Intrusion detection for in-vehicle communication networks: An unsupervised kohonen SOM approach

The diffusion of embedded and portable communication devices on modern vehicles entails new security risks since in-vehicle communication protocols are still insecure and vulnerable to attacks. Increasing interest is being given to the implementation of automotive cybersecurity systems. In this work we propose an efficient and high-performing intrusion detection system based on an unsupervised Kohonen Self-Organizing Map (SOM) network, to identify attack messages sent on a Controller Area Network (CAN) bus. The SOM network found a wide range of applications in intrusion detection because of its features of high detection rate, short training time, and high versatility. We propose to extend the SOM network to intrusion detection on in-vehicle CAN buses. Many hybrid approaches were proposed to combine the SOM network with other clustering methods, such as the k-means algorithm, in order to improve the accuracy of the model. We introduced a novel distance-based procedure to integrate the SOM network with the K-means algorithm and compared it with the traditional procedure. The models were tested on a car hacking dataset concerning traffic data messages sent on a CAN bus, characterized by a large volume of traffic with a low number of features and highly imbalanced data distribution. The experimentation showed that the proposed method greatly improved detection accuracy over the traditional approach

A Kohonen SOM architecture for intrusion detection on in-vehicle communication networks

The diffusion of connected devices in modern vehicles involves a lack in security of the in-vehicle communication networks such as the controller area network (CAN) bus. The CAN bus protocol does not provide security systems to counter cyber and physical attacks. Thus, an intrusion-detection system to identify attacks and anomalies on the CAN bus is desirable. In the present work, we propose a distance-based intrusion-detection network aimed at identifying attack messages injected on a CAN bus using a Kohonen self-organizing map (SOM) network. It is a power classifier that can be trained both as supervised and unsupervised learning. SOM found broad application in security issues, but was never performed on in-vehicle communication networks. We performed two approaches, first using a supervised X-Y fused Kohonen network (XYF) and then combining the XYF network with a K-means clustering algorithm (XYF-K) in order to improve the efficiency of the network. The models were tested on an open source dataset concerning data messages sent on a CAN bus 2.0B and containing large traffic volume with a low number of features and more than 2000 different attack types, sent totally at random. Despite the complex structure of the CAN bus dataset, the proposed architectures showed a high performance in the accuracy of the detection of attack messages

Improving plastic management by means of people awareness

In past decades the usage of plastic has seen a tremendous increment. This raise is mainly caused by industrial development and by the spread of this material in every aspect of people life, from food package to aerospace application. For sure plastic has a key role in society and it is not possible to erase, nevertheless its overuse has a serious impact on the environment as well know. In particular, just a few percentage of the total amount of plastic is recycled, the rest has to be landfilled or burnt causing serious pollution side effect. This poor circularity in plastic value chain is mainly caused by difficulties in sorting processes and expensiveness of recycling. By the way a great part of plastic applications could be avoided without implying a reduction in life quality for the people. In addition, a better education in plastic objects shopping and plastic waste management could decrease the difficulties in sorting and recycling. One of the crucial reason why these applications and incorrect behaviour are still present is that the information on alternatives are not present or very hard to be found. In the present paper a novel platform to enhance a more plastic-free life is presented. First a detailed description of the problem is stated, then the process to achieve the proposed solution is described. Finally the platform prototype is analysed in details among its functionalities

Towards a reduction of greenhouse gas emission from wastewater treatment plants: a new plant wide experimental and modelling approach

