Machine Learning based Hybrid Approach for Email Spam Detection

Bansal, Chirag; Sidhu, Brahmaleen Kaur

doi:10.1109/icrito51393.2021.9596149

Cited by 13 publications

(4 citation statements)

References 4 publications

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“…In a study on methods for preventing spam in emails containing images, researchers found multiple approaches to filtering [66]. It is essential to have hybrid features that combine visual and textual information to increase the performance of spam filtering [77]. As a result, it was discovered that integrated SPAM detection for multilingual emails was also essential [78].…”

Section: Discussion and Open Questions On Previous Empirical Study As...mentioning

confidence: 99%

Email Security Issues, Tools, and Techniques Used in Investigation

et al. 2023

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The email system is a globally distributed communication infrastructure service that involves multiple actors playing different roles to ensure end-to-end mail delivery. It is an indispensable method of communicating that is changing how people share data and information. As a result, it facilitates effective and efficient communication, especially in business, as well as convenience, accessibility, and replication. Today, email can send more than just text files; it can also send audio, video, photos, and other files with extensions. With email becoming ubiquitous in all aspects of our lives, enhancing its security, operating procedures, and forensic investigation has become essential. The purpose of this paper is to review some real email forensic incidents and the tools and techniques that have been proposed. A discussion of the major threats to email as well as techniques to mitigate them will also be provided. A comparison study was made of several techniques and analysis tools used in email forensics. In addition, this paper compares the available software tools for email forensics based on factors such as language interface, user interface, programming language, creation of image files, calculation of hash value, cost, and advantages.

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Section: Discussion and Open Questions On Previous Empirical Study As...mentioning

confidence: 99%

Email Security Issues, Tools, and Techniques Used in Investigation

et al. 2023

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“…The first study uses EasyOCR for character recognition of high-resolution images restored with super resolution [36]. Second, the mail contents were detected using EasyOCR to detect spam [37]. Finally, the third study used EasyOCR for vehicle license plate recognition.…”

Section: Proposed Architecturementioning

confidence: 99%

IoT-based Architecture and Implementation for Automatic Shock Treatment

2022

KSII TIIS

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The Internet of Things (IoT) is being used in a wide variety of fields due to the recent 4th industrial revolution. In particular, research is being conducted that combines IoT with the medical field such as telemedicine. Among them, the field of shock detection is a big issue in the medical field because the causes of shock are diverse, treatments are very complex, and require a high level of medical knowledge and experience. The transmission of infectious diseases is common when treating critically ill patients, especially patients with shock. Thus, to effectively care for shock patients, we propose an architecture that continuously monitors the patient's condition, and automatically recommends a drug injection treatment according to the patient's shock condition. The patient's hemodynamic information is continuously monitored, and the patient's shock generation information is recorded periodically. With the recorded patient information, the patient's condition is determined and automatically injected with necessary medication. The medical team can find out whether the patient's condition has improved by checking the recorded information through web applications. The study can help relieve the shortage of medical personnel and help prevent transmission of infectious disease in medical staff. We look forward to playing a role in helping medical staff by making recommendations for the diagnosis and treatment of complex and difficult shocks.

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“…Spam, according to a study by C. Bansal et al [4], is the most talked about topic on the Internet today. When you transmit spam, it's simple for spammers to do so.…”

Section: Parallel Recent Research Outcomesmentioning

confidence: 99%

Detection of Severity-based Email SPAM Messages using Adaptive Threshold Driven Clustering

Venugopal¹,

Bhaskari²,

Seetaramanath³

2022

IJACSA

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The classification of emails is one crucial part of the email filtering process, as emails have become one of the key methods of communication. The process for identifying safe or unsafe emails is complex due to the diversified use of the language. Nonetheless, most of the parallel research outcomes have demonstrated significant benchmarks in identifying email spam. However, the standard processes can only identify the emails as spam or ham. Henceforth, a detailed classification of the emails has not been achieved. Thus, this work proposes a novel method for the identification of the emails into various classes using the proposed deep clustering process with the help of the ranking of words into severity. The proposed work demonstrates nearly 99.4% accuracy in detecting and classifying the emails into a total of five classes.

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Machine Learning based Hybrid Approach for Email Spam Detection

Cited by 13 publications

References 4 publications

Email Security Issues, Tools, and Techniques Used in Investigation

Email Security Issues, Tools, and Techniques Used in Investigation

IoT-based Architecture and Implementation for Automatic Shock Treatment

Detection of Severity-based Email SPAM Messages using Adaptive Threshold Driven Clustering

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