Image-based malware classification: A space filling curve approach

Anti-virus (AV) software is effective at distinguishing between benign and malicious programs yet lack the ability to effectively classify malware into their respective family classes. AV vendors receive considerably large volumes of malicious programs daily and so classification is crucial to quickly identify variants of existing malware that would otherwise have to be manually examined. This paper proposes a novel method of visualizing and classifying malware using Space-Filling Curves (SFC\u27s) in order to improve the limitations of AV tools. The classification models produced were evaluated on previously unseen samples and showed promising results, with precision, recall and accuracy scores of 82%, 80% and 83% respectively. Furthermore, a comparative assessment with previous research and current AV technologies revealed that the method presented her was robust, outperforming most commercial and open-source AV scanner software programs

Vitamin C in the treatment of septic shock

Objective:To assess the efficacy of improving outcomes of septic shock treatment with the addition of Vitamin C to standard treatment compared to standard therapy alone. To assess whether or not Vitamin C has a favorable outcome in the treatment of septic shock in terms of decreasing duration of vasopressor usage, reducing duration of intensive care unit (ICU) stay, and improving mortality. Design: Systematic literature review. Methods: Searches were conducted in PubMed and Google Scholar using the terms ascorbic acid, sepsis, septic shock, and vasopressors. In PubMed the following filters were used: humans only, clinical trials, studies within the past 10 years. Studies that used Vitamin C for the treatment of septic shock and measured the duration of vasopressor usage, total duration of ICU stay, and mortality were included in the review. Results: All three studies showed a statistically significant reduction in the duration of vasopressor dependency with the addition of Vitamin C to the standard treatment of septic shock. There were conflicting results on the effects on mortality and duration of ICU stay. Conclusion: The addition of Vitamin C may decrease the duration of vasopressor usage in the treatment of septic shock. Additional higher-powered studies are needed to determine the effects of Vitamin C on mortality and duration of ICU stay

Image-based malware classification hybrid framework based on space-filling curves

There exists a never-ending “arms race” between malware analysts and adversarial malicious code developers as malevolent programs evolve and countermeasures are developed to detect and eradicate them. Malware has become more complex in its intent and capabilities over time, which has prompted the need for constant improvement in detection and defence methods. Of particular concern are the anti-analysis obfuscation techniques, such as packing and encryption, that are employed by malware developers to evade detection and thwart the analysis process. In such cases, malware is generally impervious to basic analysis methods and so analysts must use more invasive techniques to extract signatures for classification, which are inevitably not scalable due to their complexity. In this article, we present a hybrid framework for malware classification designed to overcome the challenges incurred by current approaches. The framework incorporates novel static and dynamic malware analysis methods, where static malware executables and dynamic process memory dumps are converted to images mapped through space-filling curves, from which visual features are extracted for classification. The framework is less invasive than traditional analysis methods in that there is no reverse engineering required, nor does it suffer from the obfuscation limitations of static analysis. On a dataset of 13,599 obfuscated and non-obfuscated malware samples from 23 families, the framework outperformed both static and dynamic standalone methods with precision, recall and accuracy scores of 97.6%, 97.6% and 97.6% respectively

Robustness of Image-Based Malware Classification Models Trained with Generative Adversarial Networks

As malware continues to evolve, deep learning models are increasingly used for malware detection and classification, including image based classification. However, adversarial attacks can be used to perturb images so as to evade detection by these models. This study investigates the effectiveness of training deep learning models with Generative Adversarial Network-generated data to improve their robustness against such attacks. Two image conversion methods, byte plot and space-filling curves, were used to represent the malware samples, and a ResNet-50 architecture was used to train models on the image datasets. The models were then tested against a projected gradient descent attack. It was found that without GAN generated data, the models’ prediction performance drastically decreased from 93-95% to 4.5% accuracy. However, the addition of adversarial images to the training data almost doubled the accuracy of the models. This study highlights the potential benefits of incorporating GAN-generated data in the training of deep learning models to improve their robustness against adversarial attacks

Comparing ligo merger rate observations with theory: distribution of star-forming conditions

