Symantec Corporation

Jeffrey Wilhelm

Carey S Nachenberg

Joseph Chen

Matthew Yeo

Frank X Barajas

Sourabh Satish

Shaun P Cooley

Michael Andrew Hart

Sandeep B Bhatkar

Adam Glick

Alfred C Hartmann

Susanta Kumar Nanda

Abubakar A Wawda

Scott D Schneider

Sharada Sundaram

Adam Bromwich

Adam Wright

Pak Wai Yung

James Croall

A computer-implemented method for managing network security may include identifying a set of trusted Internet domains, identifying traffic information that indicates Internet traffic volume for each trusted Internet domain in the set of trusted Internet domains, and analyzing the traffic information to select, from the set of trusted Internet domains, a subset of trusted Internet domains that each have higher Internet traffic volume than one or more other trusted Internet domains in the set of trusted Internet domains. The method may also include including the selected subset of trusted Internet domains in an Internet domain whitelist. The method may further include configuring a network gateway system to perform a less intensive scan on Internet traffic that originates from an Internet domain identified in the Internet domain whitelist than on traffic that originates from other Internet domains. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for managing network security

A computer-implemented method for assessing Internet addresses may include (1) identifying an Internet Protocol address, (2) identifying a plurality of files downloaded from the Internet Protocol address, (3) generating an aggregation of security assessments that relates to the Internet Protocol address and that may be based at least in part on a security assessment of each of the plurality of files, (4) determining a trustworthiness of the Internet Protocol address based at least in part on the aggregation of security assessments and (5) facilitating a security action based at least in part on the trustworthiness of the Internet Protocol address. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for assessing internet addresses

The disclosed computer-implemented method for anticipating file-security queries may include (1) monitoring queries from client devices for information that describes the security of files, (2) determining that a threshold number of the client devices are querying for information describing the security of a file within a threshold amount of time, (3) anticipating, based on the determination, that at least one client device that did not query for the information will query for the information, and (4) delivering, in response to anticipating that the client device that did not query for the information will query for the information, the information to the client device that did not query for the information. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for anticipating file-security queries

A computer-implemented method for trust propagation of signed files across devices may include identifying a signed file on a device, calculating, on the device, a hash based at least in part on the signed file, querying, with the hash, a server which has verified that the signed file is trustworthy based on a digital signature of the signed file having been verified by an additional device capable of verifying digital signatures, receiving on the device, in response to querying the server, a trust indicator indicating that the digital signature of the signed file has been verified and trusting the signed file on the device, based on the trust indicator indicating that the digital signature of the signed file has been verified. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for trust propagation of signed files across devices

A plurality of classifiers is identified. A set of test cases is selected based on time. The set of test cases are grouped into a plurality of datasets based on time where each of the plurality of datasets is associated with a corresponding interval of time. Each of the plurality of classifiers is applied to each of the plurality of datasets to generate classifications for test cases in each of the plurality of datasets. For each of the plurality of classifiers, a classification performance score is determined for each of the plurality of datasets based on the classifications generated for the test cases of each dataset. A classifier is selected from among the plurality of classifiers for production based on the classification performance scores of each of the plurality of classifiers across the plurality of datasets.

Identifying predictive models resistant to concept drift

A computer-implemented method for preventing chronic false positives may include (1) whitelisting a file based on a challenge notification that challenges a classification of the file as insecure, (2) obtaining attribute information about the file, (3) identifying, by analyzing the attribute information, a primitive that identifies a source of origin for the file, (4) determining, based on an analysis of files that originate from the source of origin, that the source of origin identified by the primitive is trustworthy, and (5) adjusting, based on the determination that the source of origin identified by the primitive is trustworthy, a security policy associated with the primitive to prevent future false positives for other files that originate from the source of origin. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for preventing chronic false positives

A client sends a file information request to a security server, where the file information request identifies a URL from which the client is attempting to download a file. Upon receiving the request, the security server determines the stability information of the identified URL and provides the requested file information for the file provided by the URL. The security server determines the stability information of a URL by analyzing the file identifiers and URLs identified in downloaded file reports received from multiple clients. The determination of the stability information of a URL may be based on a variety of factors, such as stability of a URL over time, a textual analysis of the URL, and the set of files provided by the URL. A user of the client can review the file information and decide whether to expend the resources to download the file.

