Abstract. In this short survey, we provide an overview of obfuscation and then shift our focus to outlining various non-trivial control-flow obfuscation techniques. Along the way, we highlight two transforms having provable security properties: the dispatcher model and opaque predicates. We comment on the strength and weaknesses of these transforms and outline difficulties associated in generating generalised classes of these.

Abstract. An obfuscation aims to transform a program, without affecting the functionality, so that some secret information within the program can be hidden for as long as possible from an adversary. Proving that an obfuscating transform is correct (i.e. it preserves functionality) is considered to be a challenging task.In this paper we show how data refinement can be used to specify imperative data obfuscations. An advantage of this approach is that we can establish a framework in which we can prove the correctness of our obfuscations. We demonstrate our framework by considering some examples from obfuscation literature. We show how to specify these obfuscations, prove that they are correct and produce generalisations.

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Abstract-Aliasing occurs when two variables refer to the same memory location. This technique has been exploited for constructing resilient obfuscation transforms in languages that extensively use indirect referencing. The theoretical basis for these transforms is derived from the hard complexity results of precisely determining which set of variables refer to the same memory location at a given program point during execution. However, no method is known for randomly generating hard problem instances. Unless we are able to evaluate the obfuscatory strength of these transforms using static analysis tools, we cannot correlate the resilience expected in theory with what actually holds in practice. In this contribution, we will outline the main difficulties in experimentally evaluating obfuscatory strength and give an overview of techniques that are suited for analysing wellestablished alias-based obfuscation transforms.

Manufacturing industry can improve its competitiveness through innovation and technological excellence, and appropriate Industrial Learning can help to achieve this goal through allowing the manufacturing workforce to acquire new skills related to the advanced developments in information and communication technologies. This raises the need for new Industrial Learning tools and methods from the viewpoint of learning content, learning processes, and delivery mechanisms. In this paper, we present a generic competence-based approach for Industrial Learning developed in the framework of ActionPlanT project. The approach is composed of (i) an Industrial Learning model which serves to represent and understand competence-based learning, and (ii) a methodology which implements through a number of steps the Industrial Learning actions defined using the Industrial Learning model in industrial organisations. Both the model and the methodology are presented in details. A metrics-based method for evaluating the implementation of the learning actions defined using the approach is also described