In this paper, we design an Anomaly Detection (AD) framework for mobile data traffic,
capable of identifying different types of anomalous events generated by flash crowds in …

Healthcare fraud is considered a challenge for many societies. Health care funding that
could be spent on medicine, care for the elderly or emergency room visits are instead lost to …

Automatic deception detection is a challenging issue since human behaviors are too
complex to establish any standard behavioral signs that would explicitly indicate that a …

The growing systems complexity calls for dedicated monitoring and data analysis strategies
aiming to detect faults, attacks and errors before they escalate into failures. Distributed and …

Cellular frustrated models have been developed to describe how the adaptive immune
system works. They are composed by independent agents that continuously pair and unpair …

In practice, the energy consumption of industrial equipment rises mostly due to wear and
tear, which might include leaks or faulty plant conditions. By using statistical techniques and …

Anomaly detection problems are particularly important in various real-word contest such as
fraud detection, finance, intrusion detection and cyber-security. Several methods that are …

During the last years of technological development, we are seeing exponential growth in the
number of Internet of Things (IoT) devices we interact with daily, which is leading to an …

1.1 Main Goals Data-driven techniques are gaining more and more ground becoming more
powerful and complex, capable of performing incredible tasks. On the other hand the …

Outlier detection is getting significant attention in the research field of big data. Detecting the
outlier is important in various applications such as communication, finance, fraud detection …