Patents by Inventor Kimmo Hatonen

Kimmo Hatonen has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 8331904
    Abstract: Apparatus including functionality configured to monitor said apparatus for security attacks; and a reporter configured to send data to a security node, wherein the data sent to said security node is dependent on a security level of said apparatus.
    Type: Grant
    Filed: October 20, 2006
    Date of Patent: December 11, 2012
    Assignee: Nokia Corporation
    Inventors: Markus Miettinen, Kimmo Hatonen
  • Patent number: 7778979
    Abstract: The present invention relates to a method and apparatus for compressing a log record information provided e.g. to a monitoring system. Frequent patterns in the log information are detected and, then, redundant frequent patterns whose value or record combination is a subset of a value or record combination of another one of said detected frequent patterns are removed. Accordingly, a general method is provided which can be applied to all event logs arising from communication networks or other monitoring systems. The detection of frequent patterns is only based on value or record combinations and is thus independent of the specific application. On the other hand, the size of the stored log files can be decreased remarkably while remaining readable for human beings.
    Type: Grant
    Filed: March 26, 2002
    Date of Patent: August 17, 2010
    Assignee: Nokia Siemens Networks Oy
    Inventors: Kimmo Hätönen, Markus Miettinen
  • Patent number: 7613668
    Abstract: A method for teaching an anomaly detecting mechanism in a system comprising observable elements (302), at least one of which has a periodic time-dependent behaviour, the anomaly detecting mechanism comprising a computerized learning mechanism (314). The method comprises assembling indicators (304) indicating the behaviour of the elements (302) and arranging the assembled indicators such that each observable element's indicators are assigned to the same input data component. The learning mechanism (314) is taught so that the input data of the learning mechanism comprises the input data components which are based on the assembled indicators (304). Points which approximate the input data are placed in the input space. A presentation of time (420-424) is incorporated into at least one input data component wherein the presentation of time is periodic, continuous and un-ambiguous within the period of the at least one element with periodic time-dependent behaviour.
    Type: Grant
    Filed: March 7, 2003
    Date of Patent: November 3, 2009
    Assignee: Nokia Siemens Networks Oy
    Inventors: Albert Höglund, Kimmo Hätönen, Antti Sorvari
  • Patent number: 7519860
    Abstract: A method and system for monitoring the behavior of at least one observable object, e.g. a network element, of a network, wherein at least one parameter of the observable object is repeatedly detected. An actually detected parameter is input to a learning process and to an analyzing process, wherein the learning process forms a reference, based on at least two detected parameter values, for describing the behavior of the observable object. The analyzing process compares the input parameter and the reference for detecting an anomal behavior. The parameter preferably is a vector which includes several values describing properties or functioning of the observable object, and is formed based on events and/or reports from the object.
    Type: Grant
    Filed: June 6, 2001
    Date of Patent: April 14, 2009
    Assignee: Nokia Corporation
    Inventors: Kimmo Hätönen, Albert Höglund, Markus Miettinen, Jyrki Berg, Kari Kulmala, Sampo Torikka
  • Patent number: 7461037
    Abstract: A data processing system processes data arrays that collectively describe cyclic behavior of at least one variable in several entities in a physical process. Each cycle comprises several time slots. An input routine (2-4) receives multiple data arrays, each data array containing multiple data items, each of which describes a variable of an entity in one time slot. A magnitude-determination routine (2-6) determines a specific magnitude parameter, such as average, volume or peak, for each of the several entities. A scaling routine (2-8) scales the data arrays between entities such that the specific magnitude parameters are suppressed and only their shape is maintained. A training routine (2-10) trains a clustering system with a first plurality of the scaled data arrays, to determine a set of cluster centers. After training, a clustering routine (2-12) applies a second plurality of the scaled data arrays to the trained clustering system.
    Type: Grant
    Filed: December 31, 2003
    Date of Patent: December 2, 2008
    Assignee: Nokia Siemens Networks Oy
    Inventors: Kimmo Hätönen, Pekka Kumpulainen, Pekko Vehviläinen
  • Publication number: 20080096526
    Abstract: Apparatus including functionality configured to monitor said apparatus for security attacks; and a reporter configured to send data to a security node, wherein the data sent to said security node is dependent on a security level of said apparatus.
    Type: Application
    Filed: October 20, 2006
    Publication date: April 24, 2008
    Inventors: Markus Miettinen, Kimmo Hatonen
  • Publication number: 20080005265
    Abstract: A method and system for parsing textual report data found in free-text fields is disclosed. The textual report data may be included in log files that document a systems operation. A message template is created from reports or log data and used to automate the parsing of these variable data fields.
