No NAT'd User left Behind: Fingerprinting Users behind NAT from NetFlow Records alone

It is generally recognized that the traffic generated by an individual connected to a network acts as his biometric signature. Several tools exploit this fact to fingerprint and monitor users. Often, though, these tools assume to access the entire traffic, including IP addresses and payloads. This is not feasible on the grounds that both performance and privacy would be negatively affected. In reality, most ISPs convert user traffic into NetFlow records for a concise representation that does not include, for instance, any payloads. More importantly, large and distributed networks are usually NAT'd, thus a few IP addresses may be associated to thousands of users. We devised a new fingerprinting framework that overcomes these hurdles. Our system is able to analyze a huge amount of network traffic represented as NetFlows, with the intent to track people. It does so by accurately inferring when users are connected to the network and which IP addresses they are using, even though thousands of users are hidden behind NAT. Our prototype implementation was deployed and tested within an existing large metropolitan WiFi network serving about 200,000 users, with an average load of more than 1,000 users simultaneously connected behind 2 NAT'd IP addresses only. Our solution turned out to be very effective, with an accuracy greater than 90%. We also devised new tools and refined existing ones that may be applied to other contexts related to NetFlow analysis

Trace class operators and states in p-adic quantum mechanics

Within the framework of quantum mechanics over a quadratic extension of the non-Archimedean field of p-adic numbers, we provide a definition of a quantum state relying on a general algebraic approach and on a p-adic model of probability theory. As in the standard complex case, a distinguished set of physical states are related to a notion of trace for a certain class of bounded operators and, in fact, we show that one can define a suitable space of trace class operators in the non-Archimedean setting, as well. The analogies, but also the several (highly non-trivial) differences, with respect to the case of standard quantum mechanics in a complex Hilbert space are analyzed.Comment: 70 pages; minor changes, typos correcte

Numerical approach to modelling pulse mode soil flushing on a Pb-contaminated soil

4noPurpose: Soil flushing can represent a suitable technology in remediation of soils, sediments and sludge contaminated by persistent species (e.g. toxic metal). This paper presents a model specifically developed to evaluate the feasibility of chelating agent-enhanced flushing. The model, here applied to the remediation of real Pb-contaminated soils, was conceived also to simulate an innovative pulse-mode soil flushing technique. Materials and methods: The soil flushing application was firstly carried out through columns laboratory experiments. Columns were filled with a real Pb-contaminated soil (3,000 mg kg−1 of dry soil) and flushing was operated in a pulse mode with different chelating agent dosages (3 and 4.3 mmol kg−1soil). Experimental results were used to calibrate and validate the developed reactive transport model that accounts for transport of ethylenediamine tetraacetic acid (EDTA) and EDTA–Pb chelate complexes, Pb residual concentration on soil and the reduction in permeability by soil dissolution. Determination of hydrodynamic and hydrodispersive parameters was carried out through a numerical approach incorporating the use of neural network as interpolating function of breakthrough data obtained by a tracer test. Results and discussion: The EDTA dosage strongly influenced the efficiency in Pb extraction and soil permeability. Cumulative extractions of Pb were found to be 20 and 29 % for the EDTA concentrations of 3 and 4.3 mmol/kg of dry soil, respectively. The soil dissolution caused a significant flow rate decrease, as a consequence of the increase in chelating agent concentration. Therefore the recovery phase duration increased from 738 to 2,080 h. The ability of the model in simulating all the examined phenomena is confirmed by a good fit with experimental results in terms of (a) soil permeability reduction, (b) eluted Pb and (c) residual Pb in the soil. Conclusions: Results highlighted as the model, supported by a preliminary and careful characterization of the soil, can be useful to assess the feasibility of the flushing treatment (avoiding soil clogging) and to address the choice of the operating parameters (flow rate, chelating agent dosage and application method). On the basis of the present research results, a protocol is suggested for in situ soil pulse–flushing application.openLuciano, A.; Viotti, P.; Torretta, V.; Mancini, G.Luciano, A.; Viotti, P.; Torretta, Vincenzo; Mancini, G

