On the security of pay-per-click and other Web advertising schemes
WWW '99 Proceedings of the eighth international conference on World Wide Web
Secure and lightweight advertising on the Web
WWW '99 Proceedings of the eighth international conference on World Wide Web
A Survey of Indexing Techniques for Sparse Matrices
ACM Computing Surveys (CSUR)
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
SAWM: a tool for secure and authenticated web metering
SEKE '02 Proceedings of the 14th international conference on Software engineering and knowledge engineering
Finding Frequent Items in Data Streams
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Frequency Estimation of Internet Packet Streams with Limited Space
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Defending Against the Wily Surfer-Web-based Attacks and Defenses
Proceedings of the Workshop on Intrusion Detection and Network Monitoring
A simple algorithm for finding frequent elements in streams and bags
ACM Transactions on Database Systems (TODS)
What's hot and what's not: tracking most frequent items dynamically
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
New directions in traffic measurement and accounting: Focusing on the elephants, ignoring the mice
ACM Transactions on Computer Systems (TOCS)
Dynamically maintaining frequent items over a data stream
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Diamond in the rough: finding Hierarchical Heavy Hitters in multi-dimensional data
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Duplicate detection in click streams
WWW '05 Proceedings of the 14th international conference on World Wide Web
Using association rules for fraud detection in web advertising networks
VLDB '05 Proceedings of the 31st international conference on Very large data bases
An integrated efficient solution for computing frequent and top-k elements in data streams
ACM Transactions on Database Systems (TODS)
Detectives: detecting coalition hit inflation attacks in advertising networks streams
Proceedings of the 16th international conference on World Wide Web
The Zombie roundup: understanding, detecting, and disrupting botnets
SRUTI'05 Proceedings of the Steps to Reducing Unwanted Traffic on the Internet on Steps to Reducing Unwanted Traffic on the Internet Workshop
Detecting hit shaving in click-through payment schemes
WOEC'98 Proceedings of the 3rd conference on USENIX Workshop on Electronic Commerce - Volume 3
On Hit Inflation Techniques and Detection in Streams of Web Advertising Networks
ICDCS '07 Proceedings of the 27th International Conference on Distributed Computing Systems
Approximate frequency counts over data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Finding hierarchical heavy hitters in data streams
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
The dark side of the Internet: Attacks, costs and responses
Information Systems
Estimating the number of users behind ip addresses for combating abusive traffic
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
V-SMART-join: a scalable mapreduce framework for all-pair similarity joins of multisets and vectors
Proceedings of the VLDB Endowment
Measuring and fingerprinting click-spam in ad networks
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Measuring and fingerprinting click-spam in ad networks
ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
ViceROI: catching click-spam in search ad networks
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
DECAF: detecting and characterizing ad fraud in mobile apps
NSDI'14 Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation
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Several data management challenges arise in the context of Internet advertising networks, where Internet advertisers pay Internet publishers to display advertisements on their Web sites and drive traffic to the advertisers from surfers' clicks. Although advertisers can target appropriate market segments, the model allows dishonest publishers to defraud the advertisers by simulating fake traffic to their own sites to claim more revenue. This paper addresses the case of publishers launching fraud attacks from numerous machines, which is the most widespread scenario. The difficulty of uncovering these attacks is proportional to the number of machines and resources exploited by the fraudsters. In general, detecting this class of fraud entails solving a new data mining problem, which is finding correlations in multidimensional data. Since the dimensions have large cardinalities, the search space is huge, which has long allowed dishonest publishers to inflate their traffic, and deplete the advertisers' advertising budgets. We devise the approximate SLEUTH algorithms to solve the problem efficiently, and uncover single-publisher frauds. We demonstrate the effectiveness of SLEUTH both analytically and by reporting some of its results on the Fastclick network, where numerous fraudsters were discovered.