Multi-layered Security Architecture Research Articles

Comprehensive Security for IoT Devices with Kubernetes and Raspberry Pi Cluster

Environmental monitoring systems have gained prominence across diverse applications, necessitating the integration of cutting-edge technologies. This article comprehensively explores such a system, emphasizing the integration of a Raspberry Pi cluster with the BME680 environmental sensor within a Kubernetes framework. This study encompasses the technical aspects of hardware configuration and places a significant focus on security benchmarks and robustness validation. The environmental monitoring infrastructure discussed in this article delves into the intricacies of the Raspberry Pi cluster’s hardware setup, including considerations for scalability and redundancy. This research addresses critical security gaps in contemporary environmental monitoring systems, particularly vulnerabilities linked to IoT deployments. Amidst increasing threats, this study introduces a robust framework that integrates advanced security tools—HashiCorp (San Francisco, CA, USA) Vault v1.16 for dynamic secret management and OpenID Connect for authentication processes—to enhance applications and system integrity and resilience within the Kubernetes environment. The approach involves a multi-layered security architecture that fortifies the storage and management of credentials and ensures authenticated and authorized interactions within IoT networks. Furthermore, our research incorporates a series of security benchmark tests, including vulnerability scanning, penetration testing, and access control assessments. Additionally, this article addresses crucial aspects related to data management and analysis, detailing the methodologies employed for storing, processing, and deriving insights from the collected environmental data. It further explores the integration of the monitoring system with existing infrastructure and systems, facilitating seamless data sharing and interoperability and offering valuable insights into the system’s ability to withstand potential threats and vulnerabilities. The integration of Raspberry Pi clusters with BME680 environmental sensors within a Kubernetes-managed framework significantly enhances the scalability and security of IoT systems. This study quantifies the improvements, demonstrating at least a 30% enhancement in system responsiveness and a minimum 40% reduction in vulnerability exposures, as verified by extensive security benchmarks, including penetration testing. These advancements facilitate robust, scalable IoