Abstract

In recent years, high utility itemsets (HUIs) mining from the transactional databases becomes one of the most emerging research topic in the field of data mining due to its wide range of applications in online e-commerce data analysis, identifying interesting patterns in biomedical data and for cross marketing solutions in retail business. It aims to discover the itemsets with high utilities efficiently by considering item quantities in a transaction and profit values of each item. However, it produces a tremendous number of HUIs, which imposes further burden in analysis of the extracted patterns and also degrades the performance of mining methods. Mining the set of closed + high utility itemsets (CHUIs) solves this issue as it is a loss-less and condensed representation of all HUIs. In this paper, we aim to present a new algorithm for finding CHUIs from a transactional database, called the CHUM (Closed + High Utility itemset Miner), which is scalable and efficient. The proposed mining algorithm adopts a tricky aimed vertical representation of the database in order to speed up the execution time in generating itemset closures and compute their utility information without accessing the database. The proposed method makes use of the item co-occurrences strategy in order to further reduce the number of intersections needed to be performed. Several experiments are conducted on various sparse and dense datasets and the simulation results clearly show the scalability and superior performance of our algorithm as compared to those for the existing state-of-the-art CHUD (Closed + High Utility itemset Discovery) algorithm.

Abstract

Due to the rapid development of wireless communication systems, authentication becomes a key security component in smart grid environments. Authentication then plays an important role in the smart grid domain by providing a variety of security services including credentials' privacy, session-key (SK) security, and secure mutual authentication. In this paper, we analyze the security of a recent relevant work in smart grid, and it is unfortunately not able to deal with SK-security and smart meter secret credentials' privacy under the widely accepted Canetti-Krawczyk adversary (CK-adversary) model. We then propose a new efficient provably secure authenticated key agreement scheme for smart grid. Through the rigorous formal security analysis, we show that the proposed scheme achieves the well-known security functionalities including smart meter credentials' privacy and SK-security under the CK-adversary model. The proposed scheme reduces the computation overheads for both smart meters and service providers. Furthermore, the proposed scheme offers more security functionalities as compared to the existing related schemes.

Abstract

A wireless medical sensor network (WMSN) is a professional application of the traditional wireless body area sensor networks in medicine. Using WMSNs, the parameters of patients’ vital signs can be gathered from the sensor nodes deployed on the body of the patients and accessed by the healthcare professionals by using a mobile device. Due to wireless communication, securing communication becomes a vital issue in WMSNs. Since the vital signs parameters are sensitive to the patients’ health status and these information must not be revealed to the others except the healthcare professionals, the protection of patients’ privacy becomes another key issue for WMSNs applications. Thus, user authentication with anonymity property is the most basic and commonly used method in order to resolve the security and privacy issues of WMSNs. He et al. presented a user authentication protocol for healthcare applications using WMSNs to protect the security and privacy problems. However, Li et al. showed that their scheme is incorrect in authentication and session key agreement phase, has no wrong password detection mechanism and is vulnerable to denial of service caused by password change with wrong password. In this paper, we review Li et al.’s scheme and show that their scheme is still vulnerable to privileged-insider attack, sensor node capture attack and fails to provide user anonymity property. Moreover, we find that He et al.’s scheme is still vulnerable to the same attacks as we find out in Li et al.’s scheme. In order to remedy the security weak-nesses found in both He et al.’s scheme and Li et al.’s scheme, we present a secure biometrics-based user authentication scheme in WMSNs using smart card. Through the rigorous formal and informal security analysis, we show that our scheme is secure against possible known attacks. In addition, we simulate our scheme using the most-widely accepted and used Automated Validation of Internet Security Protocols and Application stool and the simulation results reveal that our scheme is secure. Our scheme is also efficient in computation and communication as compared to He et al.’s scheme, Li et al.’sscheme and other related schemes.

Abstract

Authentication protocol plays an important role in the short-range wireless communications for the Near Field Communication (NFC) technology. Due to the shared nature of wireless communication networks, there are several kinds of security vulnerabilities. Recently, a pseudonym-based NFC protocol (PBNFCP) has been proposed to withstand the security pitfalls found in the existing conditional privacy preserving security protocol (CPPNFC). However, this paper further analyzes PBNFCP and shows that it still fails to prevent the claimed security properties, such as impersonation attacks against an adversary, who is a malicious registered user having a valid pseudonym and corresponding private key. In order to overcome these security drawbacks, this paper proposes a secure and efficient authentication protocol (SEAP) for NFC applications using lifetime-based pseudonyms. The proposed SEAP is simulated for the formal security verification using the widely-accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool. The simulation results show that SEAP is secure. The rigorous security and performance analysis shows that the proposed SEAP is secure and efficient as compared to the related existing authentication protocols for NFC applications.

