Recognition of Activities of Daily Living and Environments Using Acoustic Sensors Embedded on Mobile Devices

The identification of Activities of Daily Living (ADL) is intrinsic with the user’s environment recognition. This detection can be executed through standard sensors present in every-day mobile devices. On the one hand, the main proposal is to recognize users’ environment and standing activities. On the other hand, these features are included in a framework for the ADL and environment identification. Therefore, this paper is divided into two parts—firstly, acoustic sensors are used for the collection of data towards the recognition of the environment and, secondly, the information of the environment recognized is fused with the information gathered by motion and magnetic sensors. The environment and ADL recognition are performed by pattern recognition techniques that aim for the development of a system, including data collection, processing, fusion and classification procedures. These classification techniques include distinctive types of Artificial Neural Networks (ANN), analyzing various implementations of ANN and choosing the most suitable for further inclusion in the following different stages of the developed system. The results present 85.89% accuracy using Deep Neural Networks (DNN) with normalized data for the ADL recognition and 86.50% accuracy using Feedforward Neural Networks (FNN) with non-normalized data for environment recognition. Furthermore, the tests conducted present 100% accuracy for standing activities recognition using DNN with normalized data, which is the most suited for the intended purpose.This work is funded by FCT/MEC through national funds and co-funded by FEDER-PT2020 partnership agreement under the project UID/EEA/50008/2019

Post-Quantum Authentication in TLS 1.3: A Performance Study

The potential development of large-scale quantum computers is raising concerns among IT and security research professionals due to their ability to solve (elliptic curve) discrete logarithm and integer factorization problems in polynomial time. All currently used public key algorithms would be deemed insecure in a post-quantum (PQ) setting. In response, the National Institute of Standards and Technology (NIST) has initiated a process to standardize quantum-resistant crypto algorithms, focusing primarily on their security guarantees. Since PQ algorithms present significant differences over classical ones, their overall evaluation should not be performed out-of-context. This work presents a detailed performance evaluation of the NIST signature algorithm candidates and investigates the imposed latency on TLS 1.3 connection establishment under realistic network conditions. In addition, we investigate their impact on TLS session throughput and analyze the trade-off between lengthy PQ signatures and computationally heavy PQ cryptographic operations. Our results demonstrate that the adoption of at least two PQ signature algorithms would be viable with little additional overhead over current signature algorithms. Also, we argue that many NIST PQ candidates can effectively be used for less time-sensitive applications, and provide an in-depth discussion on the integration of PQ authentication in encrypted tunneling protocols, along with the related challenges, improvements, and alternatives. Finally, we propose and evaluate the combination of different PQ signature algorithms across the same certificate chain in TLS. Results show a reduction of the TLS handshake time and a significant increase of a server\u27s TLS tunnel connection rate over using a single PQ signature scheme