The increasing interest in greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) has led to the development of new tools for their design and management. Studies about gas emissions show that the sewer collection and the wastewater treatment plant are anthropogenic GHG potential sources, so they contribute to the climate change and air pollution. A wastewater treatment plant receives wastewater from sewers and, while produces treated water for discharge into surface water, emits the three major greenhouse gases, CO2, CH4, and N2O, during the treatment processes, and additional amounts of CO2 and CH4 from the energy demands (Bani Shahabadi et al., 2009). Indeed, energy consumption can be considered as an indirect source of GHGs. Greenhouse-gas emissions are generated by water-line and sludge- line processes and by the on-site combustion of biogas and fossil fuels for energy generation. GHGs may also be produced during sludge disposal or reuse (transportation and degradation of remaining biosolids off-site), off-site energy production and off-site chemicals production. In recent years, increasing attention is given to the assessment of N2O emissions from WWTPs. N2O is a powerful greenhouse gas that is almost 300 times stronger than CO2. Nevertheless, the source and magnitude of N2O are relatively unknown and the knowledge is still incomplete. This paper presents the first results of an ongoing research project aiming at setting-up an innovative mathematical model platform (Decision Support System—DSS) for the design and management of WWTPs. The project is constituted by four research units (UOs) and its final goal is to minimize, by means of this platform, the environmental impact of WWTPs through their optimization in terms of energy consumptions and pollutants, sludge and GHG emissions

Advances in Azorella glabra Wedd. Extract research: In vitro antioxidant activity, antiproliferative effects on acute myeloid leukemia cells and bioactive compound characterization

Azorella glabra Wedd. (AG) is traditionally used to treat gonorrhea or kidney's problems. The antioxidant, antidiabetic, anticholinesterase and in vitro antitumor activities of AG extracts were recently reported. The aim of this work was to investigate anti-leukemic properties of AG chloroform fraction (AG CHCl3) and of its ten sub-fractions (I-X) and to identify their possible bioactive compounds. We determined their in vitro antioxidant activity using 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), nitric oxide (NO) and superoxide anion (SO) assays, and their phytochemical profile by spectrophotometric and LC-MS/MS techniques. I-X action on two acute myeloid leukemia (AML) cell lines viability, apoptosis and cell cycle were evaluated by MTS, western blotting and cytofluorimetric assays. Different polyphenol, flavonoid and terpenoid amount, and antioxidant activity were found among all samples. Most of I-X induced a dose/time dependent reduction of cell viability higher than parent extract. IV and VI sub-fractions showed highest cytotoxic activity and, of note, a negligible reduction of healthy cell viability. They activated intrinsic apoptotic pathway, induced a G0/G1 block in leukemic cells and, interestingly, led to apoptosis in patient AML cells. These activities could be due to mulinic acid or azorellane terpenoids and their derivatives, tentatively identified in both IV and VI. In conclusion, our data suggest AG plant as a source of potential anti-AML agents

Future in the past: Azorella glabra wedd. as a source of new natural compounds with antiproliferative and cytotoxic activity on multiple myeloma cells

Multiple myeloma (MM) is the second most common hematologic malignancy and, although the development of novel agents has improved survival of patients, to date, it remains incurable. Thus, newer and more effective therapeutic strategies against this malignancy are necessary. Plant extracts play an important role in anti-tumor drug discovery. For this reason, in the investigation of novel natural anti-MM agents, we evaluated the phytochemical profiles, in vitro antioxidant activity, and effects on MM cells of Azorella glabra (AG) Wedd. Total polyphenols (TPC), flavonoids (TFC), and terpenoids (TTeC) contents were different among samples and the richest fractions in polyphenols demonstrated a higher antioxidant activity in in vitro assays. Some fractions showed a dose and time dependent anti-proliferative activity on MM cells. The chloroform fraction (CHCl 3 ) showed major effects in terms of reduction of cell viability, induction of apoptosis, and cell cycle arrest on MM cells. The apoptosis induction was also confirmed by the activation of caspase-3. Importantly, the CHCl 3 fraction exhibited a negligible effect on the viability of healthy cells. These results encourage further investigations on AG extracts to identify specific bioactive compounds and to define their potential applications in MM

DNA methylation dynamic of bone marrow hematopoietic stem cells after allogeneic transplantation

