Search results for "Defence"

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…

Secure and Privacy Preserving Pattern Matching in Distributed Cloud-based Data Storage

2019

Given two strings: pattern $p$ of length $m$ and text $t$ of length $n$ . The string matching problem is to find all (or some) occurrences of the pattern $p$ in the text $t$ . We introduce a new simple data structure, called index arrays, and design fast privacy-preserving matching algorithm for string matching. The motivation behind introducing index arrays is determined by the need for pattern matching on distributed cloud-based datasets with semi-trusted cloud providers. It is intended to use encrypted index arrays both to improve performance and protect confidentiality and privacy of user data.

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…

Soils from an iron and steel scrap storage yard remediated with aided phytostabilization

2018

The role of extracellular polymeric substances (EPS) on aerobic granules formation: comparison between a case of synthetic wastewater supply and anot…

2017

The paper focused on the evolution and the comparison of the extracellular polymeric substances (EPSs) content during the granulation process in two Granular Sequencing Batch Airlift Reactors (GSBAR) (3,5 L) fed with synthetic (R1) and industrial wastewater (R2). The results showed that in both the reactors the EPSs, in particular proteins (PN), were mainly produced during the feast phase because of the high substrate availability, especially under conditions of metabolic stress. Then, the EPSs content reduced during the famine period, because of biodegradation by bacteria. More in detail, during the granulation process, a greater polysaccharides (PS) consumption occurred in both reactors, …

Role of particle characteristics in the compression behaviour of gap-graded sands

2019

Abstract The compression in gap-graded mixtures of sands with combined mineralogy has been investigated in recent research, focusing on the key factors that might imply the occurrence of convergent or non-convergent paths in compression (i.e., transitional or non-transitional behaviour). From previous work, the mineralogy of a matrix composed of larger grains seems to determine the possibility of the occurrence of transitional behaviour. Hence, if there is a strong and stiff matrix made of quartz sand particles, which are either larger than or at least of similar size to the other component, then non-convergent compression paths (i.e., transitional behaviour) are likely to occur. As a furth…

Automatic Integration of Spatial Data into the Semantic Web

2017

International audience

Self-validating bundles for flexible data access control

2016

Modern cloud-based services offer free or low-cost content sharing with significant advantages for the users but also new issues in privacy and security. To protect sensitive contents (i.e., copyrighted, top secret, and personal data) from the unauthorized access, sophisticated access management systems or/and decryption schemes have been proposed, generally based on trusted applications at client side. These applications work also as access controllers, verifying specific permissions and restrictions accessing user’s resources. We propose secure bundles (S-bundles), which encapsulate a behavioral model (provided as bytecode) to define versatile stand-alone access controllers and encoding/d…

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…