Computing on Encrypted Data Searching and Reporting: Cryptographic protocols that support searching and reporting on encrypted data – any information about the plaintext not deducible from the search criteria are guaranteed to be hidden. Fully Homomorphic Encryption: Cryptographic protocols that support operations on the underlying plaintext of an encryption – any information about the plaintext is guaranteed to be hidden. Secure Data Aggregation: Aggregating data without compromising privacy. Key Management Provenance End-point Input Validation: Mechanism to validate whether input data is coming from an authenticated source, such as digital signatures. Syntactic: Validation at a syntactic level. Semantic: Semantic validation is an important concern. Generally, semantic validation would validate typical business rules such as a due date. This capability can extend to the relationship of the particular file format and that the constructs which may be based on a standard can have a variance that may poise a denial of service in the form of a lockup of an application. This may also be observed even when using data translators which may not recognize the particular variant. Protocols and data formats may be altered by a vendor using reserved data field for example that will allow their products to have capabilities that differentiate their products from other products. This may also appears in differences in versions of systems for consumer devices, such as mobile devices such as cell phones. The semantic of a message and the data that is to be transported should be validated to assure at minimum conformant with standards. The use of digital signatures will be important to provide assurance that the data has been verified using a validator or data checker. This may be important to provide assurance that data from a sensor or from the data provider. This capability is important particularly if the data is to be Transformed or in the Curation of the data. If that data fails to meet the requirements it may be discarded and if that data continues to present a problem the source may be restricted in its ability to submit the data. These types of errors would be logged and prevented from being able to be disseminated to consumers. The Big Data system is a special case where use of digital signatures will be very important.
Computing on Encrypted Data Searching and Reporting: Cryptographic protocols that support searching and reporting on encrypted data – any information about the plaintext not deducible from the search criteria are guaranteed to be hidden. Fully Homomorphic Encryption: Cryptographic protocols that support operations on the underlying plaintext of an encryption – any information about the plaintext is guaranteed to be hidden. Secure Data Aggregation: Aggregating data without compromising privacy. Key Management Provenance End-point Input Validation: Mechanism to validate whether input data is coming from an authenticated source, such as digital signatures. Syntactic: Validation at a syntactic level. Semantic: Semantic validation is an important concern. Generally, semantic validation would validate typical business rules such as a due date. This capability can extend to the relationship of the particular file format and that the constructs which may be based on a standard can have a variance that may poise a denial of service in the form of a lockup of an application. This may also be observed even when using data translators which may not recognize the particular variant. Protocols and data formats may be altered by a vendor using reserved data field for example that will allow their products to have capabilities that differentiate their products from other products. This may also appears in differences in versions of systems for consumer devices, such as mobile devices such as cell phones. The semantic of a message and the data that is to be transported should be validated to assure at minimum conformant with standards. The use of digital signatures will be important to provide assurance that the data has been verified using a validator or data checker. This may be important to provide assurance that data from a sensor or from the data provider. This capability is important particularly if the data is to be Transformed or in the Curation of the data. If that data fails to meet the requirements it may be discarded and if that data continues to present a problem the source may be restricted in its ability to submit the data. These types of errors would be logged and prevented from being able to be disseminated to consumers. The Big Data system is a special case where use of digital signatures will be very important.