Abstract: Embodiments are directed towards encoding and transmitting data over a homogeneous network, heterogeneous network or without a network using secure sessions. An application generates a payload that includes information associated with the application and a another application. An encoding engine obtains a session bundle and the payload from the application. A message package that includes an encoded version of the payload such that the payload may be encoded based on the session bundle and the payload. The message package may be provided to the application. The application may select a communication facility to send the message package to the other application. The other application employs its communication facility to receive the message package from the application. The decoding engine may decode the message package based on a second session bundle. The decoding engine may provide the payload of the decoded message package to the other application.

Abstract: Embodiments are directed towards encoding and transmitting data over a homogeneous network, heterogeneous network or without a network using secure sessions. An application generates a payload that includes information associated with the application and a another application. An encoding engine obtains a session bundle and the payload from the application. A message package that includes an encoded version of the payload such that the payload may be encoded based on the session bundle and the payload. The message package may be provided to the application. The application may select a communication facility to send the message package to the other application. The other application employs its communication facility to receive the message package from the application. The decoding engine may decode the message package based on a second session bundle. The decoding engine may provide the payload of the decoded message package to the other application.

Abstract: Embodiments are directed to a searchable encryption model for fast indexing and searching of encoded documents. The encoded documents may have multiple encryption and/or compression layers applied. The model supports full or partial keywords and simple or complex queries. The index model may be based on prefix trees to optimize space and time complexities during indexing and searching. This index model can be used as the foundation to more complex search engines. Indexed documents may be tokenized and each token indexed in a prefix tree data structure, or trie index. Tokens in the index may be associated with a token catalog that includes information related to the documents that include the token. Token catalogs may be implemented as inverted indices that map tokens to documents. If a query is provided, a result set responsive to the query may be provided based on the token index and the token catalogs.

Abstract: Embodiments are directed to a searchable encryption model for fast indexing and searching of encoded documents. The encoded documents may have multiple encryption and/or compression layers applied. The model supports full or partial keywords and simple or complex queries. The index model may be based on prefix trees to optimize space and time complexities during indexing and searching. This index model can be used as the foundation to more complex search engines. Indexed documents may be tokenized and each token indexed in a prefix tree data structure, or trie index. Tokens in the index may be associated with a token catalog that includes information related to the documents that include the token. Token catalogs may be implemented as inverted indices that map tokens to documents. If a query is provided, a result set responsive to the query may be provided based on the token index and the token catalogs.

Abstract: Embodiments are directed towards efficient variable length encoding and decoding of numerical data sets using new interleaved start-step codes. The proposed codes minimize the space required to represent and store numerical values in data intensive applications. Efficient implementations are possible at higher processing speeds and reduced code size than current state-of-the-art codes. Encoding engines select one of a plurality of numerical values from an input stream. The encoding engines convert each numerical value into a codeword. Each codeword consists of a plurality of data bits interleaved with a group of control bits. The encoding engines provide each codeword to an encoded stream. Decoding engines select one of a plurality of codewords from an encoded stream. The decoding engines convert each codeword into a numerical value. The decoding engines provide each codeword to an output stream. Interleaved codes can add intrinsic value to Blockchain applications and the Internet of Things (IoT).

Abstract: Embodiments are directed to a secure MapReduce model for distributed processing and decoding of big data streams. An encoding engine may be employed to divide a data stream into equally sized segments. The segments may be encoded using a document key provided in a set of bundles. The bundles may contain encoded segment metadata, including the document key used to encode the stream. The document key and segment metadata may be encrypted using public key cryptography, and optionally included in the bundles. The encrypted bundles may be embedded into the encoded segments which may be provided to other network computers that include a decoding engine and an application engine. The encrypted bundles may be decrypted to obtain the document key for each encoded segment. The encoded segments may then be decrypted using the document key. And, each decoded segment may be provided to an application engine for further processing.

