Iyengar et al., 2017 - Google Patents
Integrated SPAM detection for multilingual emailsIyengar et al., 2017
- Document ID
- 11007005169605785632
- Author
- Iyengar A
- Kalpana G
- Kalyankumar S
- GunaNandhini S
- Publication year
- Publication venue
- 2017 International Conference on Information Communication and Embedded Systems (ICICES)
External Links
Snippet
Emails and social communication is the newest and easiest way of data communication. Although Electronic communications are facile in nature, it is equally easy to attack these services with an intention of fraud and trickery motivation. The cyberpunks use emails to …
- 238000001514 detection method 0 title description 9
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/54—Store-and-forward switching systems
- H04L12/58—Message switching systems, e.g. electronic mail systems
- H04L12/585—Message switching systems, e.g. electronic mail systems with filtering and selective blocking capabilities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
- G06Q10/107—Computer aided management of electronic mail
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/30707—Clustering or classification into predefined classes
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—Arrangements for user-to-user messaging in packet-switching networks, e.g. e-mail or instant messages
- H04L51/12—Arrangements for user-to-user messaging in packet-switching networks, e.g. e-mail or instant messages with filtering and selective blocking capabilities
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/54—Store-and-forward switching systems
- H04L12/58—Message switching systems, e.g. electronic mail systems
- H04L12/5885—Message switching systems, e.g. electronic mail systems with provisions for tracking the progress of a message
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1425—Traffic logging, e.g. anomaly detection
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—Arrangements for user-to-user messaging in packet-switching networks, e.g. e-mail or instant messages
- H04L51/28—Details regarding addressing issues
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Rathod et al. | Content based spam detection in email using Bayesian classifier | |
Bergholz et al. | Improved Phishing Detection using Model-Based Features. | |
US8489689B1 (en) | Apparatus and method for obfuscation detection within a spam filtering model | |
Subramaniam et al. | Overview of textual anti-spam filtering techniques | |
Iyengar et al. | Integrated SPAM detection for multilingual emails | |
Nosseir et al. | Intelligent word-based spam filter detection using multi-neural networks | |
Rathod et al. | A comparative performance evaluation of content based spam and malicious URL detection in E-mail | |
Christina et al. | A study on email spam filtering techniques | |
Mallampati et al. | A machine learning based email spam classification framework model: related challenges and issues | |
Khan et al. | Text mining approach to detect spam in emails | |
Lee et al. | An online subject-based spam filter using natural language features | |
Mujtaba et al. | Detection of suspicious terrorist emails using text classification: A review | |
Roy et al. | An efficient spam filtering techniques for email account | |
Kågström | Improving naive bayesian spam filtering | |
Chiu et al. | An alliance-based anti-spam approach | |
Issac et al. | Improved Bayesian anti-spam filter implementation and analysis on independent spam corpuses | |
Mathew et al. | Analyzing the effectiveness of N-gram technique based feature set in a Naive Bayesian spam filter | |
Tham et al. | Phishing message detection based on keyword matching | |
Rawat et al. | A real time spam classification of twitter data with comparative analysis of classifiers | |
Hershkop et al. | Identifying spam without peeking at the contents | |
Glymin et al. | Rough set approach to spam filter learning | |
Adamkani et al. | A content filtering scheme in social sites | |
Jain et al. | A hybrid approach for spam filtering using local concentration based K-means clustering | |
Salim | Using decision tree algorithms in detecting spam emails written in Malay: A comparison study | |
Pera et al. | SpamED: A spam E‐mail detection approach based on phrase similarity |