Add to ORKGMobile communication networks produce massive amounts of data which may be useful in identifying the location of an emergency situation and the area it affects. We propose a one pass clustering algorithm’s for quickly identifying anomalous data points. We evaluate this algorithms ability to detect outliers in a data set and describe how such an algorithm may be used as a component of an emergency response management system.
The increasing complexity of cellular radio networks yields new demands concerning network security....
We propose an unsupervised learning based anomaly detection framework for identifying cells experien...
In the past couple of years, sensor networks have evolved into an important infrastructure component...
Functioning mobile telecommunication networks are taken for granted in present-day society. The netw...
New security threats emerge against mobiledevices as the devices’ computing power and storagecapabil...
Huge amounts of operation data are constantly collected from the performance monitoring and system l...
Leveraging the ICT evolution, the modern systems collect voluminous sets of monitoring data, which a...
Anomaly detection has always been the focus of researchers and especially, the developments of mobil...
Mobile networks represent a considerable industry globally and are known to rely on robust and highl...
This paper proposes an anomaly detection framework that utilizes key performance indicators (KPIs) a...
International audienceAnalysing mobile apps communications can unleash significant information on bo...
The use of mobile phones has exploded over the past years, abundantly through the introduction of sm...
Recent studies have shown that a number of network attacks that were used to target mainframes and p...
Anomaly detection has become more and more difficult for telecommunication network due to the variou...
Among the smart capabilities promised by the next generation cellular networks (5G and beyond), it i...
The increasing complexity of cellular radio networks yields new demands concerning network security....
We propose an unsupervised learning based anomaly detection framework for identifying cells experien...
In the past couple of years, sensor networks have evolved into an important infrastructure component...
Functioning mobile telecommunication networks are taken for granted in present-day society. The netw...
New security threats emerge against mobiledevices as the devices’ computing power and storagecapabil...
Huge amounts of operation data are constantly collected from the performance monitoring and system l...
Leveraging the ICT evolution, the modern systems collect voluminous sets of monitoring data, which a...
Anomaly detection has always been the focus of researchers and especially, the developments of mobil...
Mobile networks represent a considerable industry globally and are known to rely on robust and highl...
This paper proposes an anomaly detection framework that utilizes key performance indicators (KPIs) a...
International audienceAnalysing mobile apps communications can unleash significant information on bo...
The use of mobile phones has exploded over the past years, abundantly through the introduction of sm...
Recent studies have shown that a number of network attacks that were used to target mainframes and p...
Anomaly detection has become more and more difficult for telecommunication network due to the variou...
Among the smart capabilities promised by the next generation cellular networks (5G and beyond), it i...
The increasing complexity of cellular radio networks yields new demands concerning network security....
We propose an unsupervised learning based anomaly detection framework for identifying cells experien...
In the past couple of years, sensor networks have evolved into an important infrastructure component...