The explosive growth in social networks that publish real-time content begs the question of whether their feeds can complement traditional sensors to achieve augmented sensing capabilities. One such capability is to explain anomalous sensor readings. Towards that end, in this work, we build an automated anomaly clarification service, called ClariSense. It explains sensor anomalies using social ...

Given a large social graph, like a scientific collaboration network, what can we say about its robustness? Can we estimate a robustness index for a graph quickly? If the graph evolves over time, how these properties change? In this work, we are trying to answer the above questions studying the expansion properties of large social graphs. First, we present a measure which characterizes the robus...

Online social networks can be modelled as graphs; in this paper, we analyze the use of graph metrics for identifying users with anomalous relationships to other users. A framework is proposed for analyzing the effectiveness of various graph theoretic properties such as the number of neighbouring nodes and edges, betweenness centrality, and community cohesiveness in detecting anomalous users. Ex...

This paper is concerned with the asymptotic behavior of solutions of stochastic differential equations dyt = dωt − ∇V (yt ) dt , y0 = 0. When d = 1 and V is not periodic but obtained as a superposition of an infinite number of periodic potentials with geometrically increasing periods [V (x)= ∑∞ k=0 Uk(x/Rk), where Uk are smooth functions of period 1, Uk(0)= 0, and Rk grows exponentially fast wi...

Sensors and Internet-of-Things scenarios promise a wealth of interaction data that can be naturally represented by means of timevarying graphs. This brings forth new challenges for the identification and removal of temporal graph anomalies that entail complex correlations of topological features and activity patterns. Here we present an anomaly detection approach for temporal graph data based o...

This paper is concerned with the asymptotic behavior solutions of stochastic differential equations dyt = dωt − ∇V (yt)dt, y0 = 0. When d = 1 and V reflects media characterized by an infinite number of spatial scales V (x) = ∞ k=0 Uk(x/Rk), where Uk are smooth functions of period 1, Uk(0) = 0, and Rk grows exponentially fast with k, we can show that yt has an anomalous slow behavior and obtain ...