Benchmark Structures and Conformational Landscapes of Amino Acids in the Gas Phase: A Joint Venture of Machine Learning, Quantum Chemistry, and Rotational Spectroscopy

The accurate characterization of prototypical bricks of life can strongly benefit from the integration of high resolution spectroscopy and quantum mechanical computations. We have selected a number of representative amino acids (glycine, alanine, serine, cysteine, threonine, aspartic acid and asparagine) to validate a new computational setup rooted in quantum-chemical computations of increasing accuracy guided by machine learning tools. Together with low-lying energy minima, the barriers ruling their interconversion are evaluated in order to unravel possible fast relaxation paths. Vibrational and thermal effects are also included in order to estimate relative free energies at the temperature of interest in the experiment. The spectroscopic parameters of all the most stable conformers predicted by this computational strategy, which do not have low-energy relaxation paths available, closely match those of the species detected in microwave experiments. Together with their intrinsic interest, these accurate results represent ideal benchmarks for more approximate methods

Fast exploration of potential energy surfaces with a joint venture of quantum chemistry, evolutionary algorithms and unsupervised learning

Contemporary molecular spectroscopy allows the study of flexible molecules, whose conformational behavior is ruled by flat potential energy surfaces (PESs) involving a large number of energy minima with comparable stability. Under such circumstances assignment and interpretation of the spectral signatures can strongly benefit from quantum chemical computations, which face, however, several difficulties. In particular, the mandatory characterization of all the relevant energy minima leads to a huge increase in the number of accurate quantum chemical computations (which may even hamper the feasibility of a study) and the intricate couplings among several soft degrees of freedom can defy simple heuristic approaches and chemical intuition. From this point of view, the exploration of flat PESs is akin to other optimization problems and can be tackled with suitable metaheuristics, which can drive QC computations by reducing the number of necessary calculations and providing effective routes to sample the most relevant regions of the PES. Unfortunately, in spite of the significant reduction of the number of QC calculations, a brute-force approach based on state-of-the-art methods remains infeasible. This problem can be solved effectively by multi-level strategies combining methods of different accuracy in the first PES exploration, refinement of the structures of the most important stationary points and computation of spectroscopic parameters. Building on previous experience, in this contribution we introduce new improvements in an evolutionary algorithm based method using curvilinear coordinates for both intra- and inter-molecular interactions. Two test cases will be analyzed in detail, namely aspartic acid in the gas-phase and the silver cation in aqueous solution. Comparison between fully a priori computed spectroscopic parameters and the experimental counterparts will provide an unbiased validation of the proposed strategy

A Novel Stealthy Attack to Gather SDN Configuration-Information

Software Defined Networking (SDN) is a recent network architecture based on the separation of forwarding functions from network logic, and provides high flexibility in the management of the network. In this paper, we show how an attacker can exploit SDN programmability to obtain detailed knowledge about the network behaviour. In particular, we introduce a novel attack, named Know Your Enemy (KYE), which allows an attacker to gather vital information about the configuration of the network. Through the KYE attack, an attacker can obtain information ranging from the configuration of security tools, such as attack detection thresholds for network scanning, to general network policies like QoS and network virtualization. Additionally, we show that the KYE attack can be performed in a stealthy fashion, allowing an attacker to learn configuration secrets without being detected. We underline that the vulnerability exploited by the KYE attack is proper of SDN and is not present in legacy networks. Finally, we address the KYE attack by proposing an active defense countermeasure based on network flows obfuscation, which considerably increases the complexity for a successful attack. Our solution offers provable security guarantees that can be tailored to the needs of the specific network under consideration

