Cluster Layout Planarity testing Booth/Lueker and Boyer/Myrvold Cluster (Feng et al) Upward (Bertolazzi et al) Customizable planarization method Edge insertion (fixed & variable embedding) Crossing Minimization optimal, minor-monotone, simultaneous Orthogonal layout Compaction (constructive + improvement) Customizable Sugiyama layout Energy-based layout (FM, ) Tree-, Circular-, Balloon-layout, 

The Open Graph Drawing Framework (OGDF)

The advent of the information age has notably amplified the importance of security. Unfortunately security considerations still widely occur as an afterthought. For many companies, security is not a requirement to conduct business and is therefore readily neglected. However the lack of security may obstruct, impede and even ruin an otherwise flourishing enterprise. Only when internal computer networks shut down, web portals are inaccessible, mail servers are attacked, or similar incidents affect the day to day business of an enterprise, security enters into the field of vision of companies. As such, security by design is only slowly becoming accepted practice.

Amongst security researchers, there is no dispute that a reasonable approach to- wards uninterrupted business activities includes security measures and controls from the beginning. To support these efforts, many security models have been developed. Graphical security models are a type of security model that help illus- trate and guide the consideration of security throughout the lifecycle of a product, system or company. Their visual properties are especially well-suited to elucidate security requirements and corresponding security measures.

During the last four years, we have developed a new graphical security model called attack–defense trees. The new framework, presented in this thesis, generalizes the well-known attack trees model. Attack–defense trees formally extend attack trees and enhance them with defenses.
To be able to deploy attack–defense trees as a security support tool, we have 
equipped them with three different syntaxes: A visually appealing, graph-based syntax that is dedicated to representing security problems, an algebraic, term-based syntax that simplifies correct, formal and quantitative analysis of security scenarios and a textual syntax that is a compromise between succinct, visual representation and easy, computerized input.

We have also equipped attack–defense trees with a variety of semantics. This became necessary, since different applications require different interpretations of attack–defense trees. Besides the very specific and problem oriented propositional, De Morgan and multiset semantics, we have introduced equational semantics. The latter semantics is, in fact, an alternative, unified presentation of semantics based on equational theory. We have expressed the propositional and the multiset seman- tics in terms of the equational semantics. This facilitates algorithmic treatment since the two different semantics have a unified formal foundation.

To be able to perform quantitative security analysis, we have introduced the notion of an attribute for attack–defense trees. To guarantee that the evaluation of an attribute on two or more semantically equal attack–defense trees results in the same value, we have introduced the notion of a compatibility condition between semantics and attributes. We have also provided usability guidelines for attributes. These guidelines help a user to specify security-relevant questions that can unambiguously be answered using attributes.
We have performed several case studies that allowed us to test and improve the attack–defense tree methodology. We have provided detailed explanations for our design choices during the case studies as well as extensive applicability guidelines that serve a prospective user of the attack–defense tree methodology as a user manual.

We have demonstrated the usefulness of the formal foundations of attack–defense trees by relating attack–defense terms to other scientific research disciplines. Con- cretely, we have shown that attack–defense trees in the propositional semantics are computationally as complex as propositional attack trees. Moreover, we have described how to merge Bayesian networks with attack–defense trees and have il- lustrated that attack–defense trees in the propositional semantics are equivalent to a specific class of games frequently occurring in game theory.

Concluding the thesis, we have related the attack–defense tree methodology to other graphical security models in an extensive literature overview over similar methodologies.

Attack-Defense Trees

https://hal.inria.fr/hal-00657306/document

Building safe PaaS clouds: A survey on security in multitenant software platforms

ADTool is free, open source software assisting graphical modeling and quantitative analysis of security, using attack---defense trees. The main features of ADTool are easy creation, efficient editing, and automated bottom-up evaluation of security-relevant measures. The tool also supports the usage of attack trees, protection trees and defense trees, which are all particular instances of attack---defense trees.

/pdf/adtool-security-analysis-with-attack-defense-trees-4qpyha5cz1.pdf

ADTool: security analysis with attack---defense trees

System and method for supporting per-program classpath and class sharing in a multi-tasking virtual machine. A virtual machine may allow each program to specify its classpath independently of other programs classpaths. Tasks that specify identical classpaths for their respective class loaders may share the runtime representation of classes. A multi-tasking virtual machine may generate and compare canonical forms of classpaths to determine which programs may share classes with each other. The runtime representation of a class may be split between shared and private portions of the runtime representation. A shared runtime representation may be associated with multiple private runtime representations. In one embodiment, unique class loader keys and a system dictionary may be used to associate tasks, class loaders and the shared representations of classes.

Supporting per-program classpaths with class sharing in a multi-tasking virtual machine

The Java™ 2 Platform, Enterprise Edition (J2EE™), is established as the standard platform for hosting enterprise applications written in the Java programming language. Similar to an operating system, a J2EE server can host multiple applications, but this is problematic due to limitations on scalability, weak inter-application isolation and inadequate resource management facilities in the underlying Java platform. These limitations lead to a proliferation of server instances with a consequent dramatic increase in the total memory footprint and more complex system administration. The Multi-tasking Virtual Machine (MVM) solves this problem by providing an efficient and scalable implementation of the isolate API for multiple, isolated tasks, enabling the co-location of multiple server instances in a single MVM process. Isolates also enable the restructuring of a J2EE server implementation as a collection of isolated components, offering increased flexibility and reliability. The resulting system is a step towards a complete and scalable operating environment for enterprise applications. Copyright © 2006 John Wiley & Sons, Ltd.

/pdf/scaling-j2ee-application-servers-with-the-multi-tasking-57ohzlkphz.pdf

Scaling J2EE™ application servers with the multi-tasking virtual machine

This paper addresses problem of the middleware for Next Generation Grid construction and presents how two important concepts such as virtualization and provisioning could satisfy some major requirements of these systems. A vision of NGG is presented and requirements set on middleware layer are analyzed. Next an enabling technology for NGG is considered . The concept of virtualization and provisioning of grid resources is explained. Finally case study illustrating N1 technology application usage is presented.

Role of n1 technology in the next generation grids middleware

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Scaling J2EE™ application servers with the multi-tasking virtual machine

Role of n1 technology in the next generation grids middleware