Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disciplines; this reflects its broad appeal and usefulness as one of the steps in exploratory data analysis. However, clustering is a difficult problem combinatorially, and differences in assumptions and contexts in different communities has made the transfer of useful generic concepts and methodologies slow to occur. This paper presents an overview of pattern clustering methods from a statistical pattern recognition perspective, with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering practitioners. We present a taxonomy of clustering techniques, and identify cross-cutting themes and recent advances. We also describe some important applications of clustering algorithms such as image segmentation, object recognition, and information retrieval.

/pdf/data-clustering-a-review-4c452f5cab.pdf

Data clustering: a review

A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators

/pdf/handbook-of-fingerprint-recognition-16mh887j24.pdf

Handbook of Fingerprint Recognition

In order to ensure that the performance of an automatic fingerprint identification/verification system will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement algorithm in the minutiae extraction module. We present a fast fingerprint enhancement algorithm, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency. We have evaluated the performance of the image enhancement algorithm using the goodness index of the extracted minutiae and the accuracy of an online fingerprint verification system. Experimental results show that incorporating the enhancement algorithm improves both the goodness index and the verification accuracy.

/pdf/fingerprint-image-enhancement-algorithm-and-performance-405diava9j.pdf

Fingerprint image enhancement: algorithm and performance evaluation

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

IEEE Transactions on Pattern Analysis and Machine Intelligence

Smart cards play a very important and complimentary role in biometrics-based access control systems. While the most common application of the smart card in biometrics systems is as a platform for the secure storage of biometric data, matching on the smart card will enhance both the users privacy and the over all security of the system. However, the proprietary and non-standard smart card operating systems and development environments, make developing biometric matching on the card very difficult. Java Cards partially address this problem by ensuring inter-operability through the use of Java Virtual Machines (JVM). However, the use of an interpreted language like Java is not without a performance penalty and does not help biometric interoperability at the application level. The objective of this paper is to provide a synthesis of current smart card open standard development with respect to biometric applications. After introducing the current state of smart card open standards, we aim to highlight some of the more pertinent issues faced by biometric application developers. To aid this process we present two fingerprint-based applications for access control, both developed on an IBM JCOP31 smart card. The first example is our implementation of a storage-based fingerprint application using the contact-less interface available on the JCOP31. The second example is our implementation of a high performance, fingerprint-based match-on-card application using the new JC-BioAPI. We will conclude by presenting some performance figures that should help dispel the myth that Java Card biometric applications by nature have to be slow.

A JC-BioAPI compliant smart card with biometrics for secure access control

Face recognition systems, trained in controlled environment, often fail to efficiently match low resolution images with high resolution images. In this research, a co-transfer learning framework is proposed in which knowledge learnt in controlled high resolution environment is transferred for matching low resolution probe images with high resolution gallery. The proposed framework seamlessly combines transfer learning and co-training to perform knowledge transfer by updating classifier's decision boundary with low resolution probe instances. Experiments are performed on the CMU-Multi-PIE and SCface database with gallery images of size 72 × 72 and size of probe images varying from 48 × 48 to 16 × 16. The results show that, in terms of rank-1 identification accuracy, the proposed algorithm outperforms existing approaches by at least 5%.

Matching cross-resolution face images using co-transfer learning

A system and method for generating compact iris representations based on a database (502) of iris images includes providing full-length iris codes (504) for iris images in a database, where the full-length iris code includes a plurality of portions corresponding to circumferential rings in an associated iris image. Genuine and imposter score distributions are computed using a processor (512) for the full-length iris codes, and code portions (514) are identified that have a contribution that provides separation between imposter and genuine distributions relative to a threshold. A correlation between remaining code portions is measured. A subset of code portions having low correlations within the subset is generated to produce a compact iris representation.

System and method for generating and employing short length iris codes

In many areas in machine learning, decision trees play a crucial role in classification and regression. When a decision tree based classifier is hosted as a service in a critical application with the need for privacy protection of the service as well as the user data, fully homomorphic encrypted can be employed. However, a decision node in a decision tree can’t be directly implemented in FHE. In this paper, we describe an end-to-end approach to support privacyenhanced decision tree classification using IBM supported open-source library HELib. Using several options for building a decision node and employing oblivious computations coupled with an argmax function in FHE we show that a highly secure and trusted decision tree service can be enabled.

/pdf/privacy-enhanced-decision-tree-inference-1p1xnhre3g.pdf

Privacy Enhanced Decision Tree Inference

While significant advancements have been made in the field of multimedia forensics to detect altered content, existing techniques mostly focus on enabling the content recipient to verify the content integrity without any inputs from the content creator. In many application scenarios, the creator has a strong incentive to establish the provenance and integrity of the multimedia data created and released by him. Hence, there is a strong need for mechanisms that allow the content creator to prove the authenticity of the released content. Since blockchain technology provides an immutable distributed database, it is an ideal solution for reliably time-stamping content with its creation time and storing an irrefutable signature of the content at the time of its creation. However, a simple digital signature scheme does not allow modification of the content after the initial commitment. Authorized multimedia content alteration by its creator is often necessary (e.g., redaction of faces to protect the privacy of individuals in a video, redaction of sensitive fields in a text document) before the content is distributed. The main contributions of this paper are: (i) a novel sanitizable signature scheme that enables the content creator to prove the integrity of the redacted content, while preventing the recipients from reconstructing the redacted segments based on the published commitment, and (ii) a blockchain-based solution for securely managing the sanitizable signature. The proposed solution employs a robust hashing scheme using chameleon hash function and Merkle tree to generate the initial signature, which is stored on the blockchain. The auxiliary data required for the integrity verification step is retained by the content creator and only a signature of this auxiliary data is stored on the blockchain. Any modifications to the multimedia content requires only updating the signature of the auxiliary data, which is securely recorded on the blockchain. We demonstrate that the proposed approach enables verification of integrity of redacted multimedia content without compromising the content privacy requirements.

Nalini K. Ratha

Papers

A JC-BioAPI compliant smart card with biometrics for secure access control

Matching cross-resolution face images using co-transfer learning

System and method for generating and employing short length iris codes

Privacy Enhanced Decision Tree Inference

Proving Multimedia Integrity using Sanitizable Signatures Recorded on Blockchain