Pradeep Kumar Singh
National Institute of Technology, Raipur
Software engineeringMachine learningSupport vector machineData miningBenchmark (computing)SurgeryFeature selectionDigital watermarkingArtificial intelligencePattern recognitionSoftware constructionWireless sensor networkEfficient energy useSoftwareComputer networkField (computer science)Computer securityComputer scienceNode (networking)Naive Bayes classifierFeature extractionSoftware developmentMedicineCluster analysisSoftware metricClassifier (UML)
229Publications
18H-index
1,135Citations
Publications 229
Newest
Abstract null null Android OS popularity has given significant rise to malicious apps targeting it. Malware use state of the art obfuscation methods to hide their functionality and evade anti-malware engines. We present BLADE, a novel obfuscation resilient system based on Opcode Segments for detection. It makes three contributions: Firstly, a novel Opcode Segment Document results in feature characterization resilient to obfuscation techniques. Secondly, we perform semantics based simplification ...
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#1Namita Agarwal (JUIT: Jaypee University of Information Technology)H-Index: 1
#2Pradeep Kumar Singh (JUIT: Jaypee University of Information Technology)H-Index: 18
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#1Amit Sharma (JUIT: Jaypee University of Information Technology)H-Index: 3
#1Amit Sharma (JUIT: Jaypee University of Information Technology)H-Index: 67
Last. Pradeep Kumar Singh (ABES Engineering College)H-Index: 18
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Abstract null null Energy is critical infrastructure, and addressing cybersecurity issues in the energy sector is challenging. Cloud computing has advanced from being a data storage solution to a complex system that enables resource management, workforce management, scalability, flexibility, managing operational expenses, etc. The energies sector relies heavily on critical infrastructure and cloud usage. Hence, there is a simultaneous increase in the insecurities prevailing in both environments....
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#1Pradeep Kumar Singh (NIT DGP: National Institute of Technology, Durgapur)H-Index: 4
#2Rafeeq Ahmed (Kamla Nehru Institute of Technology)H-Index: 2
Last. Prasenjit Choudhury (NIT DGP: National Institute of Technology, Durgapur)H-Index: 11
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With the growing nature of data over the internet, item-based collaborative filtering has become a promising method in the recommendation. The two-step process of item-based collaborative filtering, i.e., computation of similarity among items, and rating prediction using similar items are utilized in recommendation. However, the quality of recommendations after following these steps degrade in sparse datasets. Traditionally, in item-based collaborative filtering, several similarity measures have...
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#1Ishaani Priyadarshini (UD: University of Delaware)H-Index: 10
#2Pinaki Ranjan Mohanty (Purdue University)H-Index: 2
Last. Pradeep Kumar Singh (ABES Engineering College)H-Index: 18
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The outbreak of the novel Coronavirus in late 2019 brought severe devastation to the world. The pandemic spread across the globe, infecting more than ten million people and disrupting several businesses. Although social distancing and the use of protective masks were suggested all over the world, the cases seem to rise, which led to worldwide lockdown in different phases. The rampant escalation in the number of cases, the global effects, and the lockdown may have a severe effect on the psycholog...
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#1Meetesh Nevendra (NITRR: National Institute of Technology, Raipur)H-Index: 1
#2Pradeep Kumar Singh (NITRR: National Institute of Technology, Raipur)H-Index: 18
With the increasing complexity and volume of the software, the number of defects in software modules is also increasing consistently, which affects the quality and delivery of software in time and budget. To improve the software quality and timely allocation of resources, defects should be detected at the initial phases of the software development life cycle. However, the existing defect prediction methodology based on high-dimensional and limited data only focuses on predicting defective module...
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#1Deepak KumarH-Index: 43
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#3Ashutosh Sharma (SFedU: Southern Federal University)H-Index: 15
Intrusion detection is crucial in computer network security issues; therefore, this work is aimed at maximizing network security protection and its improvement by proposing various preventive techniques. Outlier detection and semisupervised clustering algorithms based on shared nearest neighbors are proposed in this work to address intrusion detection by converting it into a problem of mining outliers using the network behavior dataset. The algorithm uses shared nearest neighbors as similarity, ...
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#1Devendra KumarH-Index: 2
#1Deepak KumarH-Index: 43
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The present study accentuated a hybrid approach to evaluate the impact, association and discrepancies of demographic characteristics on a student’s job placement. The present study extracted several significant academic features that determine the Master of Business Administration (MBA) student placement and confirm the placed gender. This paper recommended a novel futuristic roadmap for students, parents, guardians, institutions, and companies to benefit at a certain level. Out of seven experim...
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