Abstract-Cloud services are prominent within the private, public and commercial domains. Many of these services are expected to be always on and have a critical nature; therefore, security and resilience are increasingly important aspects. In order to remain resilient, a cloud needs to possess the ability to react not only to known threats, but also to new challenges that target cloud infrastructures. In this paper we introduce and discuss an online cloud anomaly detection approach, comprising dedicated detection components of our cloud resilience architecture. More specifically, we exhibit the applicability of novelty detection under the one-class support Vector Machine (SVM) formulation at the hypervisor level, through the utilisation of features gathered at the system and network levels of a cloud node. We demonstrate that our scheme can reach a high detection accuracy of over 90% whilst detecting various types of malware and DoS attacks. Furthermore, we evaluate the merits of considering not only system-level data, but also network-level data depending on the attack type. Finally, the paper shows that our approach to detection using dedicated monitoring components per VM is particularly applicable to cloud scenarios and leads to a flexible detection system capable of detecting new malware strains with no prior knowledge of their functionality or their underlying instructions.Index Terms-Security, resilience, invasive software, multi-agent systems, network-level security and protection.

Compounds targeting the sigma 2 receptor, which we recently cloned and showed to be identical with transmembrane protein 97 (σ2R/TMEM97), are broadly applicable therapeutic agents currently in clinical trials for imaging in breast cancer and for treatment of Alzheimer’s disease and schizophrenia. These promising applications coupled with our previous observation that the σ2R/TMEM97 modulator SAS-0132 has neuroprotective attributes and improves cognition in wild-type mice suggests that modulating σ2R/TMEM97 may also have therapeutic benefits in other neurodegenerative conditions such as traumatic brain injury (TBI). Herein, we report that DKR-1677, a novel derivative of SAS-0132 with increased affinity and selectivity for σ2R/Tmem97 (Ki = 5.1 nM), is neuroprotective after blast-induced and controlled cortical impact (CCI) TBI in mice. Specifically, we discovered that treatment with DKR-1677 decreases axonal degeneration after blast-induced TBI and enhances survival of cortical neurons and oligodendrocytes after CCI injury. Furthermore, treatment with DKR-1677 preserves cognition in the Morris water maze after blast TBI. Our results support an increasingly broad role for σ2R/Tmem97 modulation in neuroprotection and suggest a new approach for treating patients suffering from TBI.

Abstract-Virtualized cloud environments have emerged as a necessity within modern unified ICT infrastructures and have established themselves as a reliable backbone for numerous alwayson services. 'Live' intra-cloud virtual-machine (VM) migration is a widely used technique for efficient resource management employed within modern cloud infrastructures. Despite the benefits of such functionality, there are still several security issues which have not yet been thoroughly assessed and quantified. We investigate the impact of live virtual-machine migration on stateof-the-art anomaly detection (AD) techniques (namely PCA and K-means), by evaluating live migration under various attack types and intensities. We find that the performance for both detectors degrades as shown by their Receiver Operating Characteristics (ROC) curves when intra-cloud live migration is initiated while VMs are under a netscan (NS) or a denial-of-service (DoS) attack.

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Epigenetic marks such as DNA methylation and histone modification can vary among plant accessions creating epi-alleles with different levels of expression competence. Mutations in epigenetic pathway functions are powerful tools to induce epigenetic variation. As an alternative approach, we investigated the potential of over-expressing an epigenetic function, using DNA METHYLTRANSFERASE1 (MET1) for proof-of-concept. In Arabidopsis thaliana, MET1 controls maintenance of cytosine methylation at symmetrical CG positions. At some loci, which contain dense DNA methylation in CG- and non-CG context, loss of MET1 causes joint loss of all cytosines methylation marks. We find that over-expression of both catalytically active and inactive versions of MET1 stochastically generates new epi-alleles at loci encoding transposable elements, non-coding RNAs and proteins, which results for most loci in an increase in expression. Individual transformants share some common phenotypes and genes with altered gene expression. Altered expression states can be transmitted to the next generation, which does not require the continuous presence of the MET1 transgene. Long-term stability and epigenetic features differ for individual loci. Our data show that over-expression of MET1, and potentially of other genes encoding epigenetic factors, offers an alternative strategy to identify epigenetic target genes and to create novel epi-alleles.

In plants, demethylation of 5-methylcytosine (5 mC) residues is controlled by DNA glycosylases, while in mammals it requires oxidation of 5 mC by TET proteins, a group of Fe(II)/2-oxoglutaratedependent dioxygenases. We analysed the effects of expressing the C-terminal catalytic domain of the human TET3 gene (TET3c) in Arabidopsis thaliana, using an rDNA region as a methylation reporter. In TET3c transformants, epialleles with hypomethylation or hypermethylation patterns can be induced, which is each stably retained in progeny lines even after removal of the TET3c transgene. In TET3c transformants, 5-hydroxymethylcytosine (5 hmC) marks are detected, indicative of the oxidative activity of the transgenic enzyme. 5-formylcytosine (5 fC) is only detectable in TET3c transformants with a DNA glycosylase mutant background suggesting further oxidation of 5 hmC residues to 5 fC by TET3c, and efficient recognition and removal of 5 fC by plant glycosylases. The results suggest that TET3c can be employed to induce heritable locus-specific changes in DNA methylation, and that accumulation of 5 hmC can be used as a marker for TET3c target regions.

Abstract. Cloud computing is an increasingly popular platform for both industry and consumers. The cloud presents a number of unique security issues, such as a high level of distribution and system homogeneity, which require special consideration. In this paper we introduce a resilience architecture consisting of a collection of self-organising resilience managers distributed within the infrastructure of a cloud. More specifically we illustrate the applicability of our proposed architecture under the scenario of malware detection. We describe our multi-layered solution at the hypervisor level of the cloud nodes and consider how malware detection can be distributed to each node.

DNA methylation in plants targets cytosines in three sequence contexts, CG, CHG and CHH (H representing A, C or T). Each of these patterns has traditionally been associated with distinct DNA methylation pathways with CHH methylation being controlled by the RNA dependent DNA methylation (RdDM) pathway employing small RNAs as a guide for the de novo DOMAINS REARRANGED METHYLTRANSFERASE (DRM2), and maintenance DNA METHYLTRANSFERASE1 (MET1) being responsible for faithful propagation of CG methylation. Here we report an unusual ‘dense methylation’ pattern under the control of MET1, with methylation in all three sequence contexts. We identified epi-alleles of dense methylation at a non coding RNA locus (At4g15242) in Arabidopsis ecotypes, with distinct dense methylation and expression characteristics, which are stably maintained and transmitted in genetic crosses and which can be heritably altered by depletion of MET1. This suggests that, in addition to its classical CG maintenance function, at certain loci MET1 plays a role in creating transcriptional diversity based on the generation of independent epi-alleles. Database inspection identified several other loci with MET1-dependent dense methylation patterns. Arabidopsis ecotypes contain distinct epi-alleles of these loci with expression patterns that inversely correlate with methylation density, predominantly within the transcribed region. In Arabidopsis, dense methylation appears to be an exception as it is only found at a small number of loci. Its presence does, however, highlight the potential for MET1 as a contributor to epigenetic diversity, and it will be interesting to investigate the representation of dense methylation in other plant species.