Abstract: A watermark encoding system encodes an audio signal with both a strong and a weak watermark. The strong watermark identifies the content producer and is designed to survive all typical kinds of processing and malicious attacks. The weak watermark identifies the content as an original and is designed to be significantly removed as a result of most normal signal processing (other than A/D and D/A). The watermark encoding system has a converter to convert an audio signal into frequency and phase components and a mask processor to determine a hearing threshold for corresponding frequency components. The watermark encoding system also has a pattern generator to generate both the strong and weak watermarks and a watermark insertion unit to selectively insert either the strong or weak watermark into the audio signal. The watermark insertion unit adds the strong watermark to the audio signal when the signal exceeds the hearing threshold by a buffer value (e.g.

Abstract: The described systems and methods described are directed at encoding randomly distributed features in an object. Randomly distributed features in an authentication object are determined. Data representing the randomly distributed features is compressed and encoded with a signature. A label is created and includes the authentication object and the encoded data. The data may be compressed by determining a probability density function associated with the authentication object. Vectors associated with the randomly distributed attributes are determined based, at least in part, on the probability density function. The vectors are encoded using an arithmetic coding algorithm.

Abstract: A method includes forming a feature vector associated with an iris of an individual using a transform operation including converting an iris image into a log-polar image, scaling one or more samples in the log-polar image according to a Fourier-Mellin transform, and performing a Fourier transform on the scaled samples. The method involves forming an iris digest based on the feature vector, and creating a biometric identifier based on the iris digest. A system includes an iris scanner, an iris analyzer that forms an image of a human iris wherein the presence of eyelashes in the image is minimized, forms a feature vector associated with the iris image using a modified Fourier-Mellin transform, and compresses the feature vector into an iris digest.

Abstract: Compressing program binaries with reduced compression ratios. One or several pre-processing acts are performed before performing compression using a local sequential correlation oriented compression technology such as PPM, or one of its variants or improvements. One pre-processing act splits the binaries into several substreams that have high local sequential correlation. Such splitting takes into consideration the correlation between common fields in different instructions as well as the correlation between different fields in the same instruction. Another pre-processing reschedules binary instructions to improve the degree of local sequential correlation without affecting dependencies between instructions. Yet another pre-processing act replaces common operation codes in the instruction with a symbols from a second alphabet, thereby distinguishing between operation codes that have a particular value, and other portions of the instruction that just happen to have the same value.

Abstract: Techniques are disclosed to enable utilization of randomly-occurring features of a label (whether embedded or naturally inherent) to provide counterfeit-resistant and/or tamper-resistant labels. More specifically, labels including randomly-occurring features are scanned to determine the labels' features. The information from the scan is utilized to provide identifying indicia which uniquely identifies each label and may be later verified against the label features that are present to determine whether the label is genuine. In a described implementation, the identifying indicia may be cryptographically signed.

Abstract: Compressing program binaries with reduced compression ratios. One or several pre-processing acts are performed before performing compression using a local sequential correlation oriented compression technology such as PPM, or one of its variants or improvements. One pre-processing act splits the binaries into several substreams that have high local sequential correlation. Such splitting takes into consideration the correlation between common fields in different instructions as well as the correlation between different fields in the same instruction. Another pre-processing reschedules binary instructions to improve the degree of local sequential correlation without affecting dependencies between instructions. Yet another pre-processing act replaces common operation codes in the instruction with a symbols from a second alphabet, thereby distinguishing between operation codes that have a particular value, and other portions of the instruction that just happen to have the same value.

Abstract: An implementation of a technology is described herein that facilitates rights enforcement of digital goods using watermarks. More particularly, it is a fingerprinting technology for protecting digital goods by detecting collusion as a malicious attack and identifying the participating colluders. If a digital pirate breaks one client and enables this client to avoid watermark detection, all content (both marked/protected an unmarked/free) can be played as unmarked only on that particular client. However, to enable other clients to play content as unmarked, the digital pirate needs to collude the extracted detection keys from many clients in order to create content that can evade watermark detection on all clients. The described implementation significantly improves collusion resistance through a fingerprinting mechanism that can identify the members of a malicious coalition even when their numbers are several orders of magnitude greater than what conventional collusion-protection schemes can accomplish.