Within the next decade, ground based gravitational wave detectors are in principle capable of determining the compact object merger rate per unit volume of the local universe to better than 20% with more than 30 detections. Though these measurements can constrain our models of stellar, binary, and cluster evolution in the nearby present-day and ancient universe, we argue that the universe is sufficiently heterogeneous (in age and metallicity distribution at least) and that merger rates predicted by these models can be sufficiently sensitive to those heterogeneities so that a fair comparison of models per unit similar star forming mass necessarily introduces at least an additional 30%--50% systematic error into any constraints on compact binary evolution models. Without adding new electromagnetic constraints on massive binary evolution or relying on more information from each merger (e.g. , binary masses and spins), as few as the {approx_equal}5 merger detections could exhaust the information available in a naive comparison to merger rate predictions. As a concrete example immediately relevant to analysis of initial and enhanced LIGO results, we use a nearby-universe catalog to demonstrate that no one tracer of stellar content can be consistently used to constrain merger rates without introducing a systematic error of order 0(30%) at 90% confidence (depending on the type of binary involved). For example, though binary black holes typically take many Gyr to merge, binary neutron stars often merge rapidly; different tracers of stellar content are required for these two types. More generally, we argue that theoretical binary evolution can depend sufficiently sensitively on star-forming conditions -- even assuming no uncertainty in binary evolution model -- that the distribution of star forming conditions must be incorporated to reduce the systematic error in merger rate predictions below roughly 40%. We emphasize that the degree of sensitivity to star-forming conditions depends on the binary evolution model and on the amount of relevant variation in star-forming conditions. For example, if after further comparison with electromagnetic and gravitational wave observations future population synthesis models suggest all BH-BH binary mergers occur promptly and therefore are associated with well-studied present-day star formation, the associated composition-related systematic uncertainty could be lower than the pessimistic value quoted above. Further, as gravitational wave detectors will make available many properties of each merger -- binary component masses, spins, and even short GRB associations and host galaxies could be available -- many detections can still be exploited to create high-precision constraints on binary compact object formation models

Gamma Ray Lines from a Universal Extra Dimension

Indirect Dark Matter searches are based on the observation of secondary particles produced by the annihilation or decay of Dark Matter. Among them, gamma-rays are perhaps the most promising messengers, as they do not suffer deflection or absorption on Galactic scales, so their observation would directly reveal the position and the energy spectrum of the emitting source. Here, we study the detailed gamma-ray energy spectrum of Kaluza--Klein Dark Matter in a theory with 5 Universal Extra Dimensions. We focus in particular on the two body annihilation of Dark Matter particles into a photon and another particle, which produces monochromatic photons, resulting in a line in the energy spectrum of gamma rays. Previous calculations in the context of the five dimensional UED model have computed the line signal from annihilations into \gamma \gamma, but we extend these results to include \gamma Z and \gamma H final states. We find that these spectral lines are subdominant compared to the predicted \gamma \gamma signal, but they would be important as follow-up signals in the event of the observation of the \gamma \gamma line, in order to distinguish the 5d UED model from other theoretical scenarios.Comment: 21 pages, 6 figure

Tropomyosin controls sarcomere-like contractions for rigidity sensing and suppressing growth on soft matrices

Cells test the rigidity of the extracellular matrix by applying forces to it through integrin adhesions. Recent measurements show that these forces are applied by local micrometre-scale contractions, but how contraction force is regulated by rigidity is unknown. Here we performed high temporal- and spatial-resolution tracking of contractile forces by plating cells on sub-micrometre elastomeric pillars. We found that actomyosin-based sarcomere-like contractile units (CUs) simultaneously moved opposing pillars in net steps of ∼2.5 nm, independent of rigidity. What correlated with rigidity was the number of steps taken to reach a force level that activated recruitment of α-actinin to the CUs. When we removed actomyosin restriction by depleting tropomyosin 2.1, we observed larger steps and higher forces that resulted in aberrant rigidity sensing and growth of non-transformed cells on soft matrices. Thus, we conclude that tropomyosin 2.1 acts as a suppressor of growth on soft matrices by supporting proper rigidity sensing

Home as a base for a Well-Lived Life: Comparing the capabilities of homeless service users in housing first and the staircase of transition in Europe

Nussbaum’s Central Capabilities refer to the elements of a well-lived life, and many adults who experience homelessness are deprived of these capabilities. The study aim was to investigate whether service users experience different homeless services as affording or constraining capabilities. We conducted semi-structured interviews with homeless service users (n = 77) in Housing First (HF) and staircase services (SS) in eight European countries. We used thematic analysis to identify three themes: autonomy and dependency, the relational impact of living arrangements, and community interaction and stigma. While SS participants were able to address their bodily integrity and health, their higherorder capabilities were constrained by their homeless situations. HF participants described home as a base from which they could enact a wide range of capabilities indicative of a well-lived life. We conclude that housing-led service models with appropriate supports are key to affording service users’ capabilities. Practical and policy implications are discussed.Orizoninfo:eu-repo/semantics/publishedVersio

TeV physics and the Planck scale

Supersymmetry is one of the best motivated possibilities for new physics at the TeV scale. However, both concrete string constructions and phenomenological considerations suggest the possibility that the physics at the TeV scale could be more complicated than the Minimal Supersymmetric Standard Model (MSSM), e.g., due to extended gauge symmetries, new vector-like supermultiplets with non-standard SU(2)xU(1) assignments, and extended Higgs sectors. We briefly comment on some of these possibilities, and discuss in more detail the class of extensions of the MSSM involving an additional standard model singlet field. The latter provides a solution to the $\mu$ problem, and allows significant modifications of the MSSM in the Higgs and neutralino sectors, with important consequences for collider physics, cold dark matter, and electroweak baryogenesis.Comment: 17 pages, 5 figures. To appear in New Journal of Physic