Search results for "Process"

The Camorra and protection rackets: the cost to business

2016

Based on the observations from the judicial and investigative evidence provided by prosecutors in Camorra areas in Italy, this investigation provides an estimate of the economic impact of extortion racket to businesses. In particular, the estimates refer to the total and average withdrawal of monetary amounts from the businesses victimised by Camorra clans. Further insights are provided in terms of economic activities mostly victimised, and specifically the construction sector, which is subject to a different type of extortion racket.

HyperWall: A Hypervisor for Detection and Prevention of Malicious Communication

2020

Malicious programs vary widely in their functionality, from key-logging to disk encryption. However, most malicious programs communicate with their operators, thus revealing themselves to various security tools. The security tools incorporated within an operating system are vulnerable to attacks due to the large attack surface of the operating system kernel and modules. We present a kernel module that demonstrates how kernel-mode access can be used to bypass any security mechanism that is implemented in kernel-mode. External security tools, like firewalls, lack important information about the origin of the intercepted packets, thus their filtering policy is usually insufficient to prevent c…

Deep in the Dark: A Novel Threat Detection System using Darknet Traffic

2019

This paper proposes a threat detection system based on Machine Learning classifiers that are trained using darknet traffic. Traffic destined to Darknet is either malicious or by misconfiguration. Darknet traffic contains traces of several threats such as DDoS attacks, botnets, spoofing, probes and scanning attacks. We analyse darknet traffic by extracting network traffic features from it that help in finding patterns of these advanced threats. We collected the darknet traffic from the network sensors deployed at SURFnet and extracted several network-based features. In this study, we proposed a framework that uses supervised machine learning and a concept drift detector. Our experimental res…

The regression Tsetlin machine: a novel approach to interpretable nonlinear regression

2019

Relying simply on bitwise operators, the recently introduced Tsetlin machine (TM) has provided competitive pattern classification accuracy in several benchmarks, including text understanding. In this paper, we introduce the regression Tsetlin machine (RTM), a new class of TMs designed for continuous input and output, targeting nonlinear regression problems. In all brevity, we convert continuous input into a binary representation based on thresholding, and transform the propositional formula formed by the TM into an aggregated continuous output. Our empirical comparison of the RTM with state-of-the-art regression techniques reveals either superior or on par performance on five datasets. Thi…

Seismic behavior of structures equipped with variable friction dissipative (VFD) systems

2021

Usually, to mitigate the stresses in framed structures, different strategies are used. Among them, base isolation, viscous/friction/metallic yielding dampers and tuned mass dumpers have been widely investigated. Fluid Viscous Dampers (FVD) probably result the most diffused for the simplicity in the applications. However, these type of dampers request limited interstorey drifts to avoid dangerous effects. Further, they have an elevate cost. On the contrary, friction dampers are not so expensive but request high interstorey drifts to give a significant contribute in the dissipation of energy during an earthquake. In this paper an approach for the energy dissipation by friction, modified with …

On Detection of Network-Based Co-residence Verification Attacks in SDN-Driven Clouds

2017

Modern cloud environments allow users to consume computational and storage resources in the form of virtual machines. Even though machines running on the same cloud server are logically isolated from each other, a malicious customer can create various side channels to obtain sensitive information from co-located machines. In this study, we concentrate on timely detection of intentional co-residence attempts in cloud environments that utilize software-defined networking. SDN enables global visibility of the network state which allows the cloud provider to monitor and extract necessary information from each flow in every virtual network in online mode. We analyze the extracted statistics on d…

Image-Evoked Affect and its Impact on Eeg-Based Biometrics

2019

Electroencephalography (EEG) signals provide a representation of the brain’s activity patterns and have been recently exploited for user identification and authentication due to their uniqueness and their robustness to interception and artificial replication. Nevertheless, such signals are commonly affected by the individual’s emotional state. In this work, we examine the use of images as stimulus for acquiring EEG signals and study whether the use of images that evoke similar emotional responses leads to higher identification accuracy compared to images that evoke different emotional responses. Results show that identification accuracy increases when the system is trained with EEG recordin…

ES1D: A Deep Network for EEG-Based Subject Identification

2017

Security systems are starting to meet new technologies and new machine learning techniques, and a variety of methods to identify individuals from physiological signals have been developed. In this paper, we present ESID, a deep learning approach to identify subjects from electroencephalogram (EEG) signals captured by using a low cost device. The system consists of a Convolutional Neural Network (CNN), which is fed with the power spectral density of different EEG recordings belonging to different individuals. The network is trained for a period of one million iterations, in order to learn features related to local patterns in the spectral domain of the original signal. The performance of the…

The maturity of integrated care systems: lessons learned in using the SCIROCCO tool across Europe

2018

Two-qubit entanglement dynamics for two different non-Markovian environments

2009

We study the time behavior of entanglement between two noninteracting qubits each immersed in its own environment for two different non-Markovian conditions: a high-$Q$ cavity slightly off-resonant with the qubit transition frequency and a nonperfect photonic band-gap, respectively. We find that revivals and retardation of entanglement loss may occur by adjusting the cavity-qubit detuning, in the first case, while partial entanglement trapping occurs in non-ideal photonic-band gap.