Malware Detection using Machine Learning and Deep Learning

Research shows that over the last decade, malware has been growing exponentially, causing substantial financial losses to various organizations. Different anti-malware companies have been proposing solutions to defend attacks from these malware. The velocity, volume, and the complexity of malware are posing new challenges to the anti-malware community. Current state-of-the-art research shows that recently, researchers and anti-virus organizations started applying machine learning and deep learning methods for malware analysis and detection. We have used opcode frequency as a feature vector and applied unsupervised learning in addition to supervised learning for malware classification. The focus of this tutorial is to present our work on detecting malware with 1) various machine learning algorithms and 2) deep learning models. Our results show that the Random Forest outperforms Deep Neural Network with opcode frequency as a feature. Also in feature reduction, Deep Auto-Encoders are overkill for the dataset, and elementary function like Variance Threshold perform better than others. In addition to the proposed methodologies, we will also discuss the additional issues and the unique challenges in the domain, open research problems, limitations, and future directions.Comment: 11 Pages and 3 Figure

An alternate proton acceptor for excited-state proton transfer in green fluorescent protein: Rewiring GFP

The neutral form of the chromophore in wild-type green fluorescent protein (wtGFP) undergoes excited-state proton transfer (ESPT) upon excitation, resulting in characteristic green (508 nm) fluorescence. This ESPT reaction involves a proton relay from the phenol hydroxyl of the chromophore to the ionized side chain of E222, and results in formation of the anionic chromophore in a protein environment optimized for the neutral species (the I* state). Reorientation or replacement of E222, as occurs in the S65T and E222Q GFP mutants, disables the ESPT reaction and results in loss of green emission following excitation of the neutral chromophore. Previously, it has been shown that the introduction of a second mutation (H148D) into S65T GFP allows the recovery of green emission, implying that ESPT is again possible. A similar recovery of green fluorescence is also observed for the E222Q/H148D mutant, suggesting that D148 is the proton acceptor for the ESPT reaction in both double mutants. The mechanism of fluorescence emission following excitation of the neutral chromophore in S65T/H148D and E222Q/H148D has been explored through the use of steady state and ultrafast time-resolved fluorescence and vibrational spectroscopy. The data are contrasted with those of the single mutant S65T GFP. Time-resolved fluorescence studies indicate very rapid (<1 ps) formation of I* in the double mutants, followed by vibrational cooling on the picosecond time scale. The time-resolved IR difference spectra are markedly different to those of wtGFP or its anionic mutants. In particular, no spectral signatures are apparent in the picosecond IR difference spectra that would correspond to alteration in the ionization state of D148, leading to the proposal that a low-barrier hydrogen bond (LBHB) is present between the phenol hydroxyl of the chromophore and the side chain of D148, with different potential energy surfaces for the ground and excited states. This model is consistent with recent high-resolution structural data in which the distance between the donor and acceptor oxygen atoms is =2.4 Å. Importantly, these studies indicate that the hydrogen-bond network in wtGFP can be replaced by a single residue, an observation which, when fully explored, will add to our understanding of the various requirements for proton-transfer reactions within proteins

Successful examples of the application of novel iterative trainable algorithms to guide rational mutation strategies for enzyme engineering: From prediction to lab testing to algorithm retraining

