PSG College of Technology

About: PSG College of Technology is a based out in . It is known for research contribution in the topics: Machining & Thin film. The organization has 3174 authors who have published 3575 publications receiving 40690 citations.

IoT Enabled RFID Authentication and Secure Object Tracking System for Smart Logistics

Abstract: Object tracking is a fundamental problem in Supply Chain Management (SCM). Recent innovations eliminate the difficulties in traditional approach such as manual counting, locating the object, and data management. Radio Frequency Identification (RFID) implementation in SCM improves the visibility of real-time object movement and provide solutions for anti-counterfeiting. RFID is a major prerequisite for the IoT, which connects physical objects to the Internet. Various research works have been carried out to perform object tracking using GPS, video cameras, and wifi technology. These methods just hope to see the actual object, but not the characteristic changes of the object due to environmental changes. After reviewing the implementation of latest technologies in object tracking system, it is expected that the security and privacy risks in large-scale IoT systems are to be eliminated and an efficient IoT services are provided to SCM. In this work, an architecture is proposed for a fine-grained IoT-enabled online object tracking system. Cloud storage used in this architecture enhances the scalability and data management. We propose a novel secure and efficient end to end authentication protocol that is based on a symmetric key cryptosystem and one-way hash function. A new scheme is also proposed to address object tracking communication flow which uses the secret key established in the authentication process. A formal security analysis method, GNY logic is used and proved that the proposed protocol achieves an end to end authentication. Tag/Reader impersonation attack and replay attack are prevented in the proposed scheme. It also preserves forward and backward secrecy. Performance analysis shows that the proposed protocol is not storage and computationally intensive.

Integration of Lean Six‐Sigma with ISO 9001:2008 standard

Abstract: Purpose – The purpose of this paper is to present a framework for integrating Lean Six Sigma DMAIC methodology and belt based training infrastructure with ISO 9001:2008 standard based Quality Management SystemDesign/methodology/approach – A new model called L6QMS 2008 has been developed from the process based quality management system model of ISO 9001:2008 standard based Quality Management System This model integrates the Lean Six Sigma requirements as appended additional sub‐clauses in the ISO 9001:2008 standardFindings – L6QMS 2008 aids an organization in implementing a Lean Six Sigma programme with minimum effort and expenditurePractical implications – Results of case studies illustrating the implementation of this integrated approach are presented in this research paperOriginality/value – This paper presents a unique approach of integrating the three main management models, namely Lean, Six Sigma and ISO 9001:2008 standard based Quality Management System, as a single framework benefiting contemp

Ultra-high capacity long-haul PDM-16-QAM-based WDM-FSO transmission system using coherent detection and digital signal processing

Abstract: The ever-increasing demand for wide channel bandwidth, high-speed information, and spectral-efficient communication links with advanced modulation schemes has led to the evolution of the free space optics (FSO) links. This paper proposes an FSO transmission link based on eight-channel wavelength division multiplexing technique integrating spectral-efficient polarization division multiplexing with a 16-level quadrature amplitude modulation (PDM-16-QAM) scheme, with each channel carrying 160 Gbps of information. The proposed link deploys coherent detection technique and the digital signal processing unit to boost the system efficiency and to compensate for the deterioration of the information signal due to channel fading, atmospheric attenuation and atmospheric turbulence. Using numerical simulations, we demonstrate an effective transmission of 1.28 Tbps data with FSO link range varying from 84 km to 1.95 km depending on the weather conditions with reasonable bit error rate results. We also scrutinize the output of the system with published works and demonstrate a better performance for the proposed FSO system i.e. bit rate and range. The proposed system can be implemented under complex atmospheric conditions to achieve a reliable high-speed transmission of information for fronthaul and backhaul links.

Network intrusion detection using feature selection and Decision tree classifier

Abstract: Security of computers and the networks that connect them is increasingly becoming of great significance. Machine learning techniques such as Decision trees have been applied to the field of intrusion detection. Machine learning techniques can learn normal and anomalous patterns from training data and generate classifiers that are used to detect attacks on computer system. In general the input to classifiers is in a high dimension feature space, but not all features are relevant to the classes to be classified. Feature selection is a very important step in classification since the inclusion of irrelevant and redundant features often degrade the performance of classification algorithms both in speed and accuracy. In this paper, we have considered three different approaches for feature selection, Chi square, Information Gain and ReliefF which is based on filter approach. A comparative study of the three approaches is done using decision tree as classifier. The KDDcup 99 data set is used to train and test the decision tree classifiers.