Atul Srivastava
Dehradun Institute of Technology University, Bennett University
Papers
3
Total Citations
12
H-Index
2
About
Atul Srivastava is a researcher whose work lies at the intersection of big data, web mining, and cybersecurity, with a particular focus on the critical, yet often overlooked, step of data preprocessing. His primary research addresses the immense challenge of cleaning and preparing massive, unstructured web server logs for meaningful analysis. Srivastava’s major contribution is the development of scalable, parallelized preprocessing algorithms, most notably the "IRPDP_HT2" method, which leverages the Hadoop MapReduce framework to handle the volume and velocity of modern web data efficiently. His most cited work, a 2021 study on MapReduce-based preprocessing with integrated robot detection, has garnered 8 citations, highlighting the demand for his integrated approach. A key theme in his research is the detection of "ethical and unethical" web robots, a security concern he explored in a 2017 paper. By combining data cleaning with robot identification, Srivastava provides a dual-purpose solution that not only refines data quality for mining but also fortifies web security, making his contributions vital for researchers and practitioners building robust, intelligent web analytics systems.
Research Focus
Key Achievements
Top Papers
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