Certifying Services in Cloud: The Case for a Hybrid, Incremental and Multi-layer Approach

The use of clouds raises significant security concerns for the services they provide. Addressing these concerns requires novel models of cloud service certification based on multiple forms of evidence including testing and monitoring data, and trusted computing proofs. CUMULUS is a novel infrastructure for realising such certification models

Security Attributes Based Digital Rights Management

Most real-life systems delegate responsibilities to different authorities. We apply this model to a digital rights management system, to achieve flexible security. In our model a hierarchy of authorities issues certificates that are linked by cryptographic means. This linkage establishes a chain of control, identity-attribute-rights, and allows flexible rights control over content. Typical security objectives, such as identification, authentication, authorization and access control can be realised. Content keys are personalised to detect illegal super distribution. We describe a working prototype, which we develop using standard techniques, such as standard certificates, XML and Java. We present experimental results to evaluate the scalability of the system. A formal analysis demonstrates that our design is able to detect a form of illegal super distribution

Big Data Assurance Evaluation: An SLA-Based Approach.

The Big Data community has started noticing that there is the need to complete Big Data platforms with assurance techniques proving the correct behavior of Big Data analytics and management. In this paper, we propose a Big Data assurance solution based on Service-Level Agreements (SLAs), focusing on a platform providing Model-based Big Data Analytics-as-a-Service (MBDAaaS)

Blockchain-Based Distributed Trust and Reputation Management Systems: A Survey

Distributed Ledger Technologies (DLTs), like Blockchain, are characterized by features such as transparency, traceability, and security by design. These features make the adoption of Blockchain attractive to enhance information security, privacy, and trustworthiness in very different contexts. This paper provides a comprehensive survey and aims at analyzing and assessing the use of Blockchain in the context of Distributed Trust and Reputation Management Systems (DTRMS). The analysis includes academic research as well as initiatives undertaken in the business domain. The paper defines two taxonomies for both Blockchain and DTRMS and applies a Formal Concept Analysis. Such an approach allowed us to identify the most recurrent and stable features in the current scientific landscape and several important implications among the two taxonomies. The results of the analysis have revealed significant trends and emerging practices in the current implementations that have been distilled into recommendations to guide Blockchain's adoption in DTRMS systems

Understanding the connection between platelet-activating factor, a UV-induced lipid mediator of inflammation, immune suppression and skin cancer.

none2siLipid mediators of inflammation play important roles in several diseases including skin cancer, the most prevalent type of cancer found in the industrialized world. Ultraviolet (UV) radiation is a complete carcinogen and is the primary cause of skin cancer. UV radiation is also a potent immunosuppressive agent, and UV-induced immunosuppression is a well-known risk factor for skin cancer induction. An essential mediator in this process is the glyercophosphocholine 1-alkyl-2-acetyl-sn-glycero-3-phosphocholine commonly referred to as platelet-activating factor (PAF). PAF is produced by keratinocytes in response to diverse stimuli and exerts its biological effects by binding to a single specific G-protein-coupled receptor (PAF-R) expressed on a variety of cells. This review will attempt to describe how this lipid mediator is involved in transmitting the immunosuppressive signal from the skin to the immune system, starting from its production by keratinocytes, to its role in activating mast cell migration in vivo, and to the mechanisms involved that ultimately lead to immune suppression. Recent findings related to its role in regulating DNA repair and activating epigenetic mechanisms, further pinpoint the importance of this bioactive lipid, which may serve as a critical molecular mediator that links the environment (UVB radiation) to the immune system and the epigenome.openDamiani, E; Ullrich, S.E.Damiani, Elisabetta; Ullrich, S. E

Low mass star formation and subclustering in the HII regions RCW 32, 33 and 27 of the Vela Molecular Ridge. A photometric diagnostics to identify M-type stars

Most stars born in clusters and recent results suggest that star formation (SF) preferentially occurs in subclusters. Studying the morphology and SF history of young clusters is crucial to understanding early SF. We identify the embedded clusters of young stellar objects (YSOs) down to M stars, in the HII regions RCW33, RCW32 and RCW27 of the Vela Molecular Ridge. Our aim is to characterise their properties, such as morphology and extent of the clusters in the three HII regions, derive stellar ages and the connection of the SF history with the environment. Through public photometric surveys such as Gaia, VPHAS, 2MASS and Spitzer/GLIMPSE, we identify YSOs with IR, Halpha and UV excesses, as signature of circumstellar disks and accretion. In addition, we implement a method to distinguish M dwarfs and giants, by comparing the reddening derived in several optical/IR color-color diagrams, assuming suitable theoretical models. Since this diagnostic is sensitive to stellar gravity, the procedure allows us to identify pre-main sequence stars. We find a large population of YSOs showing signatures of circumstellar disks with or without accretion. In addition, with the new technique of M-type star selection, we find a rich population of young M stars with a spatial distribution strongly correlated to the more massive population. We find evidence of three young clusters, with different morphology. In addition, we identify field stars falling in the same region, by securely classifying them as giants and foreground MS stars. We identify the embedded population of YSOs, down to about 0.1 Msun, associated with the HII regions RCW33, RCW32 and RCW27 and the clusters Vela T2, Cr197 and Vela T1, respectively, showing very different morphologies. Our results suggest a decreasing SF rate in Vela T2 and triggered SF in Cr197 and Vela T1.Comment: Accepted for publication in A&A; 20 pages, 22 figures, 6 table

Extending the Outreach : From Smart Cities to Connected Communities

Connected Communities (CCs) are socio-technical systems that rely on an information and communication technology (ICT) infrastructure to integrate people and organizations (companies, schools, hospitals, universities, local and national government agencies) willing to share information and perform joint decision-making to create sustainable and equitable work and living environments. We discuss a research agenda considering CCs from three distinct but complementary points of view: CC metaphors, models, and services

A Context-Aware System to Secure Enterprise Content: Incorporating Reliability Specifiers

The sensors of a context-aware system extract contextual information from the environment and relay that information to higher-level processes of the system so to influence the system\u2019s control decisions. However, an adversary can maliciously influence such controls indirectly by manipulating the environment in which the sensors are monitoring, thereby granting privileges the adversary would otherwise not normally have. To address such context monitoring issues, we extend CASSEC by incorporating sentience-like constructs, which enable the emulation of \u201dconfidence\u201d, into our proximity-based access control model to grant the system the ability to make more inferable decisions based on the degree of reliability of extracted contextual information. In CASSEC 2.0, we evaluate our confidence constructs by implementing two new authentication mechanisms. Co-proximity authentication employs our time-based challenge-response protocol, which leverages Bluetooth Low Energy beacons as its underlying occupancy detection technology. Biometric authentication relies on the accelerometer and fingerprint sensors to measure behavioral and physiological user features to prevent unauthorized users from using an authorized user\u2019s device. We provide a feasibility study demonstrating how confidence constructs can improve the decision engine of context-aware access control systems

A Deep Learning Approach to Radio Signal Denoising

This paper proposes a Deep Learning approach to radio signal de-noising. This approach is data-driven, thus it allows de-noising signals, corresponding to distinct protocols, without requiring explicit use of expert knowledge, in this way granting higher flexibility. The core component of the Artificial Neural Network architecture used in this work is a Convolutional De-noising AutoEncoder. We report about the performance of the system in spectrogram-based denoising of the protocol preamble across protocols of the IEEE 802.11 family, studied using simulation data. This approach can be used within a machine learning pipeline: the denoised data can be fed to a protocol classifier. A further perspective advantage of using the AutoEncoders in such a pipeline is that they can be co-trained with the downstream classifier (protocol detector), to optimize its accuracy