Mohaisen
Abedelaziz Mohaisen, Daejeon KR
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20100125608 | ROTATION BASED TRANSFORMATION METHOD AND APPARATUS FOR PRESERVING DATA PRIVACY - The present invention includes a rotation based transformation method for preserving data privacy. A rotation based transformation method according to an embodiment of the present invention divides a given data set into a plurality of data subsets, applies a plurality of different rotation matrixes to the plurality of divided data subsets, respectively, to rotate the plurality of data subsets, and re-concatenates the plurality of rotated data subsets to generate a rotated data set. The rotated data set is released and used for data clustering. The rotation based transformation method is effectively used when the impact of the AK-ICA attack is mitigated. Meanwhile, when the two parties are related to the present invention, the two parties need to agree on parameters, such as the number of data subsets. It is preferable that the data subsets be divided into equal sizes. Further, rotation-unification work that removes relative rotation deviation between the plurality of different rotation matrices can be performed in order to provide valid clustering between the data subsets rotated using the different rotation matrixes. | 05-20-2010 |
20110145929 | APPARATUS AND METHOD FOR PRIVACY PROTECTION IN ASSOCIATION RULE MINING - There are provided an apparatus and a method for privacy protection in association rule mining among data mining technologies. An apparatus for privacy protection in association rule mining according to an embodiment of the present invention comprises: a fake transaction inserter that generates fake transactions of a predetermined number each having a predetermined length and inserts the fake transactions between a plurality of transactions comprised in an original data set to generate a first virtual data set; and a distortion transaction generator that generates a second virtual data set by converting data of the transaction of the first virtual data set with a predetermined probability. | 06-16-2011 |
Abedelaziz Mohaisen, Chantilly, VA US
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20140337460 | SYSTEMS, DEVICES, AND METHODS FOR PROTECTING ACCESS PRIVACY OF CACHED CONTENT - Embodiments relate to systems, devices, and computer-implemented methods for preventing determination of previous access of sensitive content by receiving, from a user, a request for content at a device in an information centric network, where a cached version of the content is locally stored at the device; initiating a time delay based on a determination that the user has not previously requested the content; and transmitting the cached version of the content to the user after the time delay. | 11-13-2014 |
20150106494 | CHARACTERIZATION OF DOMAIN NAMES BASED ON CHANGES OF AUTHORITATIVE NAME SERVERS - Embodiments relate to systems, devices, and computer-implemented methods for characterizing domain names by determining a name server switching footprint for domain names using a data set corresponding to name server operations for the domain names. The domain names can be clustered into groups based on the name server switching footprints, and intended uses of domain names in a group can be extrapolated to other domain names in the group. Name server switching footprints can also be predicted for new domains names using a prediction model trained using the determined name server switching footprints for the domain names in the data set. | 04-16-2015 |
20150106931 | CLASSIFYING MALWARE BY ORDER OF NETWORK BEHAVIOR ARTIFACTS - The present invention generally relates to systems and methods for classifying executable files as likely malware or likely benign. The techniques utilize temporally-ordered network behavioral artifacts together with machine learning techniques to perform the classification. Because they rely on network behavioral artifacts, the disclosed techniques may be applied to executable files with obfuscated code. | 04-16-2015 |
Abedelaziz Mohaisen, Williamsville, NY US
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20160127397 | SYSTEMS, DEVICES, AND METHODS FOR SEPARATING MALWARE AND BACKGROUND EVENTS - Embodiments relate to systems, devices, and computing-implemented methods for separating malware and background events to classify malware based on traffic data by receiving the traffic data that includes malware events and background noise, converting the traffic data into a feature vector, performing a signal processing algorithm on the feature vector to separate the malware events from the background noise, where the signal processing algorithm is associated with a malware family, determining a score for the malware events using a malware classification algorithm associated with the malware family, and applying a label associated with the malware family to the traffic data based on the score to classify the traffic data. Additionally, the malware application can be contained, removed, and/or the effects of a malware application can be neutralized based on the classification. | 05-05-2016 |
Aziz Mohaisen, Chantilly, VA US
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20150244733 | SYSTEMS AND METHODS FOR BEHAVIOR-BASED AUTOMATED MALWARE ANALYSIS AND CLASSIFICATION - Embodiments relate to systems and methods for behavior-based automated malware analysis and classification. Aspects relate to platforms and techniques which access a set of samples of malware, and extract or capture a set of low-level behavioral artifacts produced by those samples. The low-level artifacts can be used to organize or identify a set of features, based upon which the sample can be classified and/or clustered into different labels, groups, or categories. The artifacts and/or features can be analyzed by one or more selectable algorithms, whose accuracy, efficiency, and other characteristics can be compared to one another for purposes of performing a classification or clustering task. The algorithm(s) can be selected by a user to achieve desired run times, accuracy levels, and/or other effects. | 08-27-2015 |
Manar Mohaisen, Incheon KR
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20100182897 | SIGNAL DETECTING METHOD FOR SPATIAL MULTIPLEXING MULTIPLE-INPUT MULTIPLE-OUTPUT SYSTEMS - A method for detecting signals in spatial multiplexing multiple-input multiple-output (MIMO) systems using a QR-decomposition with M (QRD-M) algorithm is provided. The method includes receiving signals, limiting upper and lower bounds of a complexity in a QR-decomposition with M (QRD-M) algorithm, and detecting the received signals using the QRD-M algorithm. The signal detecting method can effectively reduce the amount of operation generated while detecting signals, using the QRD-M algorithm where the upper and lower bounds of the complexity are limited. | 07-22-2010 |
20110044407 | ADAPTIVE QRD-M ALGORITHM BASED SIGNAL DETECTING METHOD BY USING CONSTELLATION SET GROUPING IN SPATIAL MULTIPLEXING MULTIPLE-INPUT MULTIPLE-OUTPUT SYSTEM - There is provided a signal detecting method using constellation set grouping in a spatial multiplexing multiple input multiple output system. The signal detecting method includes dividing a set of candidate symbols, a constellation set into a plurality of subsets by grouping the constellation set; dividing a tree search process of a QR-decomposition with M-algorithm (QRDM) algorithm into a plurality of partial detection phases; and performing the plurality of divided partial detection phases in parallel or iteratively. | 02-24-2011 |