Abstract: The disclosed systems and methods include pre-calculation, per object, of object feature bin values, for identifying close matches between objects, such as text documents, that have numerous weighted features, such as specific-length word sequences. Predetermined feature weights get scaled with two or more selected adjacent scaling factors, and randomly rounded. The expanded set of weighted features of an object gets min-hashed into a predetermined number of feature bins. For each feature that qualifies to be inserted by min-hashing into a particular feature bin, and across successive feature bins, the expanded set of weighted features get min-hashed and circularly smeared into the predetermined number of feature bins. Completed pre-calculated sets of feature bin values for each scaling of the object, together with the scaling factor, are stored for use in comparing sampled features of the object with sampled features of other objects by calculating an estimated Jaccard similarity index.

Abstract: According to an implementation of the disclosure, a computing device may record substantially all the network traffic being transported over a first node of a network over a period of time. The computing device may receive an authenticated request from a forensics system that includes access criteria. The first computing device may determine a relevant encrypted and unencrypted portion of the network traffic based on the access criteria. Based on unencrypted portion, the computing device may recalculate an encryption key applicable to the encrypted portion. The computing device may then replicate the relevant portion and the encryption key to the forensics system for forensic analysis.

Abstract: The disclosed systems and methods include pre-calculation, per object, of object feature bin values, for identifying close matches between objects, such as text documents, that have numerous weighted features, such as specific-length word sequences. Predetermined feature weights get scaled with two or more selected adjacent scaling factors, and randomly rounded. The expanded set of weighted features of an object gets min-hashed into a predetermined number of feature bins. For each feature that qualifies to be inserted by min-hashing into a particular feature bin, and across successive feature bins, the expanded set of weighted features get min-hashed and circularly smeared into the predetermined number of feature bins. Completed pre-calculated sets of feature bin values for each scaling of the object, together with the scaling factor, are stored for use in comparing sampled features of the object with sampled features of other objects by calculating an estimated Jaccard similarity index.

Abstract: According to an implementation of the disclosure, a computing device may record substantially all the network traffic being transported over a first node of a network over a period of time. The computing device may receive an authenticated request from a forensics system that includes access criteria. The first computing device may determine a relevant encrypted and unencrypted portion of the network traffic based on the access criteria. Based on unencrypted portion, the computing device may recalculate an encryption key applicable to the encrypted portion. The computing device may then replicate the relevant portion and the encryption key to the forensics system for forensic analysis.

Abstract: The disclosed systems and methods include pre-calculation, per object, of object feature bin values, for identifying close matches between objects, such as text documents, that have numerous weighted features, such as specific-length word sequences. Predetermined feature weights get scaled with two or more selected adjacent scaling factors, and randomly rounded. The expanded set of weighted features of an object gets min-hashed into a predetermined number of feature bins. For each feature that qualifies to be inserted by min-hashing into a particular feature bin, and across successive feature bins, the expanded set of weighted features get min-hashed and circularly smeared into the predetermined number of feature bins. Completed pre-calculated sets of feature bin values for each scaling of the object, together with the scaling factor, are stored for use in comparing sampled features of the object with sampled features of other objects by calculating an estimated Jaccard similarity index.

Abstract: The disclosed systems and methods include pre-calculation, per object, of object feature bin values, for identifying close matches between objects, such as text documents, that have numerous weighted features, such as specific-length word sequences. Predetermined feature weights get scaled with two or more selected adjacent scaling factors, and randomly rounded. The expanded set of weighted features of an object gets min-hashed into a predetermined number of feature bins. For each feature that qualifies to be inserted by min-hashing into a particular feature bin, and across successive feature bins, the expanded set of weighted features get min-hashed and circularly smeared into the predetermined number of feature bins. Completed pre-calculated sets of feature bin values for each scaling of the object, together with the scaling factor, are stored for use in comparing sampled features of the object with sampled features of other objects by calculating an estimated Jaccard similarity index.

Abstract: According to an implementation of the disclosure, a computing device may record substantially all the network traffic being transported over a first node of a network over a period of time. The computing device may receive an authenticated request from a forensics system that includes access criteria. The first computing device may determine a relevant encrypted and unencrypted portion of the network traffic based on the access criteria. Based on unencrypted portion, the computing device may recalculate an encryption key applicable to the encrypted portion. The computing device may then replicate the relevant portion and the encryption key to the forensics system for forensic analysis.

Abstract: The technology disclosed includes access to content and encryption key rotation in a multi-generational file system that has a first tier file, and automatically initializes a second tier file accessible using a same path and file name as the first tier file. The disclosed technology includes copying forward blocks of data from the first tier file to the second tier file, and prior to completion of the copying forward, responding to an access request by accessing the second tier file by providing data available from the second tier file that has been copied forward and by following links associated with the holes to access blocks in the first tier file to provide data from the first tier file. The first tier files are encrypted using a first encryption key; and applying a second encryption key to encrypt data in the second tier files during the copying forward and write access.

Abstract: According to an implementation of the disclosure, a computing device may record substantially all the network traffic being transported over a first node of a network over a period of time. The computing device may receive an authenticated request from a forensics system that includes access criteria. The first computing device may determine a relevant encrypted and unencrypted portion of the network traffic based on the access criteria. Based on unencrypted portion, the computing device may recalculate an encryption key applicable to the encrypted portion. The computing device may then replicate the relevant portion and the encryption key to the forensics system for forensic analysis.

