Biblio

Filters: Author is de Sá, Alan Oliveira  [Clear All Filters]
2023-01-06
Da Costa, Alessandro Monteiro, de Sá, Alan Oliveira, Machado, Raphael C. S..  2022.  Data Acquisition and extraction on mobile devices-A Review. 2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT). :294—299.
Forensic Science comprises a set of technical-scientific knowledge used to solve illicit acts. The increasing use of mobile devices as the main computing platform, in particular smartphones, makes existing information valuable for forensics. However, the blocking mechanisms imposed by the manufacturers and the variety of models and technologies make the task of reconstructing the data for analysis challenging. It is worth mentioning that the conclusion of a case requires more than the simple identification of evidence, as it is extremely important to correlate all the data and sources obtained, to confirm a suspicion or to seek new evidence. This work carries out a systematic review of the literature, identifying the different types of existing image acquisition and the main extraction and encryption methods used in smartphones with the Android operating system.
2020-05-04
de Sá, Alan Oliveira, Carmo, Luiz Fernando Rust da C., Santos Machado, Raphael C..  2019.  Countermeasure for Identification of Controlled Data Injection Attacks in Networked Control Systems. 2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0 IoT). :455–459.
Networked Control Systems (NCS) are widely used in Industry 4.0 to obtain better management and operational capabilities, as well as to reduce costs. However, despite the benefits provided by NCSs, the integration of communication networks with physical plants can also expose these systems to cyber threats. This work proposes a link monitoring strategy to identify linear time-invariant transfer functions performed by a Man-in-the-Middle during controlled data injection attacks in NCSs. The results demonstrate that the proposed identification scheme provides adequate accuracy when estimating the attack function, and does not interfere in the plant behavior when the system is not under attack.