Integrated SPAM detection for multilingual emails

Iyengar, Akash; Kalpana, G.; Kalyankumar, S.; GunaNandhini, S.

doi:10.1109/icices.2017.8070784

Cited by 6 publications

(3 citation statements)

References 4 publications

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“…This is also comparable to the classification of multi-language spam phishing by the email body text towards automated security incident investigation [79]. During COVID-19, it was discovered that a critical attitude toward library marketing that was related to sending text messages and emails to online library customers was highly significant [80]. This is related to the study that was conducted for software as a service design and construction of email marketing with lower usage costs for the hospitality industry [81][82][83].…”

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

confidence: 61%

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: 61%

Email Security Issues, Tools, and Techniques Used in Investigation

et al. 2023

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“…For this study, the raw data collected is obtained from the online resource kaggle, which will be used to train machine learning models. e data was originally available in English language, and it was obtained in the comma separated values (CSV) format [12]. Further, the dataset obtained was translated using the Googletrans python library in URDU, which uses the Google Translate Ajax API.…”

Section: Datasetmentioning

confidence: 99%

Machine Learning-Based Detection of Spam Emails

Siddique

Khan

Din

et al. 2021

Scientific Programming

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Social communication has evolved, with e-mail still being one of the most common communication means, used for both formal and informal ways. With many languages being digitized for the electronic world, the use of English is still abundant. However, various native languages of different regions are emerging gradually. The Urdu language, coming from South Asia, mostly Pakistan, is also getting its pace as a medium for communications used in social media platforms, websites, and emails. With the increased usage of emails, Urdu’s number and variety of spam content also increase. Spam emails are inappropriate and unwanted messages usually sent to breach security. These spam emails include phishing URLs, advertisements, commercial segments, and a large number of indiscriminate recipients. Thus, such content is always a hazard for the user, and many studies have taken place to detect such spam content. However, there is a dire need to detect spam emails, which have content written in Urdu language. The proposed study utilizes the existing machine learning algorithms including Naive Bayes, CNN, SVM, and LSTM to detect and categorize e-mail content. According to our findings, the LSTM model outperforms other models with a highest score of 98.4% accuracy.

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“…An additional problem is the language version of the email being sent. If the client sends emails in different languages, the problem of analysing the content for spam recognition is even more complex [17,18]. All of these elements make the analysis of thousands of emails sent every minute extremely complex and require significant hardware resources on the ESP's side.…”

Section: Introductionmentioning

confidence: 99%

Email Campaign Evaluation Based on User and Mail Server Response

Szpyrka

Suszalski²,

Obara³

et al. 2023

Applied Sciences

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The goal of an email service provider company is to send out a large number of emails to help its clients realise successful email marketing activities. Thousands of emails sent every minute need to be analysed in real time to reduce spam or phishing. The paper describes a method that uses real-time tracking of key campaign metrics such as the opens count, clicks count, hard bounces count, etc., to identify campaigns that should be stopped because they can be classified as spam or phishing. The key point of this solution is that we do not analyse email content. Nevertheless, the proposed neural networks are highly effective—the F1-score is above 0.95 for any used sample. Furthermore, the approach allows us to use the same model regardless of the language of an email. The method was developed and verified in collaboration with Freshmail, a leading provider of email marketing services in Poland. Validation of the method on real data provided by the company confirmed its high effectiveness.

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Integrated SPAM detection for multilingual emails

Cited by 6 publications

References 4 publications

Email Security Issues, Tools, and Techniques Used in Investigation

Email Security Issues, Tools, and Techniques Used in Investigation

Machine Learning-Based Detection of Spam Emails

Email Campaign Evaluation Based on User and Mail Server Response

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