Journal ArticleDOI
Fraud Detection in Telecommunications: History and Lessons Learned.
TLDR
The history of fraud detection at AT&T is reviewed, one of the first companies to address fraud in a systematic way to protect its revenue stream and the use of simple, understandable models, heavy use of visualization, and a flexible environment are advocated.Abstract:
Fraud detection is an increasingly important and difficult task in today’s technological environment. As consumers are putting more of their personal information online and transacting much more business over computers, the potential for losses from fraud is in the billions of dollars, not to mention the damage done by identity theft. This paper reviews the history of fraud detection at AT&T, one of the first companies to address fraud in a systematic way to protect its revenue stream. We discuss some of the major fraud schemes and the techniques used to address them, leading to generic conclusions about fraud detection. Specifically, we advocate the use of simple, understandable models, heavy use of visualization, and a flexible environment and emphasize the importance of data management and the need to keep humans in the loop.read more
Citations
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Book ChapterDOI
An Overview of Concept Drift Applications
TL;DR: This chapter provides an application oriented view towards concept drift research, with a focus on supervised learning tasks, and constructs a reference framework for positioning application tasks within a spectrum of problems related to concept drift.
Journal ArticleDOI
A principle component analysis-based random forest with the potential nearest neighbor method for automobile insurance fraud identification
TL;DR: In this paper, individual classifiers are appropriately combined and a multiple classifier system with an increase in classification accuracy is presented and a new voting mechanism based on Potential Nearest Neighbor is presented to replace the traditional majority vote.
Book ChapterDOI
Inferring Strange Behavior from Connectivity Pattern in Social Networks
TL;DR: A complete graph from a large who-follows-whom network is studied and it is discovered that the lockstep behavior on the graph shapes dense “block” in its adjacency matrix and creates “ray" in spectral subspaces.
Journal ArticleDOI
Social engineering in cybersecurity: The evolution of a concept
TL;DR: It is argued that while the term began its life in the study of politics, and only later gained usage within the domain of cybersecurity, these are applications of the same fundamental ideas: epistemic asymmetry, technocratic dominance, and teleological replacement.
Proceedings ArticleDOI
SoK: Fraud in Telephony Networks
TL;DR: The taxonomy differentiates the root causes, the vulnerabilities, the exploitation techniques, the fraud types and the way fraud benefits fraudsters and uses CAller NAMe (CNAM) revenue share fraud as an example to illustrate how the taxonomy helps in better understanding fraud and to mitigate it.
References
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