Abstract: Systems and methods for protection from buffer overflow vulnerability due to placement new constructs in C++ are provided. A system for protecting from buffer overflow vulnerability due to placement new constructs, comprises a compiler which is capable of receiving a program including a placement new instruction, and runtime which is capable of receiving binary code from the compiler and determining whether the program includes the placement new instruction and whether the placement new instruction would lead to buffer overflow, wherein the runtime is linked to a library including methods for preventing the buffer overflow, and selects a method for preventing the buffer overflow if the runtime determines that the placement new instruction would lead to the buffer overflow.

Abstract: The various aspects provide for a computing device and methods implemented by the device to ensure that an application executing on the device and seeking root access will not cause malicious behavior while after receiving root access. Before giving the application root access, the computing device may identify operations the application intends to execute while having root access, determine whether executing the operations will cause malicious behavior by simulating execution of the operations, and pre-approve those operations after determining that executing those operations will not result in malicious behavior. Further, after giving the application root access, the computing device may only allow the application to perform pre-approved operations by quickly checking the application's pending operations against the pre-approved operations before allowing the application to perform those operations.

Abstract: Performing adaptive cyber-security analytics including a computer implemented method that includes receiving a report on a network activity. A score responsive to the network activity and to a scoring model is computed at a computer. The score indicates a likelihood of a security violation. The score is validated and the scoring model is automatically updated responsive to results of the validating. The network activity is reported as suspicious in response to the score being within a threshold of a security violation value.

Abstract: Methods, systems and devices use operating system execution states while monitoring applications executing on a mobile device to perform comprehensive behavioral monitoring and analysis include configuring a mobile device to monitor an activity of a software application, generate a shadow feature value that identifies an operating system execution state of the software application during that activity, generate a behavior vector that associates the monitored activity with the shadow feature value, and determine whether the activity is malicious or benign based on the generated behavior vector, shadow feature value and/or operating system execution states.

Abstract: A method for identifying an unknown user according to a plurality of facets of user activity in a plurality of contexts includes receiving a plurality of priors for the facets with respect to the contexts, receiving a plurality of footprints of known users, aggregating the footprints of the users to determine an ensemble prior, receiving a plurality of network traces relevant to an unknown user in a computer environment, matching the network traces against each of the footprints to determine a plurality of matches, aggregating the matches using the ensemble prior according to the facets and the contexts, and outputting a probable user identity for the unknown user.

Abstract: Methods and apparatus are provided for detecting unauthorized bulk forwarding of sensitive data over a network. A bulk forwarding of email from a first network environment is automatically detected by determining an arrival rate for internal emails received from within the first network environment into one or more user accounts; determining a sending rate for external emails sent from the one or more user accounts to a second network environment; and detecting the bulk forwarding of email from a given user account by comparing the arrival rate for internal emails and the sending rate for external emails. The bulk forwarding of email from a given user account can be detected by determining whether statistical models of the arrival rate for internal emails and of the sending rate for external emails are correlated in time.

Abstract: A system, method and computer program product for verifying integrity of a running application program on a computing device. The method comprises: determining entry points into an application programs processing space that impact proper execution impact program integrity; mapping data elements reachable from the determined entry points into a memory space of a host system where the application to verify is running; run-time monitoring, in the memory space, potential modification of the data elements in a manner potentially breaching program integrity; and initiating a response to the potential modification. The run-time monitoring detects when a data transaction, e.g., a write event, reaches a malicious agent's entry point, a corresponding memory hook is triggered and control is passed to a security agent running outside the monitored system.

Abstract: Methods and apparatus are provided for detecting unauthorized bulk forwarding of sensitive data over a network. A bulk forwarding of email from a first network environment is automatically detected by determining an arrival rate for internal emails received from within the first network environment into one or more user accounts; determining a sending rate for external emails sent from the one or more user accounts to a second network environment; and detecting the bulk forwarding of email from a given user account by comparing the arrival rate for internal emails and the sending rate for external emails. The bulk forwarding of email from a given user account can be detected by determining whether statistical models of the arrival rate for internal emails and of the sending rate for external emails are correlated in time.

Abstract: Access is obtained to a plurality of information flow theories for a plurality of malicious programs. The information flow theories include differences in information flows between the malicious programs, executing in a controlled environment, and information flows of known benign programs. Execution of a suspicious program is monitored by comparing runtime behavior of the suspicious program to the plurality of information flow theories. An alarm is output if the runtime behavior of the suspicious program matches at least one of the plurality of information flow theories.

Abstract: A distributed feature collection and correlation engine is provided, Feature extraction comprises obtaining one or more data records; extracting information from the one or more data records based on domain knowledge; transforming the extracted information into a key/value pair comprised of a key K and a value V, wherein the key comprises a feature identifier; and storing the key/value pair in a feature store database if the key/value pair does not already exist in the feature store database using a de-duplication mechanism. Features extracted from data records can be queried by obtaining a feature store database comprised of the extracted features stored as a key/value pair comprised of a key K and a value V, wherein the key comprises a feature identifier; receiving a query comprised of at least one query key; retrieving values from the feature store database that match the query key; and returning one or more retrieved key/value pairs.

