Abstract — In this paper we present a distributed mechanism based on Principal Component Analysis (PCA) to profile the behavior of the legitimate users in telephone networks. The idea is to take advantage of probes distributed over the network to ob-tain a compact snapshot of the users they serve. A collector node effectively combines such information to gather the description of the legitimate-user behavior. Eventually, it distributes the profile to the probes, which perform anomaly detection. Experimental results on several weeks of phone data collected by a telecom operator show that our profiling mechanism is stable over time and allows an operator to decentralize the anomaly detection stage directly to its probes. Furthermore, when com...
Thesis (Ph.D.)--Boston UniversityPLEASE NOTE: Boston University Libraries did not receive an Authori...
Third generation (3G) mobile networks rely on distributed architectures where Operation and Maintena...
Users increasingly rely on crowdsourced information, such as reviews on Yelp and Amazon, and liked p...
In this paper we present a distributed mechanism based on Principal Component Analysis (PCA) to prof...
We consider the problem of network anomaly detection in large distributed systems. In this setting, ...
Principal component analysis and the residual error is an effective anomaly detection technique. In ...
Summarization: There has been growing interest in building large-scale distributed monitoring system...
As the number, complexity and diversity of cyber threats continue to increase in network infrastruct...
Anomaly detection in telecommunications data tries to discover deviant behaviour of individual subsc...
Detecting anomalous traffic is a crucial part of managing IP networks. In recent years, network-wide...
Nowadays, organization networks are facing an increased number of different attacks and existing int...
Statistical anomaly detection (SAD) is an important component of securing modern networks facing con...
Statistical Machine Learning methods are employed to improve network security (email spam filtering,...
In this report we present a rule-based approach to detect anomalous telephone calls. The method desc...
International audienceThe crucial future role of Internet in society makes of network monitoring a c...
Thesis (Ph.D.)--Boston UniversityPLEASE NOTE: Boston University Libraries did not receive an Authori...
Third generation (3G) mobile networks rely on distributed architectures where Operation and Maintena...
Users increasingly rely on crowdsourced information, such as reviews on Yelp and Amazon, and liked p...
In this paper we present a distributed mechanism based on Principal Component Analysis (PCA) to prof...
We consider the problem of network anomaly detection in large distributed systems. In this setting, ...
Principal component analysis and the residual error is an effective anomaly detection technique. In ...
Summarization: There has been growing interest in building large-scale distributed monitoring system...
As the number, complexity and diversity of cyber threats continue to increase in network infrastruct...
Anomaly detection in telecommunications data tries to discover deviant behaviour of individual subsc...
Detecting anomalous traffic is a crucial part of managing IP networks. In recent years, network-wide...
Nowadays, organization networks are facing an increased number of different attacks and existing int...
Statistical anomaly detection (SAD) is an important component of securing modern networks facing con...
Statistical Machine Learning methods are employed to improve network security (email spam filtering,...
In this report we present a rule-based approach to detect anomalous telephone calls. The method desc...
International audienceThe crucial future role of Internet in society makes of network monitoring a c...
Thesis (Ph.D.)--Boston UniversityPLEASE NOTE: Boston University Libraries did not receive an Authori...
Third generation (3G) mobile networks rely on distributed architectures where Operation and Maintena...
Users increasingly rely on crowdsourced information, such as reviews on Yelp and Amazon, and liked p...