Anti spam Research Papers - Academia.edu (original) (raw)

2024

Cybercrime has emerged as a critical threat to individuals, organizations, and governments worldwide, with Canadian agencies struggling to address the growing challenges effectively. A report by Canada's auditor general highlights significant gaps in the capacity and coordination of agencies such as the RCMP, the Communications Security Establishment (CSE), and the Canadian Radio-television and Telecommunications Commission (CRTC). These gaps include deficiencies in case tracking, staffing shortages, and fragmented reporting systems, which hinder comprehensive responses to cybercrime. While some high-priority cases receive adequate attention, systemic inefficiencies threaten Canada's ability to protect its citizens and infrastructure. The report underscores the urgent need for a unified cybercrime strategy and better inter-agency collaboration to mitigate the rising tide of cyber threats.

2024

David designed analog and digital instrumentation for Thornton Associates, Digilab and Natural Microsystems before co-founding Galactic Industries Corp, a scientific software company (since acquired by a division of Thermo Electron). His research interests include spam, intellectual property, Internet technology and First Amendment issues. David will be joining Wilmer Cutler Pickering Hale and Dorr in Boston as an Intellectual Property Associate in the fall of 2005.

2024, IFIP Advances in Information and Communication Technology

In this paper we propose a user based architecture for the email system, where the recipient of an email message manage its receipt in conjunction with both origin and destination email servers. Messages are kept to the origin email server until a confirmation from the recipient is issued though the destination email server. Therefore, spam email doesn't travel the Internet and doesn't overload the destination email server and recipient's mailbox. White and black lists for (sender, email_server) pairs are built automatically following user evaluation. With our proposal, full control is delegated to the recipient over the email activity. On the server side, Simple Mail Delivery Protocol (SMDP) manages email delivery and options. SMDP server acts as a gateway for sending emails, a repository for the users' mailboxes and a central point for managing user options related to email filtering and spam handling. The solution is suitable for group/business email handling.

2024, Advances in intelligent systems and computing

An investigation is performed of a machine learning algorithm and the Bayesian classifier in the spam-filtering context. The paper shows the advantage of the use of Reverse Polish Notation (RPN) expressions with feature extraction compared to the traditional Naïve Bayesian classifier used for spam detection assuming the same features. The performance of the two is investigated using a public corpus and a recent private spam collection, concluding that the system based on RPN LGP (Linear Genetic Programming) gave better results compared to two popularly used open source Bayesian spam filters.

2024

Internet is no doubt inevitable as it has a tremendous impact in our lives. Despite its importance, internet comes with many challenges, among which is security. From the literature, several attempts have been made to develop secure and user-friendly spam detection technique. But these attempts linger between these two fundamental issues: the robustness and the usability in CAPTCHA system, passiveness of Intrusion Detection System (IDS), which failed to detect some forms of novel attacks, flexibility to attacks and not efficient to users. In this work, honeyCAPTCHA, an enhanced intrusion detection framework is designed to solve the above problems as it is capable of detecting crawlers’ attacks, resilient and efficient to users. The system is mainly considered as an option to a CAPTCHA-BASED IDS model, which suffers the above problems. The system outperforms the existing system considering its performance measure based on the proposed metrics that includes detection rate (DR) of 76%,...

2024

Spam emails are one of the crucial problems faced by most of the email users. There are a lot of algorithms to filter spam mails from ham mails. In this paper two efficient filters-Bayesian filters and Artificial Immunity filters are studied and compared. Bayesian classifier has been suggested as an effective method to construct anti-spam filters for its strong categorization and high precision. Artificial immune system has become a new embranchment in computing intelligence for its good selflearning, self-adaptability and robustness. This paper proposes a new hybrid filtering system based on Bayesian, AIS and the concept of blacklist and whitelist .

