ASK: Active Spam Killer
نویسنده
چکیده
We present Active Spam Killer (ASK), a program that attempts to validate unknown senders before allowing delivery of their message. Validation occurs by means of a challenge reply sent to senders who are not yet known to the system. Messages are kept in a queue pending confirmation until the sender replies to the challenge. Further messages coming from confirmed senders are delivered immediately. In a sample of 1000 spam mails, ASK was 99.7% effective at blocking spam, resulting in only 3 spam messages being delivered. Other programs’ best ratios were 97.8% or as many as 22 spam messages delivered.
منابع مشابه
A Novel Method for Detecting Spam Email using KNN Classification with Spearman Correlation as Distance Measure
E-mail is the most prevalent methods for correspondence because of its availability, quick message exchange and low sending cost. Spam mail appears as a serious issue influencing this application today's internet. Spam may contain suspicious URL’s, or may ask for financial information as money exchange information or credit card details. Here comes the scope of filtering spam from legitimate em...
متن کاملSpamCooling: A Parallel Heterogeneous Ensemble Spam Filtering System Based on Active Learning Techniques
Anti-spam technology is developing rapidly in recent years. With the emerging applications of machine learning in diverse fields, researchers as well as manufacturers around the world have attempted a large number of related algorithms to prevent spam. In this paper, we designed an effective anti-spam protection system, SpamCooling, based on the mechanism of active learning and parallel heterog...
متن کاملActive Multi-Field Learning for Spam Filtering
Ubiquitous spam messages cause a serious waste of time and resources. This paper addresses the practical spam filtering problem, and proposes a universal approach to fight with various spam messages. The proposed active multi-field learning approach is based on: 1) It is cost-sensitive to obtain a label for a realworld spam filter, which suggests an active learning idea; and 2) Different messag...
متن کاملActive Learning Image Spam Hunter
Image spam is annoying email users around the world. Most previous work for image spam detection focuses on supervised learning approaches. However, it is costly to get enough trustworthy labels for learning, especially for an adversarial problem where spammers constantly modify patterns to evade the classifier. To address this issue, we employ the principle of active learning where the learner...
متن کاملOnline Active Learning Methods for Fast Label-Efficient Spam Filtering
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustworthy labels for messages may be costly to acquire. Past investigations of active learning in spam filtering have focused on the pool-based scenario, where there is assumed to be a large, unlabeled data set and the goal...
متن کامل