Wittel et al., 2004 - Google Patents
On Attacking Statistical Spam Filters.Wittel et al., 2004
View PDF- Document ID
- 7620641304004616712
- Author
- Wittel G
- Wu S
- Publication year
- Publication venue
- CEAS
External Links
- 238000001914 filtration 0 abstract description 18
Classifications
-
- 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
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/55—Detecting local intrusion or implementing counter-measures
- G06F21/56—Computer malware detection or handling, e.g. anti-virus arrangements
- G06F21/562—Static detection
- G06F21/563—Static detection by source code analysis
-
- 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
- G06F17/30634—Querying
-
- 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
- G06F17/30613—Indexing
- G06F17/30619—Indexing indexing structures
-
- 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
-
- 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
- G06F17/30861—Retrieval from the Internet, e.g. browsers
-
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Wittel et al. | On Attacking Statistical Spam Filters. | |
Nelson et al. | Misleading learners: Co-opting your spam filter | |
Lowd et al. | Good Word Attacks on Statistical Spam Filters. | |
Laskov et al. | Machine learning in adversarial environments | |
Liang et al. | Cracking classifiers for evasion: A case study on the Google's phishing pages filter | |
Egozi et al. | Phishing email detection using robust nlp techniques | |
Harikrishnan et al. | A machine learning approach towards phishing email detection | |
Sanz et al. | Email spam filtering | |
Sharma et al. | Spam mails filtering using different classifiers with feature selection and reduction technique | |
Stuart et al. | A neural network classifier for junk e-mail | |
Ma et al. | A novel spam email detection system based on negative selection | |
Seljan et al. | Information extraction from security-related datasets | |
Lemay et al. | Is eval () Evil: A study of JavaScript in PDF malware | |
Gómez Hidalgo et al. | Named entity recognition for web content filtering | |
Hershkop et al. | Identifying spam without peeking at the contents | |
Islam et al. | Machine learning approaches for modeling spammer behavior | |
Nmachi | Phishing mitigation techniques: A literature survey | |
Rajadesingan et al. | Comment spam classification in blogs through comment analysis and comment-blog post relationships | |
Yeh et al. | Near-duplicate mail detection based on url information for spam filtering | |
Cui | Detection and Analysis of Phishing Attacks | |
Adamkani et al. | A content filtering scheme in social sites | |
Pascariu et al. | Detecting Phishing Websites Through Domain and Content Analysis | |
Yamah | Detecting Spear-phishing Attacks using Machine Learning | |
Wosah et al. | Phishing mitigation techniques: A literature survey | |
Varghese et al. | An Integrated approach to spam filtering and incremental updation of spam corpus using data mining techniques with modified spell correction algorithm |