Abstract: A system and method for implementing a centralized innovation framework module are disclosed. A processor is operatively connected to one or more memories via a communication network. The processor creates a centralized web-based collaborative platform hub for collection of innovation ideas data from end users within an operation space and causes the centralized web-based collaborative platform hub to receive innovation ideas data from an end user related to development of an application. The processor also analyzes the received innovation ideas data establishes, based on analyzing, a connection between the centralized web-based collaborative platform hub and a development platform; migrates the received innovation ideas data onto the development platform; and creates a workflow on the development platform for tracking and managing development processes of the application.

Abstract: This disclosure relates generally to system and method for assessing insider influence on enterprise assets. Existing work focuses on the detection of insider threat and does not consider the influence of an insider on their peers and subordinates. The present disclosure aggregates and preprocesses the enterprise data specific to the individuals received from various sources, and further creates an enterprise graph between entities. Weights of every edge connected between any two entities in the enterprise graph is then calculated. Community of the individuals are detected wherein, relevant insider(s) are identified, and susceptibility of the individuals for probable influence by relevant insider(s) based on the analysis scenarios(s) is calculated. Paths taken by the relevant insider(s) is calculated for estimating probability of data loss.

Abstract: This disclosure relates generally to online learning against data poisoning attack. Conventional methods used data sanitization techniques for online learning against data poisoning attack. However, these methods do not remove poisoned data points from training dataset completely. Embodiments of the present disclosure method provide an influence based defense method for secure online learning against data poisoning attack. The method initially filters a subset of poisoned data points in the training dataset for training a machine learning model using data sanitization technique. Further the method computes an influence of the data points and performs an influence minimization based on a predefined threshold. Updated data points for the learning model are generated and used for training the machine learning model. The disclosed method can be used against data poisoning attacks in applications such as spam filtering, malware detection, recommender system and so on.

Abstract: Data-driven applications depend on training data obtained from multiple internal and external data sources. Hence poisoning of the training data can cause adverse effects in the data driven applications. Conventional methods identifies contaminated test samples and avert them from entering into the training. A generic approach covering all data-driven applications and all types of data poisoning attacks in an efficient manner is challenging. Initially, data aggregation is performed after receiving a ML application for testing. A plurality of feature vectors are extracted from the aggregated data and a poisoned data set is generated. A plurality of personas are generated and are further prioritized to obtain a plurality of attack personas. Further, a plurality of security assessment vectors are computed for each of the plurality of attack personas. A plurality of preventive measures are recommended for each of the plurality of attack personas based on the corresponding security assessment vector.

Abstract: Techniques for managing access to content are provided that include receiving a first signal requesting an indication whether a user has an access privilege to access to a resource associated with a first tenant of an access management service or perform an operation by a data processing system using the resource, determining that a first user account associated with the user does not have an access privilege to access the resource; performing a nested access privilege check to determine whether the user is associated with a second user account that has the access privilege to access the resource; and granting via the communication network access to the resource responsive to the nested access privilege check determining that the user is associated with the second user account and the second user account is associated with the access privilege to access the resource.

Abstract: A computer system tracks and analyzes activity data, notifications, and user interactions with activity data and notifications. By analyzing this information, the computer system can identify, for individual users and across a set of users, which activity data and notifications are most relevant. Such activity data and notifications are most relevant when they result in the end user having further user interaction through the electronic document. The information about the relevance of the activity data and notifications can be used for managing sending of notifications and presenting activity data in end user applications.

Abstract: This disclosure relates generally to malware detection, and more particularly to system and method for detecting and mitigating ransomware threats. For a User Equipment being monitored, the system performs a behavior analysis of corresponding file system to determine whether any anomalous behavior that would amount to a ransomware threat is associated with flies associated with the file system change, if present, then the system virtualizes the file system on the fly. If information pertaining to the identified anomalous behavior is present in any of the reference databases in the system, then all the I/O calls are terminated or the file system is virtualized for rest of the session. If data pertaining to the identified anomalous behavior is not found in any of the associated databases, then new behavioral features and structural patterns of the identified anomalous behavior and the associated processes are extracted, and the reference databases are updated accordingly.

Abstract: Authentication keys are selectively cached locally for faster roaming of wireless stations in a communication network. An attempt by a station to reassociate with an access point is detected. Responsive to identifying a key corresponding to the station as evidence of a previous association, the key is retrieved from the key cache without contracting a controller or an authentication server, for faster responses. At least one modified response frame is generated to include the identified key along with an approval of the association between the access point and the station. The at least one modified response is sent from the access point to the station. An attempt to roam to a station for a first time is detected responsive to a key cache miss at the access point. If the station has previously associated with an access point under purview of the controller, keys are located and sent back to the access point without contacting an authentication server as an improvement over IEEE 802.11r.

Abstract: Systems and methods for sensitive audio zone rearrangement are provided that protects confidential and sensitive information such as user identifier during query processing and authentication. The sensitive information rearrangement system generates or permutes the actual user identifier in a privacy preserving manner. The sensitive information is extracted from an input being either a speech or DTMF tones, and a virtual user identifier is generated in real time, that is specific to a transaction to be performed, or a query initiation by a user in real-time. The sensitive information is rearranged which can be either DTMF tone or speech of user to generate the virtual user identifier.

