This publication specifies the Triple Data Encryption
Algorithm (TDEA), including its primary component cryptographic engine, the
Data Encryption Algorithm (DEA). TDEA may be used by federal organizations to protect sensitive unclassified data and is intended to be used with a Special
Publication (SP) 800-38-series-compliant mode of operation in a Federal
Information Processing Standard (FIPS) 140-2-compliant cryptographic module.
Protection of data during transmission or while in storage may be
necessary to maintain the confidentiality and integrity of the information
represented by the data. This Recommendation defines the mathematical steps
required to cryptographically protect data using TDEA and to subsequently
process such protected data. TDEA is made available for use by federal agencies
within the context of a total security program consisting of physical security
procedures, good information management practices, and computer system/network
access controls.
This
report documents NIST’s
execution of the Intelligence Advanced Research Projects Activity (IARPA) Face
Recognition Prize Challenge (FRPC) 2017. The (FRPC) was conducted to assess the
capability of contemporary face recognition algorithms to recognize faces in
photographs collected without tight quality constraints, e.g., non-ideal images
collected from individuals who are unaware of, and not cooperating with, the
collection. Such images are characterized by variations in head orientation,
facial expression, illumination, and occlusion and reduced resolution.
The
report describes and presents the results for text detection and recognition
(TRAIT) evaluation in support of forensic investigations of digital media.
These images are of interest to NIST’s partner law enforcement agencies that seek to employ text recognition
in investigating serious crime. Our first evaluation uses images
seized in child exploitation investigations. The primary application is the
identification of previously known victims and suspects, as well as detection
of new victims and suspects. The presence of text, for example, on a wall
poster or on an item of clothing, may allow a location to be identified and linked
to prior cases. In total, three groups took part in this evaluation over three
Phases. The evaluation results show that the initial performance of text
recognition is low. However, from Phase 1 to Phase 3, the performance of text
recognition algorithms has shown improvement.
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