6 research outputs found
An improved Genetic Optimized Neural Network for Multimodal Biometrics
23-30In
this paper, a novel classification technique for multimodal biometric system
based on fingerprint and palmprint is proposed. The problems faced in unimodal
biometric system such as noisy data, intra class variations, restricted degrees
of freedom, non-universality, spoof attacks, and unacceptable error rates are
overcome in multimodal biometric system by integrating the evidence presented
by multiple traits. It is proposed to fuse the features of the fingerprint with
palmprint images. Features are
extracted
using Gabor filter and Discrete Cosine Transform (DCT). The extracted feature
vectors were classified using an improved Partial Recurrent Neural Network with
genetic optimization. The proposed Momentum Optimized Genetic Partial
Recurrent Neural Network (MOG-PRNN) was evaluated
using a publicly available dataset and features obtained from live dataset. The
experimental results obtained show an average classification accuracy of 98.6%
with different datasets.</span
Cross –Layer Intrusion Detection System for Wireless Sensor Networks
213-220In Wireless
Sensor Network, the sensor nodes monitor any abnormal events occurring around
the business environment to report the emergency alert whenever it detects any
abnormality in an environment or report the monitored data continuously or
periodically to the base station. These emergency alerts can be stolen or
modified by the attackers or in some cases, the sensor nodes can be physically
compromised by the attackers, which lead to an unsafe environment. To avoid
these problems, Intrusion Detection System is implemented at the base station
to filter the abnormal data mostly related to the attacks of network layer. But
this paper proposes a novel cross layer rule based intrusion detection system
to detect the attacks coming from different layers in Wireless Sensor Networks.
The method analyzed several detection rules for Physical, MAC, Network and
Application layer attacks. The implementation is done using the rules
identified from the IDS techniques available for Wireless Sensor Network. The
experimental result shows the detection rate of different attacks on different
layers. The performance of cross layer IDS are shown in the graph by making the
comparison between the detection rates of various IDS techniques
Contactless Palm Vein Authentication security technique for better adoption of e-commerce in developing countries
E-commerce has been contributing immensely to the economic development of the developed countries and the main catalyst to this could be attributed to the total adoption of e-commerce by the citizens. In order word, e-commerce could also be an economic driver in developing countries. Moreover, security has been identified as major barrier that prevents citizens from adopting e-commerce in developing countries. This paper examines Security Authentication Techniques (SAT) of Digital Signature (DF) and Fingerprint System (FPS) the limitations of these architectures and then propose Contactless Palm Vein Authentication (CPVA). The architecture of this new CPVA will be discussed in relation to Security, privacy, trust and reliability