    Type: Application
    Filed: June 30, 2006
    Publication date: January 3, 2008
    Applicant: Nokia Corporation
    Inventors: Markus Miettinen, Kimmo Hatonen
  • Publication number: 20050240582
    Abstract: In a computerized system, a frequent pattern is provided from patterns of data. A first checksum is then assigned for the frequent pattern. Upon an occurrence of the frequent pattern in data, a second checksum is computed based on information regarding the first checksum and information regarding the occurrence of the frequent pattern in the data.
    Type: Application
    Filed: July 19, 2004
    Publication date: October 27, 2005
    Inventors: Kimmo Hatonen, Markus Miettinen
  • Publication number: 20050144148
    Abstract: A data processing system processes data arrays that collectively describe cyclic behavior of at least one variable in several entities in a physical process. Each cycle comprises several time slots. An input routine (2-4) receives multiple data arrays, each data array containing multiple data items, each of which describes a variable of an entity in one time slot. A magnitude-determination routine (2-6) determines a specific magnitude parameter, such as average, volume or peak, for each of the several entities. A scaling routine (2-8) scales the data arrays between entities such that the specific magnitude parameters are suppressed and only their shape is maintained. A training routine (2-10) trains a clustering system with a first plurality of the scaled data arrays, to determine a set of cluster centers. After training, a clustering routine (2-12) applies a second plurality of the scaled data arrays to the trained clustering system.
    Type: Application
    Filed: December 31, 2003
    Publication date: June 30, 2005
    Inventors: Kimmo Hatonen, Pekka Kumpulainen, Pekko Vehvilainen
  • Publication number: 20050138046
    Abstract: The invention discloses a method, a system and a computer program for storing data on a database in a manner that the integrity and authenticity of the database can be verified later. According to the invention a data record is signed with a checksum that is computed from the previous checksum, the data record to be stored and a storage key.
    Type: Application
    Filed: February 18, 2004
    Publication date: June 23, 2005
    Inventors: Markus Miettinen, Kimmo Hatonen
  • Publication number: 20050138483
    Abstract: The present invention relates to a method and apparatus for compressing a log record information provided e.g. to a monitoring system. Frequent patterns in the log information are detected and, then, redundant frequent patterns whose value or record combination is a subset of a value or record combination of another one of said detected frequent patterns are removed. Accordingly, a general method is provided which can be applied to all event logs arising from communication net-works or other monitoring systems. The detection of frequent patterns is only based on value or record combinations and is thus independent of the specific application. On the other hand, the size of the stored log files can be decreased remarkably while remaining readable for human beings.
    Type: Application
    Filed: March 26, 2002
    Publication date: June 23, 2005
    Inventors: Kimmo Hatonen, Markus Miettinen
  • Publication number: 20040117226
    Abstract: The invention proposes a method for configuring a network, wherein the network comprises a plurality of network sections, the method comprising the steps of accessing (S2) data from network sections; forming (S3) groups of network sections using a clustering method by using at least part of the accessed data as input data; and processing (S4) parameter on network section group level. By this method, the operation load during optimising a network consisting of a large number of cells can be greatly reduced. The invention also proposes a corresponding network optimising system.
    Type: Application
    Filed: September 25, 2003
    Publication date: June 17, 2004
    Inventors: Jaana Laiho, Albert Hoglund, Kimmo Raivio, Jukka Henriksson, Kimmo Hatonen, Ari Hamalainen
  • Publication number: 20040039968
    Abstract: The invention relates to a method and system for monitoring the behaviour of at least one observable object, e.g. a network element, of a network, wherein at least one parameter of the observable object is repeatedly detected. An actually detected parameter is input to a learning process and to an analyzing process, wherein the learning process forms a reference, based on at least two detected parameter values, for describing the behaviour of the observable object. The analyzing process compares the input parameter and the reference for detecting an anomal behaviour.
    Type: Application
    Filed: September 26, 2003
    Publication date: February 26, 2004
    Inventors: Kimmo Hatonen, Albert Hoglund, Markus Miettinen, Jyrki Berg, Kari Kulmala, Sampo Torikka
  • Publication number: 20030225520
    Abstract: A method for teaching an anomaly detecting mechanism in a system comprising observable elements (302), at least one of which has a periodic time-dependent behaviour, the anomaly detecting mechanism comprising a computerized learning mechanism (314). The method comprises assembling indicators (304) indicating the behaviour of the elements (302) and arranging the assembled indicators such that each observable element's indicators are assigned to the same input data component. The learning mechanism (314) is taught so that the input data of the learning mechanism comprises the input data components which are based on the assembled indicators (304). Points which approximate the input data are placed in the input space. A presentation of time (420-424) is incorporated into at least one input data component wherein the presentation of time is periodic, continuous and unambiguous within the period of the at least one element with periodic time-dependent behaviour.
    Type: Application
    Filed: March 7, 2003
    Publication date: December 4, 2003
    Inventors: Albert Hoglund, Kimmo Hatonen, Antti Sorvari