2024, Telediritto.it: Portale giuridico umbro

Commette il reato di diffamazione aggravata colui il quale, inoltrando messaggi nella rete internet attraverso un gruppo di discussione, insulti il proprio antagonista definendolo “spammer” e diffondendo la notizia di sue precedenti condanne.
La circostanza che l'imputato si sia auto investito del compito di individuare, affrontare e segnalare con ogni sistema di diffusione, coloro che in rete lo raggiungono con messaggi pubblicitari non desiderati (c.d. “spam”) non assume importanza scriminante; il diritto di critica non può, infatti, estendersi sino a consentire l'offesa e l'umiliazione pubblica dei
propri avversari, neppure di coloro che siano stati sanzionati amministrativamente e penalmente per violazione delle regole del codice di riservatezza

2023, Not Available

Recent trends in agriculture yields a large number of researches and articles related to it. It has become a daily routine to access these articles by modern day researchers. But due to the fact that these information are in an unstructured form, readers might face difficulty to access these information. Text Categorization, a branch of Text Mining, is a very useful technique to represent these unstructured text in a structured way. In this research, a number of research articles has been categorized using text categorization by applying some popular machine learning algorithms.

2023, Lecture Notes in Computer Science

This paper presents an evolutionary multi-objective optimization problem formulation for the anti-spam filtering problem, addressing both the classification quality criteria (False Positive and False Negative error rates) and email messages classification time (minimization). This approach is compared to single objective problem formulations found in the literature, and its advantages for decision support and flexible/adaptive anti-spam filtering configuration is demonstrated. A study is performed using the Wirebrush4SPAM framework anti-spam filtering and the SpamAssassin email dataset. The NSGA-II evolutionary multi-objective optimization algorithm was applied for the purpose of validating and demonstrating the adoption of this novel approach to the anti-spam filtering optimization problem, formulated from the multi-objective optimization perspective. The results obtained from the experiments demonstrated that this optimization strategy allows the decision maker (anti-spam filtering system administrator) to select among a set of optimal and flexible filter configuration alternatives with respect to classification quality and classification efficiency.

2023, Decision Support Systems

In this paper we show an instance-based reasoning e-mail filtering model that outperforms classical machine learning techniques and other successful lazy learners approaches in the domain of anti-spam filtering. The architecture of the learning-based anti-spam filter is based on a tuneable enhanced instance retrieval network able to accurately generalize e-mail representations. The reuse of similar messages is carried out by a simple unanimous voting mechanism to determine whether the target case is spam or not. Previous to the final response of the system, the revision stage is only performed when the assigned class is spam whereby the system employs general knowledge in the form of metarules.

2023, The Journal of English Studies

The term 'spam' addresses unsolicited emails sent in bulk; therefore, the term 'financial fraud spam' refers to unwanted bulk emails in which different tricks and techniques are employed to swindle money from the recipients. Estimates show that more than 80% of worldwide email traffic in 2011 was spam. It should be noted that while the number of daily spam emails in 2002 was 2.4 billion, this number rose to 200 billion spam emails in 2011. Considering the incurred cost of spam emails, finding effective ways for identifying spam emails may help decrease the cost to a great extent. It must be borne in mind that the generators of the financial fraud spam emails employ intricate persuasive strategies that make their stories believable to the readers. In an attempt to unravel some of these persuasive strategies, the present paper focuses on the use of presupposition, personalization, and lexical choice that are frequently used by the generators of the financial fraud spam emails. The results of the analysis showed that the above mentioned persuasive strategies were widely used in the text of financial fraud spam emails. Furthermore, the study demonstrated that persuasive lexical devices were used throughout the spam emails, including the email addresses. In terms of personalization and presupposition, the study showed that all parts of the spam emails, except the address section, were subjected to the use of these persuasive strategies.

