A spatio-temporal entropy-based approach for the analysis of cyber attacks (demo paper)

Computer networks are ubiquitous systems growing exponentially with a predicted 50 billion devices connected by 2050. This dramatically increases the potential attack surface of Internet networks. A key issue in cyber defense is to detect, categorize and identify these attacks, the way they are propagated and their potential impacts on the systems affected. The research presented in this paper models cyber attacks at large by considering the Internet as a complex system in which attacks are propagated over a network. We model an attack as a path from a source to a target, and where each attack is categorized according to its intention. We setup an experimental testbed with the concept of honeypot that evaluates the spatiotemporal distribution of these Internet attacks. The preliminary results show a series of patterns in space and time that illustrate the potential of the approach, and how cyber attacks can be categorized according to the concept and measure of entropy

Scaling laws for random walks in long-range correlated disordered media

We study the scaling laws of diffusion in two-dimensional media with long-range correlated disorder through exact enumeration of random walks. The disordered medium is modelled by percolation clusters with correlations decaying with the distance as a power law, $r^{-a}$, generated with the improved Fourier filtering method. To characterize this type of disorder, we determine the percolation threshold $p_{\text c}$ by investigating cluster-wrapping probabilities. At $p_{\text c}$, we estimate the (sub-diffusive) walk dimension $d_{\text w}$ for different correlation exponents $a$. Above $p_{\text c}$, our results suggest a normal random walk behavior for weak correlations, whereas anomalous diffusion cannot be ruled out in the strongly correlated case, i.e., for small $a$.Comment: 11 pages, 6 figure

Honeypots and honeynets: issues of privacy

Honeypots and honeynets are popular tools in the area of network security and network forensics. The deployment and usage of these tools are influenced by a number of technical and legal issues, which need to be carefully considered. In this paper, we outline the privacy issues of honeypots and honeynets with respect to their technical aspects. The paper discusses the legal framework of privacy and legal grounds to data processing. We also discuss the IP address, because by EU law, it is considered personal data. The analysis of legal issues is based on EU law and is supported by discussions on privacy and related issues

The challenges of containing SARS-CoV-2 via test-trace-and-isolate

Without a cure, vaccine, or proven long-term immunity against SARS-CoV-2, test-trace-and-isolate (TTI) strategies present a promising tool to contain the viral spread. For any TTI strategy, however, a major challenge arises from pre- and asymptomatic transmission as well as TTI-avoiders, which contribute to hidden, unnoticed infection chains. In our semi-analytical model, we identified two distinct tipping points between controlled and uncontrolled spreading: one, at which the behavior-driven reproduction number of the hidden infections becomes too large to be compensated by the available TTI capabilities, and one at which the number of new infections starts to exceed the tracing capacity, causing a self-accelerating spread. We investigated how these tipping points depend on realistic limitations like limited cooperativity, missing contacts, and imperfect isolation, finding that TTI is likely not sufficient to contain the natural spread of SARS-CoV-2. Therefore, complementary measures like reduced physical contacts and improved hygiene probably remain necessary

Transition from regular to complex behaviour in a discrete deterministic asymmetric neural network model

We study the long time behaviour of the transient before the collapse on the periodic attractors of a discrete deterministic asymmetric neural networks model. The system has a finite number of possible states so it is not possible to use the term chaos in the usual sense of sensitive dependence on the initial condition. Nevertheless, at varying the asymmetry parameter, $k$, one observes a transition from ordered motion (i.e. short transients and short periods on the attractors) to a ``complex'' temporal behaviour. This transition takes place for the same value $k_{\rm c}$ at which one has a change for the mean transient length from a power law in the size of the system ($N$) to an exponential law in $N$. The ``complex'' behaviour during the transient shows strong analogies with the chaotic behaviour: decay of temporal correlations, positive Shannon entropy, non-constant Renyi entropies of different orders. Moreover the transition is very similar to that one for the intermittent transition in chaotic systems: scaling law for the Shannon entropy and strong fluctuations of the ``effective Shannon entropy'' along the transient, for $k > k_{\rm c}$.Comment: 18 pages + 6 figures, TeX dialect: Plain TeX + IOP macros (included

Editorial: Paz, la tarea es fortalecer la participación social y popular

Asistimos a un momento histórico en Colombia, se marca posiblemente, el cierre de una cruenta confrontación armada de más de 50 años, entre las Farc-Ep y el gobierno Colombiano, este solo hecho ya de por sí, es bien importante, pero no suficiente

Refined NMR solution structures of proteins using homo-and heteronuclear couplings, relaxation time measurements and relaxation matrix analysis