Both natural mutations occurring in a homologous enzyme family and mutations engineered in a given protein can have a tremendous impact in the activity and binding behavior of the enzyme towards substrates or other molecules. Binding and catalytic properties can be modified by rationally mutating selected amino acids in a protein. For instance, new specificity properties can be engineered into existing enzymes, which can be applied to the rational design of mutations to alter its catalysis. Although this approach has been largely used, the modifications introduced in the target protein have not been exempt of deleterious effects on protein function, binding or physicochemical properties. Much finer tuned modifications should be designed in order to alter the desired catalytic or binding properties of a protein and simultaneously not affecting other protein properties or functions. These engineered mutations usually require a thorough knowledge of the relevant structure-function relationships in the protein molecule. If no precise structure-function information is available for a protein, the amount of possible amino acid mutations to be tested precludes a direct search. Furthermore, in many cases a directed evolution strategy cannot be successfully used to achieve the desired results due to the unavailability of suitable screening tests. In the last years, we have developed new and powerful in silico methodologies to automatically propose, test and redesign mutagenesis strategies for a target protein, based only on evolutionarily conserved physicochemical properties of amino acids in a protein family where the target protein belongs, and on structural properties, including calculation of vibrational entropies, if available, with no need of explicit structure-function relationships. This methodology identifies amino acid positions that are putatively responsible for function, specificity, stability or binding interactions in a family of proteins and calculates amino acid propensity and distributions at each position. Not only conserved amino acid positions in a protein family can be labelled as functionally relevant, but also non-conserved amino acid positions can be identified to have a meaningful functional effect, and even amino acid substitutions that are unobserved in nature. These results can be used to predict if a given mutation can have a functional implication and which mutation is most likely to be functionally silent for a protein. Through several rounds of mutation suggestions, laboratory testing of the mutants and feedback of results to retrain the algorithms, our methodology can be used to rapidly and automatically discard any irrelevant mutation and guide the research focus toward functionally significant mutations. In this work, we will show how we have successfully used our publicly available methods to guide mutant design in enzyme engineering applied to xylanases (producing an improved octuple mutant in a single mutagenesis round), proteases, glucanases, ubiquitin ligases and other enzymes, to alter protein function, stability or thermodynamic properties independently of their catalytic properties in vitro and in vivo. We will also show how the predictions of these methods have been employed to shift chromatographic elution profiles of xylanases and ferritin nanocages for better purification without affecting their activity and to obtain ferritin variants with better properties to be used in nanotechnological applications, including modifications to the external and internal surface of the protein to change its interaction properties, improve its recombinant production, alter the characteristics of nanoparticles within or change its organic molecule carrier capacity. Finally, we will show how a similar approach has been integrated in an artificial intelligence classification scheme to identify somatic mutations in the human VHL gene that are related to renal clear-cell cancer and to predict the clinical outcome and prognosis of pVHL mutation and malfunction in humans, based on specific disruption of interactions with VHL binding partners. Clearly, our techniques show promising performance as a valuable and powerful bioinformatics tool to aid in the computer-aided design of engineered enzyme variants and in the understanding of function-structure, binding and affinity relationships in enzymes and other proteins

Performance comparision of secure and insecure VoIP environments

This paper deals with techniques of measuring and assessment of the voice transmitted in IP networks in secure and insecure environment using different virtual testbeds and a real implementation based on OpenSer. They realised their real platform, in order to understand how the voice services in IP network are affected by using the secure IP environment. The real performance test was implemented between VSB-Technical University in Ostrava and University degli studi of Milan

“I Do Not Like Being Me”: the Impact of Self-hate on Increased Risky Sexual Behavior in Sexual Minority People

Background: Increased risky sexual behaviors (RSB) in sexual minority people relative to heterosexual individuals are well documented. However, the role of trans-diagnostic factors that are not sexual orientation-specific, such as self-criticism, in predicting RSB was understudied. The present study aimed to test participants’ gender and sexual orientation as moderators between self-criticism and RSB. Methods: Data were collected during 2019. The total sample included 986 sexual minority people (Nwomen = 51%) and 853 heterosexual people (Nwomen = 46%), ranging from 18 to 35&nbsp;years of age. Self-criticism dimensions (self-hate, self-inadequacy, self-reassurance), types of positive affect (relaxed, safe/content, and activated affect), and RSB were assessed. Bivariate, multivariate analyses, and moderated regression analyses were conducted. Results: Sexual minority participants showed higher levels of RSB, self-hate, and self-inadequacy than heterosexual people. Only in sexual minority men, RSB correlated positively with self-hate and negatively with safe/content positive affect. Moderated regressions showed that only for sexual minority participants, higher RSB were predicted by higher levels of self-hate. At the same time, this association was not significant for heterosexual people controlling the effects of age, presence of a stable relationship, other self-criticism dimensions, and activation safe/content affect scale. The two-way interaction between sexual orientation and gender was significant, showing that regardless of self-hate, the strength of the association between sexual orientation and RSB is stronger for sexual minority men than sexual minority women and heterosexual participants. Conclusions: Findings highlight the distinctive role of self-hate in the occurrence of RSB in sexual minority people and support the usefulness of developing a compassion-focused intervention to target self-hate in sexual minority people

Impact of security on speech quality

This paper deals with impact of secured environment on speech quality of IP telephony. There are presented the results of the analyzing of voice over secure communication links based on TLS. The using of secure network environments can affect a speech quality. There is the performance comparision of cipher alghorithms and description how the used security mechanisms influence the final R- factor. The presented results are based on numerous of experiments which have been performed in real IP networ

Centrifuge modelling of the seismic performance of soft buried barriers

The paper presents the results of an experimental work carried out in a geotechnical centrifuge at the Schofield Centre of Cambridge University. Two reduced scale models of soft barriers in a sand layer underwent a series of ground shaking. In the first model a thin horizontal layer made of latex balloons filled with a cross-linked gel was created at about mid-height of the sand layer. In the second, the same balloons were deployed to form a V-shaped barrier aimed at isolating a relatively shallow volume of sand. The aim of the study was to get experimental evidence of the capability of such soft barriers to isolate a volume of soil thus reducing amplification of ground motion during severe seismic events. The experimental results were compared with FE numerical analyses of the same models, carried out also in free field to have a benchmark condition. By validating the FE modelling via the comparison with the experimental results, a robust model has been built, aimed at being used for carrying out a wider parametric numerical testing. The experimental results confirm the effectiveness of such soft barriers to reduce amplification in the isolated volumes during seismic events.The research activity was carried out at the University of Napoli Federico II as part of the national research project PON_03 METRICS. The financial support of the consortium Stress s.c.a r.l. is kindly acknowledged.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s10518-016-9912-

Bilateral Chilblain-like Lesions of the Toes Characterized by Microvascular Remodeling in Adolescents During the COVID-19 Pandemic.

