A set of redundant keys, or sliding sectional fingerprints, are computed for every possible alignment of the documents with respect to the monitored content. The keys are stored in repositories according to the classification of the corresponding documents. Sectional fingerprints are computed for the monitored content, and the repositories are searched. If a match is found in a repository corresponding to public content, then the monitored data section is classified as public. If a match is found only in a repository corresponding to private content, then the data section is classified as private. Otherwise, the data section is classified as unknown. In a related aspect, a set of policies are searched for a first match in part according to the classifications of the monitored data sections, and a designated action taken if the first match is found.
Identifying Whether Electronic Data Under Test Includes Particular Information From A Database
Electronic circuitry includes an input/output (I/O) interface, memory which stores a set of database fingerprints generated from records of a database, and an analyzing circuit coupled to the I/O interface and the memory. The analyzing circuit is constructed and arranged to derive a set of sample tokens from electronic data under test (e. g. , an email, an electronic document, etc. ), and form a set of sample fingerprints from the set of sample tokens. Each sample fingerprint is based on a sample token of the set of sample tokens. The analyzing circuit is further constructed and arranged to output a result signal based on a comparison between the set of sample fingerprints and the set of database fingerprints. The result signal provides an indication of whether the electronic data under test includes particular information from the database.
Inferring Document And Content Sensitivity From Public Account Accessibility
James Donald Nisbet - Menlo Park CA, US James Christopher Wiese - Dublin CA, US David Alexander Reizes - Menlo Park CA, US Stephen Crosby Hoyt - Palo Alto CA, US
In one embodiment, documents accessible via a designated public account are classified as public. In another embodiment, documents accessible according to a designated public access control list are classified as public. In some embodiments, all documents not classified as public are classified as private. Content in the public documents is linguistically analyzed, resulting in a set of keys for use in subsequent full and partial content matching. The keys and associated file names are stored in a public-content identification repository. Similarly, content in the private documents is linguistically analyzed, and the results are stored in a private-content identification repository. Subsequently, full and partial content matching is performed on monitored content according to information in the public and private repositories. In a related aspect, monitored content found to correspond to private content is selectively flagged during electronic transmission or optionally prevented from distribution according to a set of defined monitoring policies.