Abstract: Embodiments are directed towards a big data marker (BDM) model that provides label support, seeking, and decoding of arbitrary positions within small or large data streams. The features of the BDM model may be provided by a library having an easy-to-use application programming interface. The library may be considered an extension to existing data optimization and/or data encryption codecs that provides additional labeling and random access capabilities for encoding and decoding. The library enables labeling and seeking of single or multiple labels associated with various positions in a data stream, and allows encoding and decoding of full or partial streams. The library may be used with applications that already manage big data sets for archiving, logging, or backups. The library can also extend the capabilities of existing codecs by enabling the inclusion of labels and random access encoding/decoding via a common programming interface.

Abstract: Embodiments are directed towards managing data storage for secure storage of shared documents. A user or an application may provide data destined for encryption and a public key. Instruction set information that references at least a seed file that may be installed on the network computer may be generated. An encryption key based on the instruction set information may be generated. Header information that includes the instruction set may be generated. And, the header information may be encrypted using the public key. A secure bundle that includes the public key, the encrypted header information, and the encrypted data may be generated and provided to the user that provided the data and the public key or the application that provided the data and the public key. Decrypting the data included in the secure bundle the above actions are generally performed in reverse.

Abstract: Embodiments are directed towards managing data storage for secure storage of shared documents. A user or an application may provide data destined for encryption and a public key. Instruction set information that references at least a seed file that may be installed on the network computer may be generated. An encryption key based on the instruction set information may be generated. Header information that includes the instruction set may be generated. And, the header information may be encrypted using the public key. A secure bundle that includes the public key, the encrypted header information, and the encrypted data may be generated and provided to the user that provided the data and the public key or the application that provided the data and the public key. Decrypting the data included in the secure bundle the above actions are generally performed in reverse.

Abstract: Embodiments are directed towards managing data storage for secure storage of shared documents. A user or an application may provide data destined for encryption and a public key. Instruction set information that references at least a seed file that may be installed on the network computer may be generated. An encryption key based on the instruction set information may be generated. Header information that includes the instruction set may be generated. And, the header information may be encrypted using the public key. A secure bundle that includes the public key, the encrypted header information, and the encrypted data may be generated and provided to the user that provided the data and the public key or the application that provided the data and the public key. Decrypting the data included in the secure bundle the above actions are generally performed in reverse.

Abstract: Embodiments are directed toward transparent denial of service protection. Instruction set information that references a seed file may be communicated to a client computer. A network packet key may be generated based on the instruction set information or encrypted and provided by a server. A client computer may generate a client network packet key based on the instruction set information provided by the network computer and a seed file installed on the client computer. The client computer may include the client network packet key the one or more network packets that it is sending to the network computer before they are provided to the network computer. A packet rule that includes the network packet key may be generated and installed in a packet inspection engine. If network packets are received, the packet inspection engine compares the network packet key to the network packets using the packet rule.

Abstract: Embodiments compress and encrypt data in a single pass to reduce inefficiencies that occur from compression and encrypting data separately. Typically, compression and encryption are implemented in separate functional units. This has a few disadvantages: 1) encryption cannot make use of compression state to further secure the message, 2) processed data is read and written twice, 3) additional space, time, and resources are consumed, and 4) it is more prone to potential cipher-attacks since the encryption stage is independent from compression. Embodiments overcome these disadvantages by structuring these operations so that both compression and encryption is executed within the same processing loop. Thus: 1) encryption is stronger due to the dependence on the compression state, 2) I/O buffers are accessed only once reducing overhead, 3) system footprint is reduced, and 4) cipher analysis is more complex since the decryption process cannot be separated from the decompression process.

Abstract: Embodiments are directed towards managing data storage for secure storage of shared documents. A user or an application may provide data destined for encryption and a public key. Instruction set information that references at least a seed file that may be installed on the network computer may be generated. An encryption key based on the instruction set information may be generated. Header information that includes the instruction set may be generated. And, the header information may be encrypted using the public key. A secure bundle that includes the public key, the encrypted header information, and the encrypted data may be generated and provided to the user that provided the data and the public key or the application that provided the data and the public key. Decrypting the data included in the secure bundle the above actions are generally performed in reverse.