2023, Advanced Information Systems

In the current era, numerous social networks and messaging platforms have become integral parts of our lives, particularly in relation to work activities, due to the prevailing COVID-19 pandemic and russian war in Ukraine. Amidst this backdrop, the issue of spam and spammers has become more pertinent than ever, with a continuous rise in the incidence of spam within work-related text streams. Spam refers to textual content that is extraneous to a specific text stream, while a spammer denotes an individual who disseminates unsolicited messages for personal gain. The proposed article is devoted to address this scientific and practical challenge of identifying spammers and detecting spam messages within the textual context of any social network or messenger. This endeavor encompasses the utilization of diverse spam detection algorithms and approaches for spammer identification. Four algorithms were implemented, namely a naive Bayesian classifier, Support-vector machine, multilayer perceptron neural network, and convolutional neural network. The research objective was to develop a spam detection algorithm that can be seamlessly integrated into a messenger platform, exemplified by the utilization of Telegram as a case study. The designed algorithm discerns spam based on the contextual characteristics of a specific text stream, subsequently removing the spam message and blocking the spammeruser until authorized by one of the application administrators.

2023, Not Available

2023, Journal of University of Shanghai for Science and Technology

The necessity for spam detection is particularly pertinent nowadays, as there is no quality control over social media, and users have the ability to distribute unverified material, therefore facilitating fraud and deceit. Spam detection can aid in the prevention of such fraud. This scenario has developed mostly as a result of the distribution of disparate, unconfirmed information via shopping websites, emails, and text messages (SMS). There are several ways of categorising and identifying spam. Each of them has certain advantages and disadvantages. The machine learning model “Support Vector Machine” is employed to detect spam in this case. SVM is a basic concept: the method proposes a line or hyperplane to classify the data. The model can categorise any type of text into a given category after being fed a set of labelled training data for each category.

2023

This is a Diamond Open Access article distributed under the terms of the Creative Commons H T U Attribution-NonCommercial-ShareAlike 4.0 International (CC-BY-NC-SA 4.0) LicenseU T H , T which permits unrestricted non-commercial useT ,... more

2023, 2008 Second International Conference on Communications and Electronics

Language classification is the process of identifying the disposition of a presented text, such as classifying an email or a text document into a particular category. Classifying text can involve determining

2023, 2008 Second International Conference on Communications and Electronics

2023, ADCAIJ: ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL

Online reviews about the purchase of a product or services provided have become the main source of user opinions. To gain profit or fame usually spam reviews are written to promote or demote some target products or services. This practice is known as review spamming. In the last few years, different methods have been suggested to solve the problem of review spamming but there is still a need to introduce new spam review detection method to improve accuracy results. In this work, researchers have studied six different spammer behavioral features and analyzed the proposed spam review detection method using weight method. An experimental evaluation was conducted on a benchmark dataset and achieved 84.5% accuracy.

2023, Software: Practice and Experience

As the Internet matured, security became more important and formerly adequate designs became inadequate. One of the victims of the increased need for security was sendmail. This paper shows how its competitors improved on its design in response to the increased need for security. The designers of qmail and Postfix used well-known patterns to achieve better security without affecting performance; these patterns can be used by the designers of other systems with an increased need for security.

2023, 2008 Second International Conference on Communications and Electronics

2023

Increasing reliance on the electronic mail (e-mail) has attracted spammers to send more and more spam e-mails in order to maximizing their financial gains. These unwanted e-mails are not only clogging the Internet traffic but are also causing storage problems at the receiving servers. Besides these, spam e-mails also serve as a vehicle to a variety of online crimes and abuses. Although several anti-spam procedures are currently employed to distinguish spam e-mails from the legitimate e-mails yet spammers and phishes obfuscate their e-mail content to circumvent anti-spam procedures. Efficiency of anti-spam procedures to combat spam entry into the system greatly depend on their level of operation and a clear insight of various possible modes of spamming. In this paper we investigate directed graph model of Internet e-mail infrastructure and spamming modes used by spammers to inject spam into the system. The paper outlines the routes, system components, devices and protocols exploited by each spamming mode.

