Insights Into Deep Steganography: A Study of Steganography Automation and Trends

Gurunath, R.; Samanta, Debabrata; Pandey, Digvijay

doi:10.1002/9781119812555.ch6

Cited by 2 publications

References 32 publications

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Machine-Learning-Based Spam Mail Detector

Charanarur,

Jain,

Rao

et al. 2023

SN COMPUT. SCI.

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The proliferation of spam emails, a predominant form of online harassment, has elevated the significance of email in daily life. As a consequence, a substantial portion of individuals remain vulnerable to fraudulent activities. Despite Gmail’s “spam mail filtration system,” its effectiveness is not absolute. It occasionally misclassifies legitimate messages, leading to their confinement in the spam folder, or overlooks potentially harmful spam emails. This results in the occurrence of false positives. This research scrutinizes the historical data, cookies, caches, Session Restores, flash artifacts, and super cookies of Internet Explorer, Firefox, and Chrome on the Windows 10 platform. Data was collected through Google, Firefox, and Internet Explorer, operating within the Windows 10 environment. It has been observed that browsers store user behavior data on the host computer’s hard drive. The implications of this study hold substantial value for computer forensics researchers, law enforcement professionals, and digital forensics experts. The study leverages Python, alongside pertinent libraries such as pandas, Numpy, Matplotlib, scikit-learn, and flask, to facilitate its investigation. The experiment result and analysis show KN and NB algorithms have the best accuracy and precision score compared to other Algorithms.

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Machine-Learning-Based Spam Mail Detector

Charanarur,

Jain,

Rao

et al. 2023

SN COMPUT. SCI.

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A Real-Time Smart Sewage Cleaning UAV Assistance System Using IoT

Iyyanar¹,

Anand²,

Shanthi³

et al. 2023

Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities

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There is a boom in autonomous systems with rapid technological development that cannot adapt without human interaction to actual life conditions. Such programs will free people from the added activities which are mundane, repeatable, and invalid. The unmanned aerial vehicle (UAV) can use in boring, dusty, and hazardous environments, where human health and welfare are at significant risk. Autonomous systems deliver efficiencies in the supply chain, tracking, and hazardous climate control. This paper proposes the concept to improve the UAV's effectiveness, the compression and track architecture is combined. In addition, the UAV and pipe can increase the friction of the trackwheel. The process of cleaning starts when the sensors feel the mouth. The washing mechanism will not occur if the sensors do not detect the dirt. The focus of this chapter is on the drainage cleaning system automation. Device automation is required to address the mobility and space challenge. This chapter proposes the effective use of this method to manage waste disposal and routine wastage filtration.

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Insights Into Deep Steganography: A Study of Steganography Automation and Trends

Cited by 2 publications

References 32 publications

Machine-Learning-Based Spam Mail Detector

Machine-Learning-Based Spam Mail Detector

A Real-Time Smart Sewage Cleaning UAV Assistance System Using IoT

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