Abstract: Processing of masked data using table lookups is described. A mask is applied to input data to generate masked input data. The mask and the masked input data are used in combination to locate an entry in a lookup table. The entry corresponds to a transformed version of the input data.

Abstract: Systems and methods for effectively protecting data against differential fault analysis involved in Rivest, Shamir, and Adleman (“RSA”) cryptography using the Chinese Remainder Theorem (“CRT”) are described herein. A CRT RSA component facilitates modular exponentiation of a received message, and a verification component reconstructs the received message. An exponentiation component performs a first modular exponentiation and a second modular exponentiation of the received message. A recombination component performs a recombination step utilizing CRT computation as a function of the first and second modular exponentiations. A modular exponentiation component performs first and second public exponent derivations as a function of a private exponent. The verification component can reconstructs the received message as a function of the first and second public exponent derivations. The verification component calculates the received message utilizing Chinese Remainder Theorem computation.

Abstract: Processing of masked data using multiple lookup tables (LUTs), or sub-tables, is described. For each input value, an appropriate sub-table provides an output value that is the result of a non-linear transformation (e.g., byte substitution) applied to the input value. An additive mask can be applied to the input data. A transformation can be applied to the masked input data to transform the additive mask into a multiplicative-additive mask. Selected bits of the masked input data and the bits in the additive component of the multiplicative-additive mask can be used in combination to select one of the sub-tables. An entry in the selected sub-table, corresponding to a transformed version of the input data, can then be identified.

Abstract: Systems and/or methods that facilitate secure electronic communication of data are presented. A cryptographic component facilitates data encryption, data decryption, and/or generation of digital signatures, associated with messages. The cryptographic component includes a randomized exponentiation component that facilitates decryption of data and/or generation of digital signatures by exponentiating exponents associated with messages. A random number is generated and utilized to randomize the value of a message. After an exponentiation is performed on the randomized message value, intermediate results can be analyzed to determine if there was error in the exponentiation. If there was no error in the exponentiation, a final value of the exponentiation is determined and provided as output as decrypted data or a digital signature; if there is error, an “error” output can be provided.

Abstract: Processing of masked data using multiple lookup tables (LUTs), or sub-tables, is described. For each input value, an appropriate sub-table provides an output value that is the result of a non-linear transformation (e.g., byte substitution) applied to the input value. An additive mask can be applied to the input data. A transformation can be applied to the masked input data to transform the additive mask into a multiplicative-additive mask. Selected bits of the masked input data and the bits in the additive component of the multiplicative-additive mask can be used in combination to select one of the sub-tables. An entry in the selected sub-table, corresponding to a transformed version of the input data, can then be identified.

Abstract: Processing of masked data using multiple lookup tables (LUTs), or sub-tables, is described. For each input value, an appropriate sub-table provides an output value that is the result of a non-linear transformation (e.g., byte substitution) applied to the input value. An additive mask can be applied to the input data. A transformation can be applied to the masked input data to transform the additive mask into a multiplicative-additive mask. Selected bits of the masked input data and the bits in the additive component of the multiplicative-additive mask can be used in combination to select one of the sub-tables. An entry in the selected sub-table, corresponding to a transformed version of the input data, can then be identified.

Abstract: Systems and methods for effectively protecting data against differential fault analysis involved in Rivest, Shamir, and Adleman (“RSA”) cryptography using the Chinese Remainder Theorem (“CRT”) are described herein. A CRT RSA component facilitates modular exponentiation of a received message, and a verification component reconstructs the received message. An exponentiation component performs a first modular exponentiation and a second modular exponentiation of the received message. A recombination component performs a recombination step utilizing CRT computation as a function of the first and second modular exponentiations. A modular exponentiation component performs first and second public exponent derivations as a function of a private exponent. The verification component can reconstructs the received message as a function of the first and second public exponent derivations. The verification component calculates the received message utilizing Chinese Remainder Theorem computation.

Abstract: Processing of masked data using multiple lookup tables (LUTs), or sub-tables, is described. For each input value, an appropriate sub-table provides an output value that is the result of a non-linear transformation (e.g., byte substitution) applied to the input value. An additive mask can be applied to the input data. A transformation can be applied to the masked input data to transform the additive mask into a multiplicative-additive mask. Selected bits of the masked input data and the bits in the additive component of the multiplicative-additive mask can be used in combination to select one of the sub-tables. An entry in the selected sub-table, corresponding to a transformed version of the input data, can then be identified.