Browsing by Author "Singh, I."
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Item A random key generation scheme using primitive polynomials over GF(2)(Springer Verlag service@springer.de, 2016) Singh, I.; Pais, A.R.A new key generation algorithm is proposed using primitive polynomials over Glaois Field GF(2). In this approach, we have used MD5 algorithm to digest the system time and IP address of the system. The combination of these digest values acts as random seed for the key generation process. The randomness test for the generated key is performed by using Blum Blum Shub (BBS), Micali-Schnorr and Mersenne Twister (MT19937) PRNG algorithms. The generated key has been compared on the basis of the combination of 2 bit, 3 bit, 4 bit and 8 bit count values of 0’s and 1’s. In this paper, we have used chi squared test, R squared test and standard deviation to check the randomness of the generated key. We have analyzed our result based on the above three criteria and observed that the proposed algorithm achieves lower dispersion in 72.5% of the test cases, lower error rate in 61.6% of the test cases and higher fitness value in 68.3% of the test cases. © Springer Nature Singapore Pte Ltd. 2016.Item Classification of punjabi folk musical instruments based on acoustic features(2017) Singh, I.; Koolagudi, S.G.Automatic musical instrument classification can be achieved using various features extracted such as pitch, skewness, energy, etc., from extensive number of musical database. Various feature extractionmethods have already been employed to represent data set. The crucial step in the feature extraction process is to find the best features that represent the appropriate characteristics of data set suitable for classification. This paper focuses on classification of Punjabi folk musical instruments from their audio segments. Five Punjabi folk musical instruments are considered for study. Twelve acoustic features such as entropy, kurtosis, brightness, event density, etc., including pitch are used to characterize eachmusical instrument from 150 songs. J48 classifier is used for the classification. Using the acoustic features, recognition accuracy of 91% is achieved. � Springer Science+Business Media Singapore 2017.Item Classification of punjabi folk musical instruments based on acoustic features(Springer Verlag service@springer.de, 2017) Singh, I.; Koolagudi, S.G.Automatic musical instrument classification can be achieved using various features extracted such as pitch, skewness, energy, etc., from extensive number of musical database. Various feature extractionmethods have already been employed to represent data set. The crucial step in the feature extraction process is to find the best features that represent the appropriate characteristics of data set suitable for classification. This paper focuses on classification of Punjabi folk musical instruments from their audio segments. Five Punjabi folk musical instruments are considered for study. Twelve acoustic features such as entropy, kurtosis, brightness, event density, etc., including pitch are used to characterize eachmusical instrument from 150 songs. J48 classifier is used for the classification. Using the acoustic features, recognition accuracy of 91% is achieved. © Springer Science+Business Media Singapore 2017.Item Lightweight and Homomorphic Security Protocols for IoT(Springer, 2023) Singh, I.; Jain, A.; Dhody, I.S.; Chandavarkar, B.R.The rise in usage of IoT devices for data collection in various fields has been astronomical in recent times. There has been an increased requirement to process the collected data on various cloud providers as IoT devices are compute-constrained. However, online data processing presents a substantial security challenge, especially in sensitive data, such as finance and medicine. The motivation behind this chapter comes from the observation that the encryption algorithms used for IoT devices need to be lightweight because IoT devices are not capable of heavy computation and the algorithm must be homomorphic. This is important because when the encrypted data moves from the device’s private environment to the public network, the data integrity is a major factor for such sensors and measurement devices. In this way, the data never needs to be in its decrypted form outside the organization’s ecosystem. This chapter aims to first present the limitations of IoT devices in the context of IoT networks. Then, the chapter analyses some of the most popular security protocols for IoT networks and subsequently understands the need for lightweight and homomorphic encryption. Then, the chapter presents and compares the most widely used lightweight and homomorphic algorithms/schemes, finally presenting the observations and conclusions based on the study. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Item A random key generation scheme using primitive polynomials over GF(2)(2016) Singh, I.; Pais, A.R.A new key generation algorithm is proposed using primitive polynomials over Glaois Field GF(2). In this approach, we have used MD5 algorithm to digest the system time and IP address of the system. The combination of these digest values acts as random seed for the key generation process. The randomness test for the generated key is performed by using Blum Blum Shub (BBS), Micali-Schnorr and Mersenne Twister (MT19937) PRNG algorithms. The generated key has been compared on the basis of the combination of 2 bit, 3 bit, 4 bit and 8 bit count values of 0�s and 1�s. In this paper, we have used chi squared test, R squared test and standard deviation to check the randomness of the generated key. We have analyzed our result based on the above three criteria and observed that the proposed algorithm achieves lower dispersion in 72.5% of the test cases, lower error rate in 61.6% of the test cases and higher fitness value in 68.3% of the test cases. � Springer Nature Singapore Pte Ltd. 2016.