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System states that are anomalous from the perspective of a domain expert occur frequently in some anomaly detection problems. The performance of commonly used unsupervised anomaly detection methods may suffer in that setting, because they…

The worldwide growth of maritime traffic and the development of the Automatic Identification System (AIS) has led to advances in monitoring systems for preventing vessel accidents and detecting illegal activities. In this work, we describe…

In this paper, we propose a novel distributed algorithm for consensus optimization over networks and a robust extension tailored to deal with asynchronous agents and packet losses. Indeed, to robustly achieve dynamic consensus on the…

Poor security of Internet routing enables adversaries to divert user data through unintended infrastructures (hijack). Of particular concern -- and the focus of this paper -- are cases where attackers reroute domestic traffic through…

Electrical substations are becoming more prone to cyber-attacks due to increasing digitalization. Prevailing defense measures based on cyber rules are often inadequate to detect attacks that use legitimate-looking measurements. In this…

Public transit systems in urban areas usually require large state subsidies, primarily due to high fare evasion rates. In this paper, we study new models for optimizing fare inspection strategies in transit networks based on bilevel…

Money laundering has become one of the most relevant criminal activities in modern societies, as it causes massive financial losses for governments, banks and other institutions. Detecting such activities is among the top priorities when it…

Automated fraud behaviors detection on electronic payment platforms is a tough problem. Fraud users often exploit the vulnerability of payment platforms and the carelessness of users to defraud money, steal passwords, do money laundering,…

Collusion and capacity withholding in electricity wholesale markets are important mechanisms of market manipulation. This study applies a refined machine learning-based cartel detection algorithm to two cartel cases in the Italian…

International trade research plays an important role to inform trade policy and shed light on wider issues relating to poverty, development, migration, productivity, and economy. With recent advances in information technology, global and…

Crime generates significant losses, both human and economic. Every year, billions of dollars are lost due to attacks, crimes, and scams. Surveillance video camera networks are generating vast amounts of data, and the surveillance staff can…

In multi-hop mobile ad hoc networks (MANETs),mobile nodes cooperate with each other without using any infrastructure such as access points or base stations. Security remains a major challenge for these networks due to their features of open…

The interdependent nature of the global economy has become stronger with increases in international trade and investment. We propose a new model to reconstruct the international trade network and associated cost network by maximizing…

Business processes are prone to unexpected changes, as process workers may suddenly or gradually start executing a process differently in order to adjust to changes in workload, season, or other external factors. Early detection of business…

This paper proposes an active model-based fault and failure tolerant control scheme for a class of marine vehicles with thruster redundancy. Unlike widely used state and parameter estimation methods, where the estimation errors are utilized…

Deploying robust machine learning models has to account for concept drifts arising due to the dynamically changing and non-stationary nature of data. Addressing drifts is particularly imperative in the security domain due to the…

An explicit rate indication scheme for congestion avoidance in computer and telecommunication networks is proposed. The sources monitor their load and provide the information periodically to the switches. The switches, in turn, compute the…

Accurate and timely detection of cyber threats is critical to keeping our online economy and data safe. A key technique in early detection is the classification of unusual patterns of network behaviour, often hidden as low-frequency events…

Anomaly detection is an essential task in the analysis of dynamic networks, offering early warnings of abnormal behavior. We present a principled approach to detect anomalies in dynamic networks that integrates community structure as a…

Backdoor attacks allow an attacker to embed functionality jeopardizing proper behavior of any algorithm, machine learning or not. This hidden functionality can remain inactive for normal use of the algorithm until activated by the attacker.…