Background: Allogeneic hematopoietic stem cell transplantation (AHSCT) is a curative therapeutic approach for different hematological malignancies (HMs), and epigenetic modifications, including DNA methylation, play a role in the reconstitution of the hematopoietic system after AHSCT. This study aimed to explore global DNA methylation dynamic of bone marrow (BM) hematopoietic stem and progenitor cells (HSPCs) from donors and their respective recipients affected by acute myeloid leukemia (AML), acute lymphoid leukemia (ALL) and Hodgkin lymphoma (HL) during the first year after transplant. Methods: We measured DNA methylation profile by Illumina HumanMethylationEPIC in BM HSPC of 10 donors (t0) and their matched recipients at different time points after AHSCT, at day + 30 (t1), + 60 (t2), + 120 (t3), + 180 (t4), and + 365 (t5). Differential methylation analysis was performed by using R software and CRAN/Bioconductor packages. Gene set enrichment analysis was carried out on promoter area of significantly differentially methylated genes by clusterProfiler package and the mSigDB genes sets. Results: Results show significant differences in the global methylation profile between HL and acute leukemias, and between patients with mixed and complete chimerism, with a strong methylation change, with prevailing hypermethylation, occurring 30 days after AHSCT. Functional analysis of promoter methylation changes identified genes involved in hematopoietic cell activation, differentiation, shaping, and movement. This could be a consequence of donor cell “adaptation” in recipient BM niche. Interestingly, this epigenetic remodeling was reversible, since methylation returns similar to that of donor HSPCs after 1 year. Only for a pool of genes, mainly involved in dynamic shaping and trafficking, the DNA methylation changes acquired after 30 days were maintained for up to 1 year post-transplant. Finally, preliminary data suggest that the methylation profile could be used as predictor of relapse in ALL. Conclusions: Overall, these data provide insights into the DNA methylation changes of HSPCs after transplantation and a new framework to investigate epigenetics of AHSCT and its outcomes

Two-bands superconductivity with intra- and interband pairing for synthetic superlattices

We consider a model for superconductivity in a two-band superconductor, having an anisotropic electronic structure made of two partially overlapping bands with a first hole-like and a second electron-like fermi surface. In this pairing scenario, driven by the interplay between interband $V_{i,j}$ and intraband $V_{i,i}$ pairing terms, we have solved the two gap equations at the critical temperature $T = T_c$ and calculate $T_c$ and the chemical potential $\mu$ as a function of the number of carriers $n$ for various values of pairing interactions, $V_{1,1}$, $V_{2,2}$, and $V_{1,2}$. The results show the complexity of the physics of condensates with multiple order parameters with the chemical potential near band edges.Comment: 6 pages, 2 figure

Prevalence of hypertrophic cardiomyopathy (HCM) in feline population examined by the osservatorio italiano HCM felina

Hypertrophic cardiomyopathy (HCM) is the most common feline inherited cardiac disease and it is a major cause of morbidity and mortality. The Osservatorio Italiano HCM Felina was formed in 2008 by a network of clinicians, geneticists and breedings to monitor and study HCM in Italian cats. Since April 2008, 1308 adult cats, belonging to various breeds, including Maine Coon, Siberian, Norwegian Forest Cat, Ragdoll, Sphynx, British SH, Birmans and others have been prospectively enrolled. Recheck evaluations were performed in 287 cats. Each cat underwent a clinical examination, echocardiography, and blood collection for genetic testing (when appropriate) and storage in the Italian Feline Biobank. The disease status was defined by echocardiography according to established guidelines (left ventricular diastolic wall thickness<5.5mm = HCM negative, =5.5 but < 6mm = HCM equivocal, = 6mm = HCM positive). The prevalence of HCM in the population was 6% (74 cats); equivocal diagnoses were conferred on 4% (57 cats). These prevalences did not differ between breeds. The prevalence of HCM in the Italian feline population was lower compared to those reported by other investigators. Evaluation of data from the entire population demonstrated that left ventricular end-diastolic wall thickness and aortic diameter showed a weak positive correlation with body weight (p< 0.0001, r2<0.12 for all variables), suggesting that weight-dependent limits on wall thickness should be considered in cats as is currently practiced in dogs. The lower prevalence of HCM in Italian cat breeds compared with those examined elsewhere might be explained by different criteria for determining presence or absence of disease, differences in ages at which the subject were examined, or a selection bias by breeders in presenting cats they consider \u201cnormal\u201d