Abstract

The widespread popularity of the computer networks has triggered concerns about information security. Password-based user authentication with key agreement protocols have drawn attentions since it provides proper authentication of a user before granting access right to services, and then ensure secure communication over insecure channels. Recently, Lee et al. pointed out different security flaws on Tsaur et al.’s multi-server user authentication protocol, and they further proposed an extended chaotic maps-based user authentication with key agreement protocol for multi-server environments. However, we observed that Lee et al.’s protocol has some functionality and security flaws, i.e., it is inefficient in detection of unauthorized login and it does not support password change mechanism. Besides, their protocol is vulnerable to registration center spoofing attack and server spoofing attack. In order to remedy the aforementioned flaws, we proposed a novel chaotic maps-based user authentication with key agreement protocol for multi-server environments. The proposed protocol is provably secure in the random oracle model under the chaotic-maps based computational Diffie-Hellman assumption. In addition, we analyzed our protocol using BAN logic model. We also compared our protocol with Lee et al.’s protocol in aspects of computation cost, functionalities and securities.

Abstract

Transgender face recognition is gaining increasing attention in the face recognition community because ofits potential in real life applications. Despite extensive progress in traditional face recognition domain, it is very challenging to recognize faces under transgender setting.The gender transformation results in significant face variations, both in shape and texture gradually over time. This introduces additional complexities to existing face recognition algorithms to achieve a reliable performance. In this paper, we present a novel framework that incorporates appearance factor and a transformation factor caused due to Hormone Replacement Therapy (HRT) for recognition.To this extent, we employ the Hidden Factor Analysis(HFA) to jointly model a face under therapy as a linear combination of appearance and transformation factors.This is based on the intuition that the appearance factor captures the features that are unaffected by the therapy and transformation factor captures the feature changes due to therapy. Extensive experiments carried out on publicly available HRT transgender face database shows the efficacy of the proposed scheme with a recognition accuracy of82.36%

Abstract

Egocentric videos are characterized by their ability to have the first person view. With the popularity of Google Glass and GoPro, use of egocentric videos is on the rise. With the substantial increase in the number of egocentric videos, the value and utility of recognizing actions of the wearer in such videos has also thus increased. Unstructured movement of the camera due to natural head motion of the wearer causes sharp changes in the visual field of the egocentric camera causing many standard third person action recognition techniques to perform poorly on such videos. Objects present in the scene and hand gestures of the wearer are the most important cues for first person action recognition but are difficult to segment and recognize in an egocentric video. We propose a novel representation of the first person actions derived from feature trajectories. The features are simple to compute using standard point tracking and do not assume segmentation of hand/objects or recognizing object or hand pose unlike in many previous approaches. We train a bag of words classifier with the proposed features and report a performance improvement of more than 11% on publicly available datasets. Although not designed for the particular case, we show that our technique can also recognize wearer's actions when hands or objects are not visible.

Abstract

Facial fiducial detection is a challenging problem for several reasons like varying pose, appearance, expression, partial occlusion and others. In the past, several approaches like mixture of trees [32], regression based methods [8], exemplar based methods [7] have been proposed to tackle this challenge. In this paper, we propose an exemplar based approach to select the best solution from among outputs of regression and mixture of trees based algorithms (which we call candidate algorithms). We show that by using a very simple SIFT and HOG based descriptor, it is possible to identify the most accurate fiducial outputs from a set of results produced by candidate algorithms on any given test image. Our approach manifests as two algorithms, one based on optimizing an objective function with quadratic terms and the other based on simple kNN. Both algorithms take as input fiducial locations produced by running state-of-the-art candidate algorithms on an input image, and output accurate fiducials using a set of automatically selected exemplar images with annotations. Our surprising result is that in this case, a simple algorithm like kNN is able to take advantage of the seemingly huge complementarity of these candidate algorithms, better than optimization based algorithms. We do extensive experiments on several datasets, and show that our approach outperforms state-of-the-art consistently. In some cases, we report as much as a 10% improvement in accuracy. We also extensively analyze each component of our approach, to illustrate its efficacy. An implementation and extended technical report of our approach is available www.sites.google.com/site/wacv2016facefiducialexemplars.

Abstract

The primary objective of a robot is to substitute or complement humans in life-endangering situations. The paper deals with the design and analysis of a robot suitable for such Urban Search and Rescue operation (USAR) scenarios. A survey of the existing robots in this field is done and new design considerations have been developed. Further, quasi-static analysis of the robot along a circular stair is performed to confirm whether the design considerations will satisfy versatility as well as mobility, the key requirements of a true uneven terrain robot. Keywords— Compliant Design; Multi-module robot; Nonlinear optimization; 3D Quasi Static Model

Abstract

The purpose of this paper is to present the model of a Humanoid robot inspired by Poppy, modified for heavier load capacity and the balancing of humanoid in multiple work environments. The design has been modified in order to use MX-64 servos with more torque capacity than MX-28 servos which were used in original design. We have also redesigned the ankle joint and feet to make it a more accurate human like model. We are using an integrated approach using zero moment point (ZMP) with force sensing resistor (FSR) and center of mass (CoM) to find balance margins of the robot. Balancing and forward bending experiments on robot are conducted by providing some basic motion to the robot and ensuring that the robot is balanced and moving within safe margins using this approach.