Abstract: A distributed feature collection and correlation engine is provided, Feature extraction comprises obtaining one or more data records; extracting information from the one or more data records based on domain knowledge; transforming the extracted information into a key/value pair comprised of a key K and a value V, wherein the key comprises a feature identifier; and storing the key/value pair in a feature store database if the key/value pair does not already exist in the feature store database using a de-duplication mechanism. Features extracted from data records can be queried by obtaining a feature store database comprised of the extracted features stored as a key/value pair comprised of a key K and a value V, wherein the key comprises a feature identifier; receiving a query comprised of at least one query key; retrieving values from the feature store database that match the query key; and returning one or more retrieved key/value pairs.

Abstract: Methods, systems and devices for communicating behavior analysis information using an application programming interface (API) may include receiving via the API a request to register the second module to access an operation of a behavioral monitoring system of the mobile computing device, and exchanging authentication information between the first module and the second module to accomplish mutual authentication. Aspects may include receiving via the API a request for version identification information that may be used by the server to determine how to interpret, evaluate, or crowd-source information, and exchanging version identification information between the first module and the second module to cause the second module to send the information to the server. Aspects may further include receiving via the API a provision malware model request including a command causing the first module to send a malware or classifier model to a behavioral monitoring system of the mobile computing device.

Abstract: Embodiments of the invention relate to application and services promotions. One embodiment includes presenting an application or service by an application or service promotion provider, for exposing, the application or service to potential users. Recommendation and promotion preferences are selected for the application or service. The application or service is provided to an electronic device based on the recommendation and promotion preferences. It is determined whether user action occurs for the application or service using the electronic device. Revenue is generated upon user action occurring for the application or service.

Abstract: The present principles are directed to identifying and classifying web traffic inside encrypted network tunnels. A method includes analyzing network traffic of unencrypted data packets to detect packet traffic, timing, and size patterns. The detected packet, timing, and size traffic patterns are correlated to at least a packet destination and a packet source of the unencrypted data packets to create at least one of a training corpus and a model built from the training corpus. The at least one of the corpus and model is stored in a memory device. Packet traffic, timing, and size patterns of encrypted data packets are observed. The observed packet traffic, timing, and size patterns of the encrypted data packets are compared to at least one of the training corpus and the model to classify the encrypted data packets with respect to at least one of a predicted network host and predicted path information.

Abstract: The present principles are directed to identifying and classifying web traffic inside encrypted network tunnels. A method includes analyzing network traffic of unencrypted data packets to detect packet traffic, timing, and size patterns. The detected packet, timing, and size traffic patterns are correlated to at least a packet destination and a packet source of the unencrypted data packets to create at least one of a training corpus and a model built from the training corpus. The at least one of the corpus and model is stored in a memory device. Packet traffic, timing, and size patterns of encrypted data packets are observed. The observed packet traffic, timing, and size patterns of the encrypted data packets are compared to at least one of the training corpus and the model to classify the encrypted data packets with respect to at least one of a predicted network host and predicted path information.

Abstract: Methods for determining cyber-attack targets include collecting and storing network event information from sensors to extract information regarding an attacker; forming an attack scenario tree that encodes network topology and vulnerability information including paths from known compromised nodes to a set of potential targets; calculating a likelihood for each of the paths using a processor; calculating a probability distribution for the set of potential targets to determine which potential targets are most likely pursued by the attacker; calculating a probability distribution over a set of nodes and node vulnerability types already accessed by the attacker; determining a network graph edge to remove which minimizes a defender's expected uncertainty over the potential targets; and removing the determined network graph edge.

Abstract: Access is obtained to a plurality of information flow theories for a plurality of malicious programs. The information flow theories include differences in information flows between the malicious programs, executing in a controlled environment, and information flows of known benign programs. Execution of a suspicious program is monitored by comparing runtime behavior of the suspicious program to the plurality of information flow theories. An alarm is output if the runtime behavior of the suspicious program matches at least one of the plurality of information flow theories.

Abstract: Systems and methods for recognizing and reacting to malicious or performance-degrading behaviors in a mobile device include observing mobile device behaviors in an observer module within a privileged-normal portion of a secure operating environment to identify a suspicious mobile device behavior. The observer module may generate a concise behavior vector based on the observations, and provide the vector to an analyzer module in an unprivileged-secure portion of the secure operating environment. The vector may be analyzed in the unprivileged-secure portion to determine whether the mobile device behavior is benign, suspicious, malicious, or performance-degrading. If the behavior is found to be suspicious, operations of the observer module may be adjusted, such as to perform deeper observations. If the behavior is found to be malicious or performance-degrading behavior the user and/or a client module may be alerted in a secure, tamper-proof manner.

Abstract: Systems and methods for protection from buffer overflow vulnerability due to placement new constructs in C++ are provided. A system for protecting from buffer overflow vulnerability due to placement new constructs, comprises a compiler which is capable of receiving a program including a placement new instruction, and runtime which is capable of receiving binary code from the compiler and determining whether the program includes the placement new instruction and whether the placement new instruction would lead to buffer overflow, wherein the runtime is linked to a library including methods for preventing the buffer overflow, and selects a method for preventing the buffer overflow if the runtime determines that the placement new instruction would lead to the buffer overflow.

Abstract: Systems and methods for protection from buffer overflow vulnerability due to placement new constructs in C++ are provided. A system for protecting from buffer overflow vulnerability due to placement new constructs, comprises a compiler which is capable of receiving a program including a placement new instruction, and runtime which is capable of receiving binary code from the compiler and determining whether the program includes the placement new instruction and whether the placement new instruction would lead to buffer overflow, wherein the runtime is linked to a library including methods for preventing the buffer overflow, and selects a method for preventing the buffer overflow if the runtime determines that the placement new instruction would lead to the buffer overflow.