Abstract:
A data stream system includes one or more monitored machines generating real-time data stream that describes system activities of the monitored machines; a data stream management module receiving the real-time data stream; and a data stream archiving module coupled to the data stream management module, the data stream archiving module including a data stream receiver and a data stream inserter.
Abstract:
Systems and methods for managing one or more physical systems, including determining system behavior switching based on time series data from one or more sensors in the system. Time series is divided into a plurality of segments, and each of the segments represents a system behavior. A fitness model is generated for each of the segments to determine whether to select each of the segments as invariants, and an ensemble of local relationship models are built for each of the time series for each invariant to identify local behavior switching points over time. The identified local behavior switching points of each invariant are aggregated by aligning the local switching points of all invariant segments, computing a density distribution of the aligned switching points, and extracting local maximas of the density distribution to determine the global switching points. System operations are controlled based on the determined system behavior switching.
Abstract:
A system and method for detecting sensitive user input leakages in software applications, such as applications created for smartphone platforms. The system and method are configured to parse user interface layout files of the software application to identify input fields and obtain information concerning the input fields. Input fields that contain sensitive information are identified and a list of sensitive input fields, such as contextual IDs, is generated. The sensitive information fields are identified by reviewing the attributes, hints and/or text labels of the user interface layout file. A taint analysis is performed using the list of sensitive input fields and a sink dataset in order to detect information leaks in the sensitive input fields.
Abstract:
A method and system are provided. The method includes performing, by a logs-to-time-series converter, a logs-to-time-series conversion by transforming a plurality of heterogeneous logs into a set of time series. Each of the heterogeneous logs includes a time stamp and text portion with one or more fields. The method further includes performing, by a time-series-to-sequential-pattern converter, a time-series-to-sequential-pattern conversion by mining invariant relationships between the set of time series, and discovering sequential message patterns and association rules in the plurality of heterogeneous logs using the invariant relationships. The method also includes executing, by a processor, a set of log management applications, based on the sequential message patterns and the association rules.
Abstract:
Systems and methods for detection and prevention of Return-Oriented-Programming (ROP) attacks in one or more applications, including an attack detection device and a stack inspection device for performing stack inspection to detect ROP gadgets in a stack. The stack inspection includes stack walking from a stack frame at a top of the stack toward a bottom of the stack to detect one or more failure conditions, determining whether a valid stack frame and return code address is present; and determining a failure condition type if no valid stack frame and return code is present, with Type III failure conditions indicating an ROP attack. The ROP attack is contained using a containment device, and the ROP gadgets detected in the stack during the ROP attack are analyzed using an attack analysis device.
Abstract:
A system, method and computer program product for hierarchical sparse dictionary learning (“HiSDL”) to construct a learned dictionary regularized by an a priori over-complete dictionary, includes providing at least one a priori over-complete dictionary for regularization, performing sparse coding of the at least one a priori over-complete dictionary to provide a sparse coded dictionary, using a processor, updating the sparse coded dictionary with regularization using at least one auxiliary variable to provide a learned dictionary, determining whether the learned dictionary converges to an input data set, and outputting the learned dictionary regularized by the at least one a priori over-complete dictionary when the learned dictionary converges to the input data set. The system and method includes, when the learned dictionary lacks convergence, repeating the steps of performing sparse coding, updating the sparse coded dictionary, and determining whether the learned dictionary converges to the input data set.
Abstract:
A computer implemented method for network monitoring includes providing network packet event characterization and analysis for network monitoring that includes supporting summarization and characterization of network packet traces collected across multiple processing elements of different types in a virtual network, including a trace slicing to organize individual packet events into path-based trace slices, a trace characterization to extract at least 2 types of feature matrix describing those trace slices, and a trace analysis to cluster, rank and query packet traces based on metrics of the feature matrix.
Abstract:
Methods and systems for performance inference include inferring an internal application status based on a unified call stack trace that includes both user and kernel information by inferring user function instances. A calling context encoding is generated that includes information regarding function calling paths. Application performance is analyzed based on the encoded calling contexts. The analysis includes performing a top-down latency breakdown and ranking calling contexts according to how costly each function calling path is.
Abstract:
A method and system are provided for heterogeneous log analysis. The method includes performing hierarchical log clustering on heterogeneous logs to generate a log cluster hierarchy for the heterogeneous logs. The method further includes performing, by a log pattern recognizer device having a processor, log pattern recognition on the log cluster hierarchy to generate log pattern representations. The method also includes performing log field analysis on the log pattern representations to generate log field statistics. The method additionally includes performing log indexing on the log pattern representations to generate log indexes.
Abstract:
A device used in a network is disclosed. The device includes a network monitor to monitor a network state and to collect statistics for flows going through the network, a flow aggregation unit to aggregate flows into clusters and identify flows that can cause a network problem, and an adaptive control unit to adaptively regulate the identified flow according to network feedback. Other methods and systems also are disclosed.