The Experts below are selected from a list of 4419 Experts worldwide ranked by ideXlab platform
Eric Zimmerman - One of the best experts on this subject based on the ideXlab platform.
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the xwf internal Hash Database and the registry viewer
X-Ways Forensics Practitioner’s Guide, 2014Co-Authors: Brett Shavers, Eric ZimmermanAbstract:This chapter details using Hash sets to identify, compare, and optionally hide files based on known Hash values. You can save a considerable amount of time when thorough Hash sets are available for certain types of investigations. X-Ways Forensics (XWF) contains robust Hashing capabilities that allow for quickly finding items of interest or eliminating nonpertinent files in a case. There is virtually no limit to the number of individual Hash sets that you can create in XWF.
Brett Shavers - One of the best experts on this subject based on the ideXlab platform.
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the xwf internal Hash Database and the registry viewer
X-Ways Forensics Practitioner’s Guide, 2014Co-Authors: Brett Shavers, Eric ZimmermanAbstract:This chapter details using Hash sets to identify, compare, and optionally hide files based on known Hash values. You can save a considerable amount of time when thorough Hash sets are available for certain types of investigations. X-Ways Forensics (XWF) contains robust Hashing capabilities that allow for quickly finding items of interest or eliminating nonpertinent files in a case. There is virtually no limit to the number of individual Hash sets that you can create in XWF.
Harley R Myler - One of the best experts on this subject based on the ideXlab platform.
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parallel algorithm for target recognition using a multiclass Hash Database
Proceedings of SPIE, 1998Co-Authors: Mosleh Uddin, Harley R MylerAbstract:A method for recognition of unknown targets using large Databases of model targets is discussed. Our approach is based on parallel processing of multi-class Hash Databases that are generated off-line. A geometric Hashing technique is used on feature points of model targets to create each class Database. Bit level coding is then performed to represent the models in an image format. Parallelism is achieved during the recognition phase. Feature points of an unknown target are passed to parallel processors each accessing an individual class Database. Each processor reads a particular class of Hash data base and indexes feature points of the unknown target. A simple voting technique is applied to determine the best match model with the unknown. The paper discusses our technique and the results from testing with unknown FLIR targets.
M B Srinivas - One of the best experts on this subject based on the ideXlab platform.
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inspire db intelligent networks sensor processing of information using resilient encoded Hash Database
International Conference on Sensor Technologies and Applications, 2010Co-Authors: Vasanth Iyer, S S Iyengar, Garmiela Rama Murthy, Kannan Srinathan, Vir V Phoha, M B SrinivasAbstract:Sensor networks consist of small motes attached with sensors to measure ambient parameters like temperature, humidity and light. As these motes are unreliable due to wireless link quality and also the data measuring sensors cannot be calibrated accurately for a given applications need. The unique data fusion needs are that parameter being measured is distributed across the network and needs to be computed reliably and with minimum overhead and redundancy due to data value being correlated. We show the asymptotic complexity of topology control when applied to power-aware routing is scalable and argue that the accuracy and reliability of the estimated sensor values can be accurately predicted for the physical value being sensed and aggregating. A prefixbased routing protocol is used for data-centric storage, which allows querying distributed parameters using a KEY, VALUE pairs without the need of the sensor node to know its exact geographic information. Intelligent sensor information processing, which is driven by these requirements, is discussed under the framework INSPIRE-DB.
Chunshien Lu - One of the best experts on this subject based on the ideXlab platform.
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geometric distortion resilient image Hashing scheme and its applications on copy detection and authentication
Multimedia Systems, 2005Co-Authors: Chunshien LuAbstract:Media Hashing is an alternative approach to many applications previously accomplished with watermarking. The major disadvantage of the existing media Hashing technologies is their limited resistance to geometric attacks. In this paper, a novel geometric distortion-invariant image Hashing scheme, which can be employed to perform copy detection and content authentication of digital images, is proposed. Our major contributions are threefold: (i) a mesh-based robust Hashing function is proposed; (ii) a sophisticated Hash Database for error-resilient and fast matching is constructed; and (iii) the application scalability of our scheme for content copy tracing and authentication is studied. In addition, we further investigate several media Hashing issues, including robustness and discrimination, error analysis, and complexity, with respect to the proposed image Hashing system. Exhaustive experimental results obtained from benchmark attacks confirm the excellent performance of the proposed method.
