Internet of Things (IoT) has gained increasing visibility among emerging technologies and undoubtedly changing our daily life. Its adoption is strengthened by the growth of connected devices (things) as shown in recent statistics. However, as the number of connected things grows, responsibility related to security aspects also needs to increase. For instance, cyberattacks might happen if simple authentication mechanisms are not implemented on IoT applications, or if access control mechanisms are weakly defined. Considering the relevance of the subject, we performed a systematic literature review (SLR) to identify and synthesize security issues in IoT discussed in scientific papers published within a period of 8 years. Our literature review focused on four main security aspects, namely authentication, access control, data protection, and trust. We believe that a study considering these topics has the potential to reveal important opportunities and trends related to IoT security. In particular, we aim to identify open issues and technological trends that might guide future studies in this field, thus providing useful material both to researchers and to managers and developers of IoT systems. In this paper, we describe the protocol adopted to perform the SLR and present the state-of-the-art on the field by describing the main techniques reported in the retrieved studies. To the best of our knowledge, ours is the first study to compile information on a comprehensive set of security aspects in IoT. Moreover, we discuss the placement, in terms of architectural tiers, for deploying security techniques, in an attempt to provide guidelines to help design decisions of security solution developers. We summarize our results showing security trends and research gaps that can be explored in future studies.

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With the increase of the search for computational models where the expression of parallelism occurs naturally, some paradigms arise as options for the current generation of computers. In this context, dynamic dataflow and Gamma—General Abstract Model for Multiset mAnipulation—emerge as interesting computational model choices. In dynamic dataflow model, operations are performed as soon as their associated operands are available, without rely on a Program Counter to dictate the execution order of instructions. The Gamma paradigm is based on a parallel multiset rewriting scheme. It provides a nondeterministic execution model inspired by an abstract chemical machinemetaphor, where operations are formulated as reactions that occur freely among matching elements belonging to the multiset. In this work, equivalence relations between the dynamic dataflow and Gamma paradigms are exposed and explored, while methods to convert from dataflow to Gamma paradigm and vice versa are provided. It is shown that vertices and edges of a dynamic dataflow graph can correspond, respectively, to reactions and multiset elements in the Gamma paradigm. This work provides the scientific community with the possibility of taking profit of both parallel programming models, contributing with a versatility component to researchers and developers.