Columbia University

Ack Ventures Holdings, LLC

Ack Venture Holdings, LLC

Eleazar Eskin

Salvatore J Stolfo

Andrew Honig

Manasi Bhattacharyya

Andrew Howard

Shlomo Herskop

Matthew G Schultz

Andrew Oliver Arnold

Michael Prerau

Erez Zadok

Leonid Portnoy

Frank Apap

Hershkop Shlomo

Stolfo Salvatore J

Stolfo J Salvatore

An application development platform enables applications to be created easily for, e.g., mobile devices that have short-range wireless communication capability. The development platform exposes a carefully chosen core set of services through an API. Each of the applications can broadcast its services to local and remote devices. Message delivery between devices is guaranteed even for messages that cannot be delivered directly by local short-range wireless transmission. Message delivery through other channels, including the Internet, can occur transparently to the user. Each device can be associated with an 'owner', which can be a person or a entity. Services can be customized to the owner based on stored information that maps owners to devices. Information associated with each of the owners of devices can be stored centrally and used in connection with providing the services at each of the mobile devices. Virtual GPS capabilities can be provided for mobile devices that do not have GPS chips.

Mobile computing and communication

A system and methods for detecting intrusions in the operation of a computer system comprises a sensor configured to gather information regarding the operation of the computer system, to format the information in a data record having a predetermined format, and to transmit the data in the predetermined data format. A data warehouse is configured to receive the data record from the sensor in the predetermined data format and to store the data in a SQL database. A detection model generator is configured to request data records from the data warehouse in the predetermined data format, to generate an intrusion detection model based on said data records, and to transmit the intrusion detection model to the data warehouse according to the predetermined data format. A detector is configured to receive a data record in the predetermined data format from the sensor and to classify the data record in real-time as one of normal operation and an attack based on said intrusion detection model. A data analysis engine is configured to request data records from the data warehouse according to the predetermined data format and to perform a data processing function on the data records.

System and methods for adaptive model generation for detecting intrusion in computer systems

A method for unsupervised anomaly detection, which are algorithms that are designed to process unlabeled data. Data elements are mapped to a feature space which is typically a vector space. Anomalies are detected by determining which points lies in sparse regions of the feature space. Two feature maps are used for mapping data elements to a feature apace. A first map is a data-dependent normalization feature map which we apply to network connections. A second feature map is a spectrum kernel which we apply to system call traces.

Methods of unsupervised anomaly detection using a geometric framework

A system and methods of detecting an occurrence of a violation of an email security policy of a computer system. A model relating to the transmission of prior emails through the computer system is defined which is derived from statistics relating to the prior emails. For selected emails to be analyzed, statistics concerning the selected email are gathered. Such statistics may refer to the behavior or other features of the selected emails, attachments to emails, or email accounts. The determination of whether a violation of an email security policy has occurred is performed by applying the model of prior email transmission to the statistics relating to the selected email. The model may be statistical or probabilistic. A model of prior email transmission may include grouping email recipients into cliques. A determination of a violation of a security policy may occur if email recipients for a particular email are in more than one clique.

System and methods for detecting malicious email transmission

Systems and methods for adaptive model generation for detecting intrusions in computer systems

A system and methods for detecting intrusions in the operation of a computer system comprising a sensor configured to gather information regarding the operation of the computer system, to format the information in a data record, and to transmit the data record. A database is configured to receive the data record from the sensor and to store the data record. A detection model generator is configured to request data records from the database, to generate an intrusion detection model, and to transmit the intrusion detection model to the database. A detector is configured to receive a data record from the sensor and to classify the data record in real-time as one of normal operation and an attack. A data analysis engine is configured to request data records from the database and to perform a data processing function on the data records.

A system and methods for detecting malicious executable attachments at an email processing application of a computer system using data mining techniques. The email processing application may be located at the server or at the client or host. The executable attachments are filtered from said email, and byte sequence features are extracted from the executable attachment. The executable attachments are classified by comparing the byte sequence feature of the executable attachment to a classification rule set derived from byte sequence features of a data set of known executables having a predetermined class in a set of classes, e.g., malicious or benign. The system is also able to classify executable attachments as borderline when the difference between the probability that the executable is malicious and the probability that the executable is benign are within a predetermined threshold. The system can notify the user when the number of borderline attachments exceeds the threshold in order to refine the classification rule set.

Systems and methods for detection of new malicious executables

A method for detecting intrusions in the operation of a computer system is disclosed which comprises gathering features from records of normal processes that access the files system of the computer, such as the Windows registry, and generating a probabilistic model of normal computer system usage based on occurrences of said features. The features of a record of a process that accesses the Windows registry are analyzed to determine whether said access to the Windows registry is an anomaly. A system is disclosed, comprising a registry auditing module configured to gather records regarding processes that access the Windows registry; a model generator configured to generate a probabilistic model of normal computer system usage based on records of a plurality of processes that access the Windows registry and that are indicative of normal computer system usage; and a model comparator configured to determine whether the access of the Windows registry is an anomaly.

System and methods for detecting intrusions in a computer system by monitoring operating system registry accesses

System and methods for detection of new malicious executables

A system and methods for detecting intrusions in the operation of a computer system comprises a sensor configured to gather information regarding the operation of the computer system, to format the information in a data record having a predetermined format, and to transmit the data in the predetermined data format. A data warehouse is configured to receive the data record from the sensor in the predetermined data format and to store the data in a database. A detection model generator is configured to request data records from the data warehouse in the predetermined data format, to generate an intrusion detection model based on said data records, and to transmit the intrusion detection model to the data warehouse according to the predetermined data format. A detector is configured to receive a data record in the predetermined data format from the sensor and to classify the data record in real-time as one of normal operation and an attack based on said intrusion detection model. A data analysis engine is configured to request data records from the data warehouse according to the predetermined data format and to perform a data processing function on the data records.

Growing community of inventors

Santa Monica, CA, United States of America

Eleazar Eskin