Abstract: Described herein is a watermarking technology for protecting digital signals, such as a music clip. In another described implementation, a watermarking system employs a permutation technique to hide a watermark. The order in which data is imposed or encoded is rearranged may be based upon a permutation table. The same table may be used to reverse permute the data at the detector.

Abstract: Methods and apparatuses are provided for use with optical data storage media and related devices.

Abstract: Described herein is an audio watermarking technology for detecting watermarks in audio signals, such as a music clip. The watermark identifies the content producer, providing a signature that is embedded in the audio signal and cannot be removed. The watermark is designed to survive all typical kinds of processing and all types of malicious attacks that attempt to remove or modify the watermark from the signal. The implementations of the watermark detecting system, described herein, support quick, efficient, and accurate detection of watermarks by the specifically designed watermark detecting system. In one described implementation, a watermark detecting system employs an improved normalized covariance test to determine the presence of a watermark using less expensive materials (hardware), quicker calculations, and a more accurate test (than the original correlation test).

Abstract: Described herein is an audio watermarking technology for detecting watermarks in audio signals, such as a music clip. The watermark identifies the content producer, providing a signature that is embedded in the audio signal and cannot be removed. The watermark is designed to survive all typical kinds of processing and all types of malicious attacks that attempt to remove or modify the watermark from the signal. The implementations of the watermark detecting system, described herein, support quick, efficient, and accurate detection of watermarks by the specifically designed watermark detecting system. In one described implementation, a watermark detecting system employs an improved normalized covariance test to determine the presence of a watermark using less expensive materials (hardware), quicker calculations, and a more accurate test (than the original correlation test).

Abstract: Described herein is an audio watermarking technology for detecting watermarks in audio signals, such as a music clip. The watermark identifies the content producer, providing a signature that is embedded in the audio signal and cannot be removed. The watermark is designed to survive all typical kinds of processing and all types of malicious attacks that attempt to remove or modify the watermark from the signal. The implementations of the watermark detecting system, described herein, support quick, efficient, and accurate detection of watermarks by the specifically designed watermark detecting system. In one described implementation, a watermark detecting system employs an improved normalized covariance test to determine the presence of a watermark using less expensive materials (hardware), quicker calculations, and a more accurate test (than the original correlation test).

Abstract: An implementation of a technology is described herein that facilitates rights enforcement of digital goods using watermarks. More particularly, it is a fingerprinting technology for protecting digital goods by detecting collusion as a malicious attack and identifying the participating colluders. If a digital pirate breaks one client and enables this client to avoid watermark detection, all content (both marked/protected an unmarked/free) can be played as unmarked only on that particular client. However, to enable other clients to play content as unmarked, the digital pirate needs to collude the extracted detection keys from many clients in order to create content that can evade watermark detection on all clients. The described implementation significantly improves collusion resistance through a fingerprinting mechanism that can identify the members of a malicious coalition even when their numbers are several orders of magnitude greater than what conventional collusion-protection schemes can accomplish.

Abstract: An implementation of a technology is described herein that facilitates rights enforcement of digital goods using watermarks. More particularly, it is a fingerprinting technology for protecting digital goods by detecting collusion as a malicious attack and identifying the participating colluders. If a digital pirate breaks one client and enables this client to avoid watermark detection, all content (both marked/protected an unmarked/free) can be played as unmarked only on that particular client. However, to enable other clients to play content as unmarked, the digital pirate needs to collude the extracted detection keys from many clients in order to create content that can evade watermark detection on all clients. The described implementation significantly improves collusion resistance through a fingerprinting mechanism that can identify the members of a malicious coalition even when their numbers are several orders of magnitude greater than what conventional collusion-protection schemes can accomplish.