Importance: Chilblain-like lesions have been one of the most frequently described cutaneous manifestations during the COVID-19 pandemic. Their etiopathogenesis, including the role of SARS-CoV-2, remains elusive. Objective: To examine the association of chilblain-like lesions with SARS-CoV-2 infection. Design, setting, and participants: This prospective case series enrolled 17 adolescents who presented with chilblain-like lesions from April 1 to June 30, 2020, at a tertiary referral academic hospital in Italy. Main outcomes and measures: Macroscopic (clinical and dermoscopic) and microscopic (histopathologic) analysis contributed to a thorough understanding of the lesions. Nasopharyngeal swab, serologic testing, and in situ hybridization of the skin biopsy specimens were performed to test for SARS-CoV-2 infection. Laboratory tests explored signs of systemic inflammation or thrombophilia. Structural changes in peripheral microcirculation were investigated by capillaroscopy. Results: Of the 17 adolescents (9 [52.9%] male; median [interquartile range] age, 13.2 [12.5-14.3] years) enrolled during the first wave of the COVID-19 pandemic, 16 (94.1%) had bilaterally localized distal erythematous or cyanotic lesions. A triad of red dots (16 [100%]), white rosettes (11 [68.8%]), and white streaks (10 [62.5%]) characterized the dermoscopic picture. Histologic analysis revealed a remodeling of the dermal blood vessels with a lobular arrangement, wall thickening, and a mild perivascular lymphocytic infiltrate. SARS-CoV-2 infection was excluded by molecular and serologic testing. In situ hybridization did not highlight the viral genome in the lesions. Conclusions and relevance: This study delineated the clinical, histologic, and laboratory features of chilblain-like lesions that emerged during the COVID-19 pandemic, and its findings do not support their association with SARS-CoV-2 infection. The lesions occurred in otherwise healthy adolescents, had a long but benign course to self-resolution, and were characterized by a microvascular remodeling with perivascular lymphocytic infiltrate but no other signs of vasculitis. These results suggest that chilblain-like lesions do not imply a concomitant SARS-CoV-2 infection. Ongoing studies will help clarify the etiopathogenic mechanisms

The Neonatal and Paediatric Pharmacokinetics of Antimicrobials study (NAPPA): investigating amoxicillin, benzylpenicillin, flucloxacillin and piperacillin pharmacokinetics from birth to adolescence

Background: Pharmacokinetic (PK) data underlying paediatric penicillin dosing remain limited, especially in critical care.// Objectives: The primary objective of the Neonatal and Paediatric Pharmacokinetics of Antimicrobials study (NAPPA) was to characterize PK profiles of commonly used penicillins using data obtained during routine care, to further understanding of PK variability and inform future evidence-based dosing.// Methods: NAPPA was a multicentre study of amoxicillin, co-amoxiclav, benzylpenicillin, flucloxacillin and piperacillin/tazobactam. Patients were recruited with informed consent. Antibiotic dosing followed standard of care. PK samples were obtained opportunistically or at optimal times, frozen and analysed using UPLC with tandem MS. Pharmacometric analysis was undertaken using NONMEM software (v7.3). Model-based simulations (n = 10 000) tested PTA with British National Formulary for Children (BNFC) and WHO dosing. The study had ethical approval.// Results: For the combined IV PK model, 963 PK samples from 370 participants were analysed simultaneously incorporating amoxicillin, benzylpenicillin, flucloxacillin and piperacillin data. BNFC high-dose regimen simulations gave these PTA results (median fT>MIC at breakpoints of specified pathogens): amoxicillin 100% (Streptococcus pneumoniae); benzylpenicillin 100% (Group B Streptococcus); flucloxacillin 48% (MSSA); and piperacillin 100% (Pseudomonas aeruginosa). Oral population PK models for flucloxacillin and amoxicillin enabled estimation of first-order absorption rate constants (1.16 h−1 and 1.3 h−1) and bioavailability terms (62.7% and 58.7%, respectively).// Conclusions: NAPPA represents, to our knowledge, the largest prospective combined paediatric penicillin PK study undertaken to date, and the first paediatric flucloxacillin oral PK model. The PTA results provide evidence supportive of BNFC high-dose IV regimens for amoxicillin, benzylpenicillin and piperacillin