The Internet of things (IoT) is intended for ubiquitous connectivity among different entities or “things”. While it provides effective and efficient solutions to many real world challenges, the security aspect of it has always been questioned. The situation is further exacerbated by the number of connected devices growing exponentially. As a result, security and privacy has emerged as a significant challenge for the IoT. In this paper, we aim to provide a thorough survey on IoT security and privacy challenges from the perspective of technologies and architecture used. This work focuses on IoT intrinsic vulnerabilities and their implications to the fundamental information security challenges in confidentiality, integrity, and availability. The approach of this survey is to summarize and synthesize published work in IoT; relate it to the security conjuncture of the field; and project future research directions.

Security presents itself as one of the biggest threats to the enabling and the deployment of the Internet of Things (IoT). Security challenges are evident in light of recent cybersecurity attacks that targeted major internet service providers and crippled a significant portion of the entire Internet by taking advantage of faulty and ill-protected embedded devices. Many of these devices reside at home networks with user-administrators who are not familiar with network security best practices, making them easy targets for the attackers. Therefore, security solutions are needed to navigate the insecure and untrusted public networks by automating protections through affordable and accessible first-hand network information sharing. This paper proposes and implements a proof of concept (PoC) to secure Internet Service Providers (ISPs), home networks, and home-based IoT devices using blockchain technologies. The results obtained support the idea of a distributed cyber threat intelligence data sharing network capable of protecting various stakeholders.

The convergence of Information Technology (IT) and Operational Technology (OT) has heightened the need for robust cyber-risk assessment, which requires the identification of potential risky breaches and effective mitigation. Identifying the most crucial attack techniques correlating with increased cybersecurity risk is a critical step in this process. Traditional frameworks for this task often rely on expert opinions and intuitions, leading to overconfidence, inaccurate risk estimates, and inefficient mitigation suggestions. This paper presents an innovative method that uses machine learning models to perform risk assessments, identify high-risk techniques, and suggest appropriate mitigation and detection strategies. To achieve this, we present a unique feature engineering in which we integrated MITRE ATT&CK techniques and mapped data features to this standard universal framework, labeling them with the Common Vulnerability Scoring System. In addition, a probabilistic risk perspective is provided for the most relevant attack techniques in financial terms based on public information. Finally, we used statistical models to find the most frequent attack chains and build a RNN model to train a sequential model that estimated the severity score for attack chains.

The rapid adoption of the Industrial Internet of Things (IIoT) and wireless networks has introduced significant functional and cybersecurity challenges. This study aims to enhance the understanding of these concerns and identify effective mitigation measures. To achieve this, we developed a comprehensive testbed that represents industry-standard IoT architectures, incorporating commonly used elements, wireless protocols, and components. Then, we conducted a series of experiments designed to identify and assess functional and cybersecurity risks associated with IIoT deployments. We proposed mitigation measures tailored to address the identified vulnerabilities.

The Internet of Things (IoT) is intended for ubiquitous connectivity among different entities or "things". While its purpose is to provide effective and efficient solutions, security of the devices and network is a challenging issue. The number of devices connected along with the ad-hoc nature of the system further exacerbates the situation. Therefore, security and privacy has emerged as a significant challenge for the IoT. In this paper,we aim to provide a thorough survey related to the privacy and security challenges of the IoT. This document addresses these challenges from the perspective of technologies and architecture used. This work focuses also in IoT intrinsic vulnerabilities as well as the security challenges of various layers based on the security principles of data confidentiality, integrity and availability. This survey analyzes articles published for the IoT at the time and relates it to the security conjuncture of the field and its projection to the future.