As the number of IoT devices grows, ensuring the secure validation and processing of the data they generate has become critical. This challenge becomes even more pronounced for mobile nodes, such as vehicles, which must continually reconnect to new Edge Servers while in motion. This work proposes a decentralized architecture for connecting IoT devices to Edge Servers, enabling secure data delivery to applications while minimizing overhead and ensuring trustworthy handovers between Edge Servers. A fundamental concern is the integrity of Edge Servers, as they may be compromised or exhibit malicious behavior. To address this, the proposed architecture relies on an external verifier service to continuously verify the integrity of Edge Servers. To demonstrate its feasibility, two prototypes were implemented using distinct consensus technologies and evaluated under realistic conditions. The first prototype, based on BFT-SMaRt, achieved lower latency and higher throughput but required dedicated, proprietary infrastructure and lacked global auditability. In contrast, the second prototype, leveraging an existing blockchain network, provides complete auditability and decentralization without proprietary infrastructure, though at the cost of higher latency. Experimental results confirm that both approaches deliver strong security guarantees, with trade-offs between performance and transparency, validating the architecture’s suitability for dynamic IoT environments.

Quantum Computing (QC) is a fast-growing field that has enhanced the emergence of new programming languages and frameworks. Furthermore, the increased availability of computational resources has also contributed to an influx in the development of quantum programs. Given that classical and QC are significantly different due to the intrinsic nature of quantum programs, several aspects of QC (e.g., performance, bugs) have been investigated, and novel approaches have been proposed. However, from a purely quantum perspective, maintenance, one of the major steps in a software development life-cycle, has not been considered by researchers yet. In this paper, we fill this gap and investigate the prevalence of code smells in quantum programs as an indicator of maintenance issues. We defined eight quantum-specific smells and validated them through a survey with 35 quantum developers. Since no tool specifically aims to detect quantum smells, we developed a tool called QSmell that supports the proposed quantum-specific smells. Finally, we conducted an empirical investigation to analyze the prevalence of quantum-specific smells in 15 open-source quantum programs. Our results showed that 11 programs (73.33%) contain at least one smell and, on average, a program has three smells. Furthermore, the long circuit is the most prevalent smell present in 53.33% of the programs.

Due to the increasing demand for Internet of Things (IoT) applications with sensitive data, the use of encryption on constrained devices is crucial for protecting and ensuring privacy and security. The devices used in such applications have limited computational power, memory, and energy resources, making them vulnerable to attacks that exploit these limitations. Lightweight cryptography has been growing fast in recent years aiming to circumvent the lack of security in these types of devices. We propose a modular solution that capitalizes on the strengths of lightweight cryptography to offer an approach that can be easily adapted to meet the needs of private wireless sensor networks. The solution is designed to work in multi-hop communication networks, where Nodes out of range of the Gateway can be part of the network, offering the same security level that a Node in the communication range of the Gateway has. To further enhance the security and lifetime of the network, our solution incorporates a key renewal mechanism and supports the use of signature schemes for integrity. Additionally, it is designed to be distributed to achieve high levels of scalability. Experimental results show that using our solution on top of standard communication protocols does not introduce significant overhead in terms of performance.

A simple notion of quantum Turing machine with deterministic, classical control is proposed and shown to be powerful enough to compute any unitary transformation that is computable by a finitely generated quantum circuit. An efficient universal machine with the s-m-n property is presented. The BQP class is recovered. A robust notion of plain Kolmogorov complexity of quantum states is proposed and compared with those previously reported in the literature.

Antunes, Fortnow, van Melkebeek and Vinodchandran captured the notion of non-random information by computational depth, the difference between the polynomial-time- bounded Kolmogorov complexity and traditional Kolmogorov complexity. We show unconditionally how to probabilistically find satisfying assignments for formulas that have at least one assignment of logarithmic depth. The converse holds under a standard hardness assumption though fails if BPP = FewP = EXP. We also show that assuming good pseudorandom generators one cannot increase the depth of a string efficiently.

Algorithmic entropy and Shannon entropy are two conceptually different information measures, as the former is based on size of programs and the later in probability distributions. However, it is known that, for any recursive probability distribution, the expected value of algorithmic entropy equals its Shannon entropy, up to a constant that depends only on the distribution. We study if a similar relationship holds for Rényi and Tsallis entropies of order α, showing that it only holds for Rényi and Tsallis entropies of order 1 (i.e., for Shannon entropy). Regarding a time bounded analogue relationship, we show that, for distributions such that the cumulative probability distribution is computable in time t(n), the expected value of time-bounded algorithmic entropy (where the alloted time is nt(n) log(nt(n))) is in the same range as the unbounded version. So, for these distributions, Shannon entropy captures the notion of computationally accessible information. We prove that, for universal time-bounded distribution mt(x), Tsallis and Rényi entropies converge if and only if a is greater than 1.