2023, 2008 Second International Conference on Communications and Electronics

2023

Bankable Postage (BP) has been proposed as a mechanism to attack the underlying techico-economic reasons for spamming. However, BP is costly to legitimate users and threatens to be undermined by spoofing attacks. In this paper we show how to use the Claim Tool Kit to defeat these attacks and propose a collaborative recommendation technique to reduce the number of BPs required by legitimate users. Known, trustworthy senders can introduce new senders to their contacts free of charge. BPs are only necessary when no mutually trustworthy third party is able to introduce sender and receiver. We show that this can significantly reduce the number of BPs required by legitimate users, in the absence of attackers. However, collaboration introduces its own set of attacks. Depending on the search scheme, an empirical evaluation on a real-world network of email users indicates that random pleasing attacks and network topology engineered attacks, where the most important email users are pleased; significantly reduce the spammer attack cost.

2023, Journal of the Maharaja Sayajirao University of Baroda

Today, Most IT organizations prefer a Mail server for sending emails while developing applications for their clients. Initially, they used to send mail by a web server. This paper presents the comparison of sending mail using the normal PHP mail() function and sending mail using SMTP standard protocol. And it is found that sending mail using the PHP mail function has got security-related issues and it uses a web server for sending mail which has a lot of limitations when compared to the mail server which is used by PHPMailer for sending mail using SMTP protocol. It is not mandatory in the normal PHP mail function to include the header details while sending mail but in PHPMailer it is mandatory. It is very difficult to trace the mail without the header details. This paper figure out the limitations of the PHP mail() function and also outline how the limitation can be overcome by using PHPMailer that follows SMTP Protocol for sending mail.

2023

2023, 2008 Second International Conference on Communications and Electronics

2023, Le Centre pour la Communication Scientifique Directe - HAL - memSIC

Après Rouen en 2019, Dax dans les Landes puis Villefranche dans la Saône et désormais la ville de Chalon-sur-Saône : ces centres hospitaliers ou leurs collectivités ont été victimes de logiciels malveillants, paralysant leur système informatique. Entre 2017 et 2020, plusieurs collectivités et entreprises françaises ont été sujettes à des attaques, souvent suivies de demandes de rançon. Le kidnapping de données immobilise parfois des secteurs extrêmement périlleux, comme les hôpitaux, déjà bien affaiblis par la crise sanitaire. Ailleurs Bouygues, Honda, Stadler rail (une entreprise suisse), Canon, Sopra Steriaet tout récemment Gmail/Hotmail ont aussi subi ce type d'attaques. Une nouvelle modalité d'extorsion des données semble d'ailleurs émerger. Il s'agit d'une forme d'extorsion numérique plus rapide, sans cryptage de données, mais toujours avec le paiement d'une rançon. Les pays les plus touchés sont notamment le Nigéria, la Colombie, l'Afrique du Sud, la Chine, la Pologne, la Belgique et les Philippines. D'après une étude récente de Xerfi cette forme de cybercriminalité aurait coûté aux entreprises dans le monde environ 350 milliards d'euros en 2017 et 885 milliards d'euros en 2020. Le cabinet Accenture évalue d'ailleurs, pour la projection de période 2019-2024, le coût de la cybercriminalité pour les entreprises à l'échelle mondiale à 4 600 milliards d'euros. Alors comment fonctionne ce type d'attaques ? Et comment s'en prémunir ? Des modes opératoires proches des kidnappings de personnes Mes recherches sur le kidnapping et l'extorsion montrent des modes opératoires assez similaires entre le rançonnage « physique » impliquant directement des personnes et le kidnapping dit « virtuel » ou « immatériel ». L'instantanéité des échanges d'informations toujours plus rapides et volumineuses dans l'entreprise comme dans la société trouve un écho chez les cybercriminels. Ces derniers utilisent des logiciels aux noms comme Darkside, Ryuk, Egregor, DoppelPaymer, REvil ou bien encore Avaddon. Ils capturent les données en les cryptant, en échange d'une

2023, 2008 Second International Conference on Communications and Electronics

2023

Email has emerged as a dominant form of electronic communication between people. Spam is a major problem for email users, with estimates of up to 56% of email falling into that category [13]. Control of Spam is being attempted with technical [38-44] and legislative [19-36] methods. In this paper we look at email and spam from a supply-demand perspective. We propose Gridemail, an email system based on an economy of communicating parties, where participants' motivations are represented as pricing policies and profiles. This system is expected to help people regulate their personal communications to suit their conditions, and help in removing unwanted messages.