Abstract: An implementation of a technology is described herein that facilitates rights enforcement of digital goods using watermarks. More particularly, it is a fingerprinting technology for protecting digital goods by detecting collusion as a malicious attack and identifying the participating colluders. If a digital pirate breaks one client and enables this client to avoid watermark detection, all content (both marked/protected an unmarked/free) can be played as unmarked only on that particular client. However, to enable other clients to play content as unmarked, the digital pirate needs to collude the extracted detection keys from many clients in order to create content that can evade watermark detection on all clients. The described implementation significantly improves collusion resistance through a fingerprinting mechanism that can identify the members of a malicious coalition even when their numbers are several orders of magnitude greater than what conventional collusion-protection schemes can accomplish.

Abstract: An implementation of a technology is described herein that facilitates rights enforcement of digital goods using watermarks. More particularly, it is a fingerprinting technology for protecting digital goods by detecting collusion as a malicious attack and identifying the participating colluders. If a digital pirate breaks one client and enables this client to avoid watermark detection, all content (both marked/protected an unmarked/free) can be played as unmarked only on that particular client. However, to enable other clients to play content as unmarked, the digital pirate needs to collude the extracted detection keys from many clients in order to create content that can evade watermark detection on all clients. The described implementation significantly improves collusion resistance through a fingerprinting mechanism that can identify the members of a malicious coalition even when their numbers are several orders of magnitude greater than what conventional collusion-protection schemes can accomplish.

Abstract: A watermark encoding system encodes an audio signal with both a strong and a weak watermark. The strong watermark identifies the content producer and is designed to survive all typical kinds of processing and malicious attacks. The weak watermark identifies the content as an original and is designed to be significantly removed as a result of most normal signal processing (other than A/D and D/A). The watermark encoding system has a converter to convert an audio signal into frequency and phase components and a mask processor to determine a hearing threshold for corresponding frequency components. The watermark encoding system also has a pattern generator to generate both the strong and weak watermarks and a watermark insertion unit to selectively insert either the strong or weak watermark into the audio signal. The watermark insertion unit adds the strong watermark to the audio signal when the signal exceeds the hearing threshold by a buffer value (e.g.

Abstract: Described herein is audio watermarking technology for inserting and detecting watermarks in audio signals, such as a music clip. The watermark identifies the content producer, providing a signature that is embedded in the audio signal and cannot be removed. The watermark is designed to survive all typical kinds of processing and malicious attacks. In one described implementation, a watermarking system employs chess spread-spectrum sequences (i.e., “chess watermarks”) to improve the balance of positive and negative chips in the watermarking sequences. The balance is not imposed in an orderly fashion, which might make the watermark sequence more easily detectable to an attacker, but in a pseudo-random fashion. In that way, better sequence balance is achieved while preserving its randomness for an attacker without knowledge of the keys.

Abstract: One or more instructions of software being installed on a computing device are modified to embed a digital signature in the installed software. The installed software is stored on the computing device so that it can be executed on the computing device in a trusted mode if the signature is verified, and so that it can also be executed on the computing device without additional modification in a public mode where the signature is not verified.

Abstract: Described herein is an audio watermarking technology for detecting watermarks in audio signals, such as a music clip. The watermark identifies the content producer, providing a signature that is embedded in the audio signal and cannot be removed. The watermark is designed to survive all typical kinds of processing and all types of malicious attacks that attempt to remove or modify the watermark from the signal. The implementations of the watermark detecting system, described herein, support quick, efficient, and accurate detection of watermarks by the specifically designed watermark detecting system. In one described implementation, a watermark detecting system employs an improved normalized covariance test to determine the presence of a watermark using less expensive materials (hardware), quicker calculations, and a more accurate test (than the original correlation test).