Reliability issues in the design of distributed object-based architectures

PhD ThesisThis thesis is aimed at enhancing the existing set of techniques for building distributed systems, specifically from the point of view of fault-tolerant com- puting. Reliability is of fundamental importance in the design and operation of dis- tributed systems, as an increasing number of computers are employed in the automation of various essential services. In the past decade, much research effort has been concerned with the object-based methodology for the design and implementation of reliable distributed systems. This thesis describes three contributions to this effort. First, it is shown that object-based programming features can in fact be introduced into pro- cedural languages provided that these languages are endowed with certain facilities. Then, work is discussed which illustrates the relationship between distributed object-based architectures and an apparently different form of distributed architectures based on processes. This work puts the notion of object-based architectures into a new perspective, which shows that the object-based philosophy and the process-based philosophy are the dual of each other. Finally, an important aspect of the design of an object-based distributed architecture is investigated, that of automatic garbage collection. A distri- buted garbage collection scheme is described that handles fault tolerance by an extension of the technique commonly employed to detect unwanted com- putations in distributed architectures. The scheme proposed can also be seen as yet a further illustration of the link between object-based and process-based architectures.Royal Signals and Radar Establishment of the U.K. Ministry of Defence. Italian Consiglio Nazionale delle Ricerch

An Overview of Stepped Hull Performance Evaluation: Sea Trial Data vs Full-Scale CFD Simulation

It is well known that the dynamic of the stepped hull in real scale is rather complex and it’s not easy to predict that using empirical or mathematical approaches, and by the numerical and experimental way as well. Moreover, there is a huge lack in the literature of data related to sea trials of the stepped hull. Furthermore, the reliability of full-scale CFD simulations is not widely proven and validated especially for high speed and planing hull. For these several reasons, in this paper, the authors are focused on the comparison of the results carried out from model experimental tests performed in the model basin, full-scale CFD simulations, and sea trial tests. The performed simulations in full-scale have been compared to the extrapolated experimental tests and the sea-trial results. Moreover, the dynamic trim angle and the dynamic wetted surface have been taken into account to assess the reliability of the full-scale simulation performed. The stepped hull considered is a Mito 31 outboard Rigid Inflatable Boat (RIB) built by MV Marine Srl Company

Assessment of Multi-Scale Approaches for ComputingUV–Vis Spectra in Condensed Phases: Toward an Effective yetReliable Integration of Variational and Perturbative QM/MM Approaches

Computational simulation of UV/vis spectra in condensed phases can be performed starting from converged molecular dynamics (MD) simulations and then performing quantum mechanical/molecular mechanical (QM/MM) computations for a statistically significant number of snapshots. However, the need of variational solutions (e.g., ONIOM/EE) for a huge number of snapshots makes unpractical the use of state-of-the-art QM Hamiltonians. On the other hand, the effectivity of perturbative approaches (e.g., perturbed matrix method, PMM) comes at the price of poor convergence for configurations strongly different from the reference one. In this paper we introduce an integrated strategy based on a cluster analysis of the MD snapshots. Next, a representative configuration for each cluster is treated at the ONIOM/EE level, whereas local fluctuations within each cluster are described at the PMM level. Some representative systems (uracil in dimethylformamide and in water and tyrosine zwitterion in water) are analyzed to show t..

Integration of Quantum Chemistry, Statistical Mechanics, and Artificial Intelligence for Computational Spectroscopy: The UV-Vis Spectrum of TEMPO Radical in Different Solvents

The ongoing integration of quantum chemistry, statistical mechanics, and artificial intelligence is paving the route toward more effective and accurate strategies for the investigation of the spectroscopic properties of medium-to-large size chromo-phores in condensed phases. In this context we are developing a novel workflow aimed at improving the generality, reliability, and ease of use of the available computational tools. In this paper we report our latest developments with specific reference to unsupervised atomistic simulations employing non periodic boundary conditions (NPBC) followed by clustering of the trajectories employing optimized feature spaces. Next accurate variational computations are performed for a representative point of each cluster, whereas intracluster fluctuations are taken into account by a cheap yet reliable perturbative approach. A number of methodological improvements have been introduced including, e.g., more realistic reaction field effects at the outer boundary of the simulation sphere, automatic definition of the feature space by continuous perception of solute-sol v e n t interactions, full account of polarization and charge transfer in the first solvation shell, and inclusion of vibronic contributions. After its validation, this new approach has been applied to the challenging case of solvatochromic effects on the UV-vis spectra of a prototypical nitroxide radical (TEMPO) in different solvents. The reliability, effectiveness, and robustness of the new platform is demonstrated by the remarkable agreement with experiment of the results obtained through an unsupervised approach characterized by a strongly reduced computational cost as compared to that of conventional quantum mechanics and molecular mechanics models without any accuracy reduction