Abstract: This disclosure relates generally to data masking, and more particularly to method and system for dynamic data masking for mainframe application. In one embodiment, the method includes receiving a request to access a mainframe application from a user profile. A role assigned to the user-profile is fetched from a roles-repository. The role defines rights associated with the user-profile to access information from the mainframe application. Corresponding to the request, an access session is initiated based on the role, and a screen is received. The screen includes a multiple fields, where one or more fields includes sensitive data associated with the mainframe application. Contextual information associated with the plurality of fields is identified corresponding to the session. Rules indicative of the fields to be masked, are fetched corresponding to the screen based on the role. The fields are masked based on the rule and the contextual information associated with the fields.

Abstract: This disclosure provides systems, methods and apparatuses for channel selection and channel selection planning in a network including a root AP (RAP) and a number of satellite APs (SAPs). The root AP may assign operating channels for one or more of the satellite APs in a manner that optimizes network performance by considering the impact that each of the satellite APs (as well as their respective client devices) may have on the network. In some implementations, the root AP may provide centralized channel selection planning for the network based a number of network parameters observed by one or more of the satellite APs. The network parameters may include, for example, channel conditions, traffic loads, traffic patterns, service needs of client devices, available channels, and other network utilization information observed by one or more of the satellite APs.

Abstract: The present disclosure provides systems and methods to estimate Importance Measure (IM) and temporal Importance Measure (IM) for any type of data in a distributed enterprise network by involving direct and indirect stakeholders of the data in the estimation process. Firstly data type of the received data is identified. Data type plugins including pre-defined classes, IM matrix and Temporal IM matrix are loaded for the identified data type. Extracted features from the data are appropriately mapped against pre-defined classes and then the IM is estimated. Temporal IM is estimated taking into account the current time and the rate of change.

Abstract: A method and system is provided for managing complaint and reputation in a multi-party data marketplace. The system is managed by an independent external entity to monitor the data transactions in an unbiased manner. The system considers the data as commodity or resource, which is perishable and whose worth might decay with time. The system defines new parameters for reputation and liability calculation (based on complaints), for example, consideration of peer and trust network, history of peering and transaction, automatic decay of reputation and liability in case of inactive participants. According to another embodiment, the disclosure also handles any kind of collusion between external or internal entities/parties/participants. Whereas in another embodiment the disclosure also identifies and restrict influencers in a multi-party data marketplace.

Abstract: The present disclosure provides systems and methods to optimize data backup in a distributed enterprise system by firstly generating a set of unique files from all the files available in the enterprise. A backup set comprising files to be backed up are then generated from the set of unique files and backup is scheduled in the order in which the files to be backed up are identified. Unique files are generated based on file sharing patterns and communications among users that enable generating a social network graph from which one or more communities can be detected and deduplication can be performed on the files hosted by client systems in these communities thereby conserving resources.

Abstract: Aspects of the present disclosure implement techniques that allow the serving AP to obtain signal quality information over backhaul link from one or more target APs as it relates to one or more STAs that are currently being served by the serving AP. The target APs may measure signal quality between the target AP and the STA by observing uplink communication between the STA and the serving AP that may be broadcasted over the network. Based on the signal quality information received by the serving AP from one or more target APs, the serving AP may determine whether the signal quality for the STA would improve if the STA shifts from the serving AP to the target AP.

Abstract: Described herein is a method for rendering specification creation, including identifying, within one or more contents, labels as sensitive labels when data associated with the label are determined sensitive based on one or more user-defined policy rules, wherein the identifying considers structural locations of labels determined as sensitive and the data associated with the sensitive label; configuring rendering specifications for data associated with the identified sensitive labels; and associating the configured rendering specifications with the sensitive labels of the data determined as sensitive, for execution in real time.

Abstract: An end user application stores activity data in a part of an electronic document. When the electronic document is stored on a shared storage system, activity data is extracted and stored in an activity store. After activity data has been successfully stored in the activity store, the end user application can remove the activity data from the electronic document. In particular, the end user application can periodically query the activity store to identify activities that have been successfully stored in the activity store. By removing the activity data from the electronic document, the electronic document can be maintained at a reasonable size. By having the end user application remove the activity data, coherency of the data file, and consistency between local copies on end user computers and copies on the shared storage system, can be maintained.

Abstract: Aggregation windows are dynamically resized based on network congestion feedback from VOIP and other mixed types of traffic. Feedback indicative of a level of network congestion on the data communication network where aggregate packets are transmitted is received. The network congestion level is checked to see if a predetermined threshold has been exceeded. Responsive to exceeding the threshold, the network congestion level is correlated to an optimal data field size for the aggregated data packets. Further, a MAC layer is configured for the optimal data field size for frame generation. Subsequent aggregated data packets are then transmitted using the optimal data field size.

Abstract: A computer system tracks and analyzes activity data, notifications, and user interactions with activity data and notifications. By analyzing this information, the computer system can identify, for individual users and across a set of users, which activity data and notifications are most relevant. Such activity data and notifications are most relevant when they result in the end user having further user interaction through the electronic document. The information about the relevance of the activity data and notifications can be used for managing sending of notifications and presenting activity data in end user applications.

Abstract: This disclosure relates generally to malware detection, and more particularly to system and method for detecting and mitigating ransomware threats. For a User Equipment being monitored, the system performs a behavior analysis of corresponding file system to determine whether any anomalous behavior that would amount to a ransomware threat is associated with flies associated with the file system change, if present, then the system virtualizes the file system on the fly. If information pertaining to the identified anomalous behavior is present in any of the reference databases in the system, then all the I/O calls are terminated or the file system is virtualized for rest of the session. If data pertaining to the identified anomalous behavior is not found in any of the associated databases, then new behavioral features and structural patterns of the identified anomalous behavior and the associated processes are extracted, and the reference databases are updated accordingly.