Francisco Assis Nascimento

R. Oscar M. Rangel, 4500

95611-022 Taquara, RS, Brazil

Francisco is a lecturer at FIT - FACCAT, Taquara/RS, Brazil and Co-founder and CTO at sec4iot, Porto Alegre/RS, Brazil.

He completed a BSc in CS from the UFPb - João Pessoa/PB, Brazil in 1988 and an MSc in CS from Informatics Institute - UFRGS, Porto Alegre/RS, Brazil in 1992. Francisco started a Ph.D. course in CS in 2019 at Polytechnique School, PUCRS - Porto Alegre/RS, Brazil.

He has experience in CS, mainly in Design Automation for Distributed, Real-Time Embedded Systems, working on many aspects of design for computer systems in general. In his Ph.D. research, he explores machine learning techniques and distributed ledger technologies to build robust IoT-based systems.

news

Apr 13, 2022	Published and presented paper at AINA’2022.
Oct 22, 2021	Created my first github page.

selected publications

A Decentralized Federated Learning Architecture for Intrusion Detection in IoT Systems

Nascimento, Francisco Assis Moreira do, and Hessel, Fabiano

In Proceedings of the 36th International Conference on Advanced Information Networking and Applications (AINA-2022), Volume 2 2022

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Internet of Things (IoT) systems are vulnerable to several attacks, mainly due to the weakness of IoT devices, which have little computational and memory power, necessary for more sophisticated security features. In addition, IoT systems are distributed systems and thus inherit all problems related to the need to guarantee confidentiality, integrity, and availability. One of the traditional strategies to deal with these problems involves intrusion detection and prevention techniques. It is usual to implement them in a centralized way. In addition to not being scalable for IoT systems with an increasing number of devices, it implies an unacceptable single point of failure. Besides, sending all collected data to a centralized server in the cloud poses a great risk to the privacy of information. This paper presents a decentralized architecture for intrusion detection in IoT-based systems, which is based on federated machine learning, combined with distributed ledger technologies for access control, allowing a mechanism to minimize security risks.
A model-driven engineering framework for embedded systems design

Nascimento, Francisco Assis M., Oliveira, Marcio F. S., and Wagner, Flávio Rech

Innovations in Systems and Software Engineering 2012

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This work presents a Model-Driven Engineering (MDE) framework to improve embedded system design. The framework adopts concepts from MDE for the automatic generation of a control and data flow internal representation, starting from the functional specification of an embedded application described using UML class and sequence diagrams. By means of transformations rules applied on the UML model of the embedded system, an MOF-based (Meta Object Facility is a standard representation for meta-models and models proposed by OMG) internal representation is automatically obtained, which is iteratively mapped into a hardware/software implementation by means of model transformations. This mapping is optimized by a design space exploration (DSE) method based on a categorical graph product. The model transformations have also as input a platform model, which specifies the available hardware, software and interface resources, and produce an implementation model, on which software synthesis, communication synthesis and high-level synthesis algorithms are applied to generate the final implementation. A case study is described to illustrate the application of the framework.
MDA-based Approach for Embedded Software Generation from a UML/MOF Repository

Nascimento, Francisco A. M. do, Oliveira, Marcio F. da S., Wehrmeister, Marco A., Pereira, Carlos E., and Wagner, Flavio R.

In SBCCI2006 2006

Abs

This work presents a UML/MOF meta-modeling infrastructure, following the MDA approach, which is oriented to the design space exploration of embedded systems, based on the independent specification of application and platform. A mapping from the application into the platform is implemented by model transformations. A meta-data repository implementation is also introduced, automatically providing an Application Programming Interface (API) that is suitable to the manipulation of the UML meta-models and models and to the implementation of design tools for embedded systems. In order to illustrate the applicability of these resources, a source code generation tool for embedded software has been implemented and applied in a concrete case study.