Abstract In order to compare high resolution crystal structures of proteins with the corresponding solution structures a detailed analysis of NMR parameters obtained for various proteins was carried out. As many NOE values as possible were transformed into distances using a relaxation matrix analysis. In addition homo-and heteronuclear 3J couplings from I3C and I5N enriched protein species were determined. From these couplings the dihedral angles $, and x1 were evaluated. It was possible to interpret the various 3J values in terms of either distinct dihedral angles or with a certain variance of angles or with an equilibrium of different rotameric states. The refined solution structures were obtained using the distance constraints together with the dihedral angle constraints in a distance geometry algorithm (DIANA program package). The resulting DG structure was the starting conformation of a subsequent molecular dynamics simulation. From a determination of relaxation times TI, T, and NOE build-up rates of "N and I3C nuclei order parameters were obtained to describe the dynamic behaviour of protein molecular parts. Refined solution structures were obtained for ribonuclease TI, a flavodoxin from D.vulgaris, fatty acid binding protein from bovine heart and for a heat shock transcription factor from tomato. In most cases the high resolution crystal structures differ only slightly from the refined solution structures

Relaxation, closing probabilities and transition from oscillatory to chaotic attractors in asymmetric neural networks

Attractors in asymmetric neural networks with deterministic parallel dynamics were shown to present a "chaotic" regime at symmetry eta < 0.5, where the average length of the cycles increases exponentially with system size, and an oscillatory regime at high symmetry, where the typical length of the cycles is 2. We show, both with analytic arguments and numerically, that there is a sharp transition, at a critical symmetry \e_c=0.33, between a phase where the typical cycles have length 2 and basins of attraction of vanishing weight and a phase where the typical cycles are exponentially long with system size, and the weights of their attraction basins are distributed as in a Random Map with reversal symmetry. The time-scale after which cycles are reached grows exponentially with system size $N$, and the exponent vanishes in the symmetric limit, where $T\propto N^{2/3}$. The transition can be related to the dynamics of the infinite system (where cycles are never reached), using the closing probabilities as a tool. We also study the relaxation of the function $E(t)=-1/N\sum_i |h_i(t)|$, where $h_i$ is the local field experienced by the neuron $i$. In the symmetric system, it plays the role of a Ljapunov function which drives the system towards its minima through steepest descent. This interpretation survives, even if only on the average, also for small asymmetry. This acts like an effective temperature: the larger is the asymmetry, the faster is the relaxation of $E$, and the higher is the asymptotic value reached. $E$ reachs very deep minima in the fixed points of the dynamics, which are reached with vanishing probability, and attains a larger value on the typical attractors, which are cycles of length 2.Comment: 24 pages, 9 figures, accepted on Journal of Physics A: Math. Ge

Identification of Genetic and Epigenetic Variations in a Rat Model for Neurodevelopmental Disorders

A combination of genetic variations, epimutations and environmental factors may be involved in the etiology of complex neurodevelopmental disorders like schizophrenia. To study such disorders, we use apomorphine-unsusceptible (APO-UNSUS) Wistar rats and their phenotypic counterpart apomorphine-susceptible (APO-SUS) rats that display a complex phenotype remarkably similar to that of schizophrenic patients. As the molecular basis of the APO-SUS/UNSUS rat model, we recently identified a genomic rearrangement of the Aph-1b gene. Here, we discovered between the two rat lines differences other than the Aph-1b gene defect, including a remarkable cluster of genetic variations, two variants corresponding to topoisomerase II-based recombination hot spots and an epigenetic (DNA methylation) difference in cerebellum and (hypo)thalamic but not hippocampal genomic DNA. Furthermore, genetic variations were found to correlate with the degree of apomorphine susceptibility in unselected Wistar rats. Together, the results show that a number of genetic and epigenetic differences exist between the APO-SUS and -UNSUS rat genomes, raising the possibility that in addition to the Aph-1b gene defect the newly identified variations may also contribute to the complex APO-SUS phenotype

Topoisomerase IIβ Activates a Subset of Neuronal Genes that Are Repressed in AT-Rich Genomic Environment

DNA topoisomerase II (topo II) catalyzes a strand passage reaction in that one duplex is passed through a transient brake or gate in another. Completion of late stages of neuronal development depends on the presence of active β isoform (topo IIβ). The enzyme appears to aid the transcriptional induction of a limited number of genes essential for neuronal maturation. However, this selectivity and underlying molecular mechanism remains unknown. Here we show a strong correlation between the genomic location of topo IIβ action sites and the genes it regulates. These genes, termed group A1, are functionally biased towards membrane proteins with ion channel, transporter, or receptor activities. Significant proportions of them encode long transcripts and are juxtaposed to a long AT-rich intergenic region (termed LAIR). We mapped genomic sites directly targeted by topo IIβ using a functional immunoprecipitation strategy. These sites can be classified into two distinct classes with discrete local GC contents. One of the classes, termed c2, appears to involve a strand passage event between distant segments of genomic DNA. The c2 sites are concentrated both in A1 gene boundaries and the adjacent LAIR, suggesting a direct link between the action sites and the transcriptional activation. A higher-order chromatin structure associated with AT richness and gene poorness is likely to serve as a silencer of gene expression, which is abrogated by topo IIβ releasing nearby genes from repression. Positioning of these genes and their control machinery may have developed recently in vertebrate evolution to support higher functions of central nervous system