Abstract: Disclosed technology includes access to rotatable-key-encrypted content in a multi-tier disk partition system, with a first-tier-track, and initializing a second-tier-track accessible using the same block designator. A stack of bit vectors, stored in SSD memory, represents tier-tracks and a bit flag indicates whether a respective tier-track holds currently-active data or another bit vector needs to be consulted for access to a predecessor of the tier-track. Copying forward of data from the first-tier-track to the second-tier-track, as-scheduled or in response to an authorized write access to the second-tier-track includes, prior to completion, responding to an access request by providing data from the second-tier-track that has been copied forward and following mappings associated with the flag sets to provide data from the first-tier-track.

Abstract: A codeword is generated from a message. One or more anchor values are appended to the codeword at predetermined anchor positions. Before the codeword is stored in a memory block, the locations and values of stuck cells in the memory block are determined. Based on the values and positions of the stuck cells, the values of the codeword are remapped so that values of the codeword that are the same as the values of the stuck cells are placed at the positions of the stuck cells. The remapped codeword is stored in the memory block. When the message is later read, the original codeword can be recovered from the remapped codeword based on the locations of the anchor values in the remapped codeword.

Abstract: A codeword is generated from a message. One or more anchor values are appended to the codeword at predetermined anchor positions. Before the codeword is stored in a memory block, the locations and values of stuck cells in the memory block are determined. Based on the values and positions of the stuck cells, the values of the codeword are remapped so that values of the codeword that are the same as the values of the stuck cells are placed at the positions of the stuck cells. The remapped codeword is stored in the memory block. When the message is later read, the original codeword can be recovered from the remapped codeword based on the locations of the anchor values in the remapped codeword.

Abstract: A codeword is generated from a message. One or more anchor values are appended to the codeword at predetermined anchor positions. Before the codeword is stored in a memory block, the locations and values of stuck cells in the memory block are determined. Based on the values and positions of the stuck cells, the values of the codeword are remapped so that values of the codeword that are the same as the values of the stuck cells are placed at the positions of the stuck cells. The remapped codeword is stored in the memory block. When the message is later read, the original codeword can be recovered from the remapped codeword based on the locations of the anchor values in the remapped codeword.

Abstract: A codeword is generated from a message. One or more anchor values are appended to the codeword at predetermined anchor positions. Before the codeword is stored in a memory block, the locations and values of stuck cells in the memory block are determined. Based on the values and positions of the stuck cells, the values of the codeword are remapped so that values of the codeword that are the same as the values of the stuck cells are placed at the positions of the stuck cells. The remapped codeword is stored in the memory block. When the message is later read, the original codeword can be recovered from the remapped codeword based on the locations of the anchor values in the remapped codeword.

Abstract: Hash tables comprising load factors of up to and above 97% are disclosed. The hash tables may be associated with three or more hash functions, each hash function being applied to a key to identify a location in a hash table. The load factor of a hash table may be increased, obviating any need to increase the size of the hash table to accommodate more insertions. Such increase in load factor may be accomplished by a combination of increasing the number of cells per bucket in a hash table and increasing the number of hash functions associated with the hash table.

Abstract: An implementation of a disk drive with improved efficiency where a read head supported by a first positioning component is provided and a write head supported by a second positioning component is also provided. By positioning the write head behind the read head at a predetermined angle, the disk drive can execute a “read-before-write” or “read-modify-by-XOR-write ” operation by before the platter has rotated a full revolution.

Abstract: A probabilistic detector is utilized to query a database. Utilization of a probabilistic detector provides assurance with 100 per cent probability that a search expression in the query is not in the database index. The probabilistic detector is implemented in the form of a Bloom filter. The probabilistic detector is created by hashing expressions in the database index and mapping the resulting hash values into the probabilistic detector. Upon receiving a query, expressions of the query are hashed. The probabilistic detector is queried using these hash values. If the results of querying the probabilistic detector indicate that searched for information may be in the database, the database is not queried. If the results of querying the probabilistic detector indicate that the information may be in the database, the database is queried for the information using the original query. This technique is advantageous in mitigating detrimental effects of denial of service attacks.

Abstract: The vulnerable interval between the occurrence of a localized or spot failure and the occurrence of a detectable disk failure is reduced by providing redundancy within a single disk. Sectors of the disk may be grouped into independent sets. Error-correcting or erasure-correcting codes may be applied across groups of sectors where the maximum number of failures prior to detectable disk failure is expected to be small. It is desirable to place all sectors in adjacent tracks in different redundancy groups. This provides a lower bound on the number of redundancy groups needed.

Abstract: Nodal pattern configuration is described, including generating successive values at a source node, processing the successive values using a plurality of intermediate nodes, sending the processed values from a node in the plurality of intermediate nodes to a destination node, and configuring the plurality of intermediate nodes such that each node of the plurality of intermediate nodes, concurrently performs at least two actions. Also, nodal pattern configuration includes generating a series of data blocks at a source node, processing data blocks from the series of data blocks using a plurality of intermediate nodes in data communication with the source node, each node of the plurality of intermediate nodes being configured to concurrently perform at least two operations, and sending processed data blocks from the plurality of intermediate nodes to a destination node, the destination node being in data communication with the plurality of intermediate nodes.

Abstract: Evaluating content includes receiving content, analyzing the content for web spam using a content-based identification technique, and classifying the content according to the analysis. An index of analyzed contents may be created. A system for evaluating content includes a storage device configured to store data and a processor configured to analyze content using content-based identification techniques to determine whether web spam is present.