2022, 2008 Second International Conference on Communications and Electronics

2022

Unsolicited e-mails pose considerable inconvenience on part of the frequent Internet users. Unfortunately it is not possible to have human moderators monitoring emails of other people for possible spammers all the time. It is also a serious issue violating privacy acts, which most mail service providers fear. Individuals as well as e-commerce sites are also getting spammed on regular basis. The reason for this growing trend of spamming is the fact that there is no efficient filtering system fully developed as yet. In this paper, Electronic COP (E-COP) has been proposed. E-COP is a filtering system against known spams as well as newly evolved spam messages by using grid networks incorporated with some protocol level changes. Objective of this paper is to define structure and working principle of E-COP.

2022, International Journal of Engineering Research and

Nowadays, a big part of people rely on available email or messages sent by the stranger. The possibility that anybody can leave an email or a message provides a golden opportunity for spammers to write spam message about our different interests .Spam fills inbox with number of ridiculous emails. Degrades our internet speed to a great extent .Steals useful information like our details on our contact list. Identifying these spammers and also the spam content can be a hot topic of research and laborious tasks. Email spam is an operation to send messages in bulk by mail .Since the expense of the spam is borne mostly by the recipient ,it is effectively postage due advertising. Spam email is a kind of commercial advertising which is economically viable because email could be a very cost effective medium for sender .With this proposed model the specified message can be stated as spam or not using Bayes' theorem and Naive Bayes' Classifier and Also IP addresses of the sender are often detected .

2022, Not Available

2022, 2008 Second International Conference on Communications and Electronics

2022, Prva studentska konferencija o …

Automatska kategorizacija web dokumenata s primjenom u financijskom inzenjerstvu Mislav Boro, Jurica Cerovec, Deni Dugandzic, Tin Englman Sveucilite u Zagrebu, Fakultet elektrotehnike i racunarstva Unska 3, 10000 Zagreb, Hrvatska... more

2022, Information Security Technical Report

Spam is a big problem for email users, and more serious for wireless mobile users with limited bandwidth. The battle between spamming and anti-spamming technologies has been going on for many years. Though many advanced antispamming technologies are progressing significantly, spam is still able to bombard many email users. The problem worsens when some anti-spamming methods unintentionally filtered legitimate emails instead! In this paper, we first review existing anti-spam technologies, then propose a layered defense framework using a combination of anti-spamming methods. Under this framework, the server-level defense is targeted for common spam while the client-level defense further filters specific spam for individual users. This layered structure improves on filtering accuracy and yet reduces the number of false positives.

2022, Computer Communications

Unsolicited Commercial Email, or Spam, is nowadays an increasingly serious problem to email users. A number of anti-spam schemes have been proposed in the literature and some of them have been deployed in email systems, but the problem has yet been well addressed. One of those schemes is challenge-response, in which a challenge, ranging from a simple mathematical problem to a hard-AI problem, is imposed on an email sender in order to forbid machine-based spam reaching receivers' mailboxes. However, such a scheme introduces new problems for the users, e.g., delay of service and denial of service. In this paper, we introduce the pre-challenge scheme, which is based on the challenge-response mechanism and takes advantage of some features of email systems. It assumes each user has a challenge that is defined by the user himself/herself and associated with his/her email address, in such a way that an email sender can simultaneously retrieve a new receiver's email address and challenge before sending an email in the first contact. Some new mechanisms are employed in our scheme to reach a good balance between security against spam and convenience to normal email users. Our scheme can be also used for protecting other messaging systems, like Instant Messaging and Blog comments.

