There is a concern about possible threats deriving from the widespread adoption of IoT (Internet of Things). The number of devices connected to the Internet is going to increase dramatically, potentiating their security risks. A Distributed Denial of Service (DDoS) attack is a good candidate to explore IoT security vulnerabilities, because of the enormous number of new devices connected to the Internet there is also an increase in the number of possible compromised devices. This study aims to analyze the efficiency of a DDoS attack in a typical IoT environment, by using simulations that, in the best of our knowledge, have not been conducted yet.

Replication is a technique widely used to improve the reliability of applications. State machine replication is a special approach, where a set of computers are kept synchronised in the same state despite of failures that could occur in the system. The Raft algorithm can be used to implement a total order delivery protocol, delivering requests at the same order at all replicas, which is fundamental since in this approach all replicas must execute the same sequence of requests to present the same evolution in their states. Raft is easy to understand and implement, when compared to the Paxos algorithm. On the other hand, virtualisation can be seen as a technique that helps the development of reliable applications since it maintains each virtual machine (VM) isolated from the others. Virtualisation in data centres is changing from the traditional VMs to containers. In this context, this paper proposes KRaft, an incorporation of Raft in Kubernetes, a system that manages containers. After an evaluation of performance and resource consumption of KRaft, we found that it presents performance close to Raft executing on physical machines. Moreover, KRaft demands more network transmission while Raft executed in physical machines needs more processing power and memory.

Consensus is a fundamental building block for constructing reliable and fault-tolerant distributed services. Many Byzantine fault-tolerant consensus protocols designed for partially synchronous systems adopt a pessimistic approach when dealing with adversaries, ensuring safety even under the worst-case scenarios that adversaries can create. Following this approach typically results in either an increase in the message complexity (e.g., PBFT) or an increase in the number of communication steps (e.g., HotStuff). In practice, however, adversaries are not as powerful as the ones assumed by these protocols. Furthermore, it might suffice to ensure safety and liveness properties with high probability. To accommodate more realistic and optimistic adversaries and improve the scalability of BFT consensus, we propose ProBFT (Probabilistic Byzantine Fault Tolerance). ProBFT is a leader-based probabilistic consensus protocol with a message complexity of [EQUATION] and an optimal number of communication steps that tolerates Byzantine faults in permissioned partially synchronous systems. It is built on top of well-known primitives, such as probabilistic Byzantine quorums and verifiable random functions. ProBFT guarantees safety and liveness with high probability even with faulty leaders, as long as a supermajority of replicas is correct and using only a fraction (e.g., 20%) of messages exchanged in PBFT. We provide a detailed description of ProBFT's protocol and its analysis.

The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.