Providing file information to a client responsive to a file download stability prediction

A computer-implemented method for treating locally created files as trustworthy may include identifying at least one file created on a computing system protected by a security system that determines whether files encountered by the computing system are trustworthy. The method may also include identifying a software application used to create the file on the computing system. The method may further include determining that the software application used to create the file on the computing system comprises a reputable software application used to create trustworthy files within a user community comprising users of computing systems protected by the security system. In addition, the method may include establishing a trustworthiness exception that causes the security system to treat the file as trustworthy on the computing system that created the file. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for treating locally created files as trustworthy

A method and apparatus for automatically excluding false positives from detection as malware is described. In one embodiments, a method for using one or more processors to provide false positive reduction for heuristic-based malware detection of a plurality of files in memory includes accessing global first appearance information associated with a plurality of files, accessing global malware information comprising heuristics and an emergence date associated with each malware group of a plurality of malware groups, comparing the global malware information with the global first appearance information to identify at least one false positive amongst the plurality of files and preventing detection of the at least one false positive as malware.

Method and apparatus for automatically excluding false positives from detection as malware

A parsing module identifies a framed page within a web page received from a network. The parsing module further identifies information regarding the frame such as the framed page's uniform resource locator. A lookup module accesses a memory module to determine if the identified information regarding the frame is included in a protection list stored in the memory module. A notification module notifies a client's user that the framing web page is fraudulent if the identified information regarding the frame is included in the protection list. Alternatively, the parsing module is adapted to identify a security tag within the framed page indicating that the framed page is not permitted to be displayed within a frame. If the framed page includes a security tag, the notification module notifies the client's user that the framing web page is fraudulent.

Frame injection blocking

A parsing module receives a web page from a network. The parsing module identifies a frame embedded within the intercepted web page. The parsing module identifies information regarding the embedded frame. A collection module collects the identified information regarding the embedded frame and maintains such information in an exclusion list stored in a memory module. A lookup module intercepts a web page from the network before the web page reaches the client. The lookup module identifies information regarding this web page and accesses the memory module to determine if the identified information is included in the exclusion list. If the identified information regarding the web page is not included in the exclusion list, a modification module modifies the web page such that the web page will not be loaded on the client within a frame.

Dynamic frame buster injection

Techniques for identifying potential malware domain names are disclosed. In one particular exemplary embodiment, the techniques may be realized as a system for identifying potential malware domain names. The system may comprise one or more processors communicatively coupled to a network. The one or more processors may be configured to receive a request for network data, where the request for network data may comprise a domain name. The one or more processors may also be configured to apply a lexical and linguistic analysis to the domain name. The one or more processors may also be configured to identify whether the domain name is a potential malware domain name based on the lexical and linguistic analysis.

Techniques for identifying potential malware domain names

A method for using acquisitional contexts to prevent false-positive malware classifications. The method may include (1) receiving, from at least one client-side computing device within a community of users, contextual information associated with a file, (2) determining, based at least in part on the contextual information received from the client-side computing device, a reputation rating for the file, and (3) providing the reputation rating for the file to at least one additional client-side computing device within the community in order to prevent the additional client-side computing device from falsely classifying the file as untrustworthy due to acquiring an additional instance of the file via a context that is insufficient to determine that the additional instance of the file is trustworthy. Various other methods and systems are also disclosed.

Systems and methods for using acquisitional contexts to prevent false-positive malware classifications

Techniques for behavior based malware analysis are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method for behavior based analysis comprising receiving trace data, analyzing, using at least one computer processor, observable events to identify low level actions, analyzing a plurality of low level actions to identify at least one high level behavior, and providing an output of the at least one high level behavior.

Growing community of inventors

Los Angeles, CA, United States of America

Jeffrey Wilhelm