2022
Evaluating operational readiness using chaos engineering simulations on Kubernetes architecture in Big Data
Gautam Siwach, Adinarayana Haridas, Nagaraj Chinni
2022 International Conference on Smart Applications, Communications and Networking (SmartNets), pp. 1-7
Abstract
- How much confidence we can have in the interconnected complex systems that we put into production environment? In this paper we will provide the solution for operational readiness of a platform strengthening the backup, restore, network file transfer, failover capabilities and overall security. We provide the evaluation of inducing chaos to a Kubernetes environment which terminates random pods with data from edge devices in data centers while processing analytics on Big Data network and infer the recovery time of pods to calculate an estimated response time. In this research, we discuss the Operational Acceptance Testing through Chaos Engineering at all layers and more precisely on the modern architecture and practices like Microservices Architecture and Cloud computing which have changed our IT landscape in recent times.
Inferencing Big Data with Artificial Intelligence & Machine Learning Models in Metaverse
Gautam Siwach, Adinarayana Haridas, Don Bunch
2022 International Conference on Smart Applications, Communications and Networking (SmartNets), pp. 01-06
Abstract
This quantitaive study provides different methods of visualization for processing Big Data sets in augmented and virtual reality. The goal is to provide the detailed implementation of the statistical methods and modeling techniques i.e. using machine learning algorithms and artificial intelligence. The Statistical analysis is performed on the Big Data sets in Metaverse, that points towards real time inferencing infrastructure and techniques. Also, This paper elaborates the importance of pervasive and Ubiquitous Computing Architecture and Applications that enable High-end computing on Big Data sets. In this paper, we evaluate the need for a combination of cognitive mechanism and high-end infrastructure to address the performance, latency, and security issues when working on Big Data sets in environments like virtual or Augmented reality. Despite the modernization and advancement in technology there are increasing number of breaches in cloud and hybrid infrastructures, this justifies the need to meet the requirements of strengthening security, safeguard mechanisms and privacy. This paper discusses methods beyond basic visualizations through a deep dive exploration on improvising the applications of existing analytical methods, and use of advanced exploratory tools and visualization techniques on the next generation platforms.
2015
2014
Encrypted Search & Cluster Formation in Big Data
Siwach, Gautam and Esmailpour, Amir
IN ASEE 2014 Zone I Conference, University of Bridgeport, Bridgpeort
Abstract
Abstract-In this paper we investigate the key features of big data as formation of clusters and their interconnections along with their connections to the databases. We focused on the security of big data and the actual orientation of the term towards the presence of different type of data in an encrypted form at cloud interface by providing the raw definitions and real time examples within the technology. Moreover, we propose an approach for identifying the encoding technique in order to perform an expedited search over encrypted text ensuring the security enhancements in big data.
LTE Security potential vulnerability and algorithm enhancements
Siwach, Gautam and Esmailpour, Amir
Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference on, pp. 1--7
Abstract
Abstract: In this paper we investigate potential vulnerabilities in the implementation of encryption processes within the EEA2 algorithm of Long-Term Evolution (LTE), and we propose an enhancement for the security features in LTE. We show that during the encryption process in EEA2, a leakage of 128 bits of plain text and its corresponding cipher text in a PDU, could potentially allow an intruder to recover the key, hence the entire original plain text could be compromised. We propose a solution by adding a matrix block to the encryption process of the cipher text. The proposed encryption process uses a random set of numbers in the form of a matrix, which is used with the cipher text in order to obtain an enriched block of ciphered data. We have implemented the algorithm in Matlab, and successfully tested several use cases to produce an enriched block of encrypted data, which is then decrypted to obtain the original text. We also show by simulation that enriching the data using this system will improve the encryption process; however, the cost is increasing the complexity of the algorithm.
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