IRHDF: Iris Recognition using Hybrid Domain Features

Iris Biometric is a unique physiological noninvasive trait of human beings that remains stable over a person's life. In this paper, we propose an Iris Recognition using Hybrid Domain Features (IRHDF) as Dual Tree Complex Wavelet Transform (DTCWT) and Over Lapping Local Binary Pattern (OLBP). An eye is preprocessed to extract the complex wavelet features to obtain the Region of Interest (ROI) area from an iris. OLBP is further applied on ROI to generate features of magnitude coefficients. Resultant features are generated by fusion of DTCWT and OLBP using arithmetic addition. Euclidean Distance (ED) is used to match the test iris image with database iris features to recognize a person. We observe that the values of Equal Error Rate (EER) and Total Success Rate (TSR) are better than in [7]

WCTFR : WRAPPING CURVELET TRANSFORM BASED FACE RECOGNITION

The recognition of a person based on biological features are efficient compared with traditional knowledge based recognition system. In this paper we propose Wrapping Curvelet Transform based Face Recognition (WCTFR). The Wrapping Curvelet Transform (WCT) is applied on face images of database and test images to derive coefficients. The obtained coefficient matrix is rearranged to form WCT features of each image. The test image WCT features are compared with database images using Euclidean Distance (ED) to compute Equal Error Rate (EER) and True Success Rate (TSR). The proposed algorithm with WCT performs better than Curvelet Transform algorithms used in [1], [10] and [11]

IRDO: Iris Recognition by Fusion of DTCWT and OLBP

Iris Biometric is a physiological trait of human beings. In this paper, we propose Iris an Recognition using Fusion of Dual Tree Complex Wavelet Transform (DTCWT) and Over Lapping Local Binary Pattern (OLBP) Features. An eye is preprocessed to extract the iris part and obtain the Region of Interest (ROI) area from an iris. The complex wavelet features are extracted for region from the Iris DTCWT. OLBP is further applied on ROI to generate features of magnitude coefficients. The resultant features are generated by fusing DTCWT and OLBP using arithmetic addition. The Euclidean Distance (ED) is used to compare test iris with database iris features to identify a person. It is observed that the values of Total Success Rate (TSR) and Equal Error Rate (EER) are better in the case of proposed IRDO compared to the state-of-the art technique

OSPCV: Off-line Signature Verification using Principal Component Variances

Signature verification system is always the most sought after biometric verification system. Being a behavioral biometric feature which can always be imitated, the researcher faces a challenge in designing such a system, which has to counter intrapersonal and interpersonal variations. The paper presents a comprehensive way of off-line signature verification based on two features namely, the pixel density and the centre of gravity distance. The data processing consists of two parallel processes namely Signature training and Test signature analysis. Signature training involves extraction of features from the samples of database and Test signature analysis involves extraction of features from test signature and it’s comparison with those of trained values from database. The features are analyzed using Principal Component Analysis (PCA). The proposed work provides a feasible result and a notable improvement over the existing systems

HPAKE: Hybrid Precocious Authentication and Key Establishment in IoT

In Internet of Things (IoT), the objects of the physical world communicate with each other through the Sensor Devices via Internet connection. A large number of connected Devices frequently transmit small size data. Machine-to-Machine communication and the information obtained from the devices allow the automation of basic tasks in the Application services. Thus, a restriction of the low-powered devices in IoT and collecting a wide range of data lead to a challenge in designing an appropriate data networking and security. Authentication is the process of determining legitimate communication between the IoT devices. The proposed system, Hybrid Precocious Authentication and Key Establishment (HPAKE) Scheme uses a Hybrid model consisting of Hash Functions and Public Key Encryption along with a Nonce for Machine-to-Machine communication between the IoT devices. The HPAKE enhances the security

IR-FF-GSO: Image Retrieval using Feature Fusion and Glowworm Swarm Optimization

Image retrieval plays an important role in the Digital imaging and media such as image classification, photography, medical imaging etc., in which the obtained information is crucial for the analysis of images. Extraction of representative features is a challenge due to the variations in geometric, photometric image features. The feature fusion process affords compact discriminative features of an image; this crucial information requires in analysing images accurately to increase the accuracy. Hence, Image Retrieval using feature fusion and Glowworm Swarm Optimization (IR-FF-GSO) is proposed. Multiple features are extracted with Texture, Color, Statistical and Scale Invariant Feature Transform (SIFT) descriptors to perform retrieval process. Feature vector is fused using optimized weight value which is obtained from GSO algorithm. The proposed method yields 95.5% retrieval accuracy on ImageNet database and is

HSSM: High Speed Split Multiplier for Elliptic Curve Cryptography in IoT

Security of data in the Internet of Things (IoT) deals with Encryption to provide a stable secure system. The IoT device possess a constrained Main Memory and Secondary Memory that mandates the use of Elliptic Curve Cryptographic (ECC) scheme. The Scalar Multiplication has a great impact on the ECC implementations in reducing the Computation and Space Complexity, thereby enhancing the performance of an IoT System providing high Security and Privacy. The proposed High Speed Split Multiplier (HSSM) for ECC in IoT is a lightweight Multiplication technique that uses Split Multiplication with Pseudo-Mersenne Prime Number and Montgomery Curve to withstand the Power Analysis Attack. The proposed algorithm reduces the Computation Time and the Space Complexity of the Cryptographic operations in terms of Clock cycles and RAM when compared with Liu et al.,'s multiplication algorithms [1]

CKDAC: Cluster-Key Distribution and Access Control for Secure Communication in IoT

The Internet of Things (IoT) is a system of interconnected Smart Devices, Digital Machines, and Things that exchange data through Machine-to-Machine communication with minimal human mediation. The scalability of the IoT devices increases the degree of connectivity to share the Data and causes unidentified trap doors for any intruder to exploit. In the proposed system, Cluster-Key Distribution and Access Control (CKDAC) for secure communication in IoT uses Publication-Subscription architecture with the dynamic Cluster Head election to enhance the security and availability of the communicating IoT Devices. The proposed CKDAC reduces Time of Computation by decreasing the processing time of the re-keying operations when the IoT node enters or exits the Cluster using the Cryptographic algorithm in the Publication-Subscription model. CKDAC extends the availability by electing the Cluster Head with the

SIRLC: Secure information retrieval using lightweight cryptography in HIoT

Advances in new Communication and Information innovations has led to a new paradigm known as Internet of Things (IoT). Healthcare environment uses IoT technologies for Patients care which can be used in various medical applications. Patient information is encrypted consistently to maintain the access of therapeutic records by authoritative entities. Healthcare Internet of Things (HIoT) facilitate the access of Patient files immediately in emergency situations. In the proposed system, the Patient directly provides the Key to the Doctor in normal care access. In Emergency care, a Patient shares an Attribute based Key with a set of Emergency Supporting Representatives (ESRs) and access permission to the Doctor for utilizing Emergency key from ESR. The Doctor decrypts the medical records by using Attribute based key and Emergency key to save the Patient's life. The proposed model Secure Information Retrieval