2022, 2008 Second International Conference on Communications and Electronics

2022, International Journal of Artificial Intelligence & Applications

Currently, spam and scams are passive attack over the inbox which can initiated to steal some confidential information, to spread Worms, Viruses, Trojans, cookies and Sometimes they are used for phishing attacks. Spam mails are the major issue over mail boxes as well as over the internet. Spam mails can be the cause of phishing attack, hacking of banking accounts, attacks on confidential data. Spamming is growing at a rapid rate since sending a flood of mails is easy and very cheap. Spam mails disturb the mind-peace, waste time and consume various resources e.g., memory space and network bandwidth, so filtering of spam mails is a big issue in cyber security. This paper presents an novel approach of spam filtering which is based on some query generated approach on the knowledge base and also use some artificial neural network methods to detect the spam mails based on their behavior. analysis of the mail header, cross validation. Proposed methodology includes the 7 several steps which are well defined and achieve the higher accuracy. It works well with all kinds of spam mails (text based spam as well as image spam). Our tested data and experiments results shows promising results, and spam's are detected out at least 98.17 % with 0.12% false positive.

2022, Lecture Notes in Computer Science

Spam is serious problem that affects email users (e.g. phishing attacks, viruses and time spent reading unwanted messages). We propose a novel spam email filtering approach based on network-level attributes (e.g. the IP sender geographic coordinates) that are more persistent in time when compared to message content. This approach was tested using two classifiers, Naive Bayes (NB) and Support Vector Machines (SVM), and compared against bag-of-words models and eight blacklists. Several experiments were held with recent collected legitimate (ham) and non legitimate (spam) messages, in order to simulate distinct user profiles from two countries (USA and Portugal). Overall, the network-level based SVM model achieved the best discriminatory performance. Moreover, preliminary results suggests that such method is more robust to phishing attacks.

2022

The increasing volume of unsolicited bulk email (also known as spam) has generated a need for reliable anti-spam filters. Machine learning techniques now days used to automatically filter the spam e-mail in a very successful rate. In this paper we review some of the most popular machine learning methods (Bayesian classification, k-NN, ANNs, SVMs, Artificial immune system and Rough sets) and of their applicability to the problem of spam Email classification. Descriptions of the algorithms are presented, and the comparison of their performance on the Spam Assassin spam corpus is presented. Electronic mail has eased communication methods for many organizations as well as individuals. This method is exploited for fraudulent gain by spammers through sending unsolicited emails. This article aims to present a method for detection of spam emails with machine learning algorithms that are optimized with bioinspired methods. A literature review is carried to explore the efficient methods applied on different datasets to achieve good results. An extensive research was done to implement machine learning models using Naïve Bayes, Support Vector Machine, Random Forest, Decision Tree and Multi-Layer Perceptron on seven different email datasets, along with feature extraction and pre-processing. The bio-inspired algorithms like Particle Swarm Optimization and Genetic Algorithm were implemented to optimize the performance of classifiers. Multinomial Naïve Bayes with Genetic Algorithm performed the best overall. The comparison of our results with other machine learning and bio-inspired models to show the best suitable model is also discussed.

2022, Proceedings of the 11th INDIACom; INDIACom-2017; IEEE Conference ID: 40353 2017 4th International Conference on “Computing for Sustainable Global Development”, 01st - 03rd March, 2017

Cloud computing is mainly used in companies and organizations. The reason for its high demand in the market is primarily because it requires less planning, allowing people to start with minimum use of resources, but gradually increases with the increase of demand in services. However, there are many issues related to the security of data in Cloud computing. Data security and Privacy in data are the two main concern by the researchers and clients who want to opt for Cloud computing. Therefore, an attempt is made in this paper to analyze the security challenges in cloud computing that will further provide a better understanding on the various security issues and detection of those security issues. This paper also illustrates the countermeasures that have been adopted by the Cloud S ervice Industries.