Abstract: Embodiments are directed toward transparent denial of service protection. Instruction set information that references a seed file may be communicated to a client computer. A network packet key may be generated based on the instruction set information or encrypted and provided by a server. A client computer may generate a client network packet key based on the instruction set information provided by the network computer and a seed file installed on the client computer. The client computer may include the client network packet key the one or more network packets that it is sending to the network computer before they are provided to the network computer. A packet rule that includes the network packet key may be generated and installed in a packet inspection engine. If network packets are received, the packet inspection engine compares the network packet key to the network packets using the packet rule.

Abstract: Embodiments are directed towards managing data storage for secure storage of shared documents. A user or an application may provide data destined for encryption and a public key. Instruction set information that references at least a seed file that may be installed on the network computer may be generated. An encryption key based on the instruction set information may be generated. Header information that includes the instruction set may be generated. And, the header information may be encrypted using the public key. A secure bundle that includes the public key, the encrypted header information, and the encrypted data may be generated and provided to the user that provided the data and the public key or the application that provided the data and the public key. Decrypting the data included in the secure bundle the above actions are generally performed in reverse.

Abstract: Embodiments are directed toward transparent denial of service protection. Instruction set information that references a seed file may be communicated to a client computer. A network packet key may be generated based on the instruction set information or encrypted and provided by a server. A client computer may generate a client network packet key based on the instruction set information provided by the network computer and a seed file installed on the client computer. The client computer may include the client network packet key the one or more network packets that it is sending to the network computer before they are provided to the network computer. A packet rule that includes the network packet key may be generated and installed in a packet inspection engine. If network packets are received, the packet inspection engine compares the network packet key to the network packets using the packet rule.

Abstract: Various embodiments are directed toward compressing and/or decompressing data communicated between one or more network devices (e.g., codec operations). In particular, embodiments are directed towards improving codec performance by seeding the computation workspace that may be used by various codec processors. The seeding data may be determined based on at least one characteristic of a particular codec and the characteristics of data that may be processed by the codec processor. Also, the codec processor may be employed to generate data for the codec workspace based on the determined seeding data. Workspace data may be generated by processing the seeding data with the same codec processor that is used for normal codec operations. The workspace generated from the seeding data may be stored for future use, such as, when a matched data stream arrives.

Abstract: Embodiments compress and encrypt data in a single pass to reduce inefficiencies that occur from compression and encrypting data separately. Typically, compression and encryption are implemented in separate functional units. This has a few disadvantages: 1) encryption cannot make use of compression state to further secure the message, 2) processed data is read and written twice, 3) additional space, time, and resources are consumed, and 4) it is more prone to potential cipher-attacks since the encryption stage is independent from compression. Embodiments overcome these disadvantages by structuring these operations so that both compression and encryption is executed within the same processing loop. Thus: 1) encryption is stronger due to the dependence on the compression state, 2) I/O buffers are accessed only once reducing overhead, 3) system footprint is reduced, and 4) cipher analysis is more complex since the decryption process cannot be separated from the decompression process.

Abstract: Various embodiments are directed toward compressing and/or decompressing data communicated between one or more network devices (e.g., codec operations). In particular, embodiments are directed towards improving codec performance by seeding the computation workspace that may be used by various codec processors. The seeding data may be determined based on at least one characteristic of a particular codec and the characteristics of data that may be processed by the codec processor. Also, the codec processor may be employed to generate data for the codec workspace based on the determined seeding data. Workspace data may be generated by processing the seeding data with the same codec processor that is used for normal codec operations. The workspace generated from the seeding data may be stored for future use, such as, when a matched data stream arrives.

Abstract: Embodiments compress and encrypt data in a single pass to reduce inefficiencies that occur from compression and encrypting data separately. Typically, compression and encryption are implemented in separate functional units. This has a few disadvantages: 1) encryption cannot make use of compression state to further secure the message, 2) processed data is read and written twice, 3) additional space, time, and resources are consumed, and 4) it is more prone to potential cipher-attacks since the encryption stage is independent from compression. Embodiments overcome these disadvantages by structuring these operations so that both compression and encryption is executed within the same processing loop. Thus: 1) encryption is stronger due to the dependence on the compression state, 2) I/O buffers are accessed only once reducing overhead, 3) system footprint is reduced, and 4) cipher analysis is more complex since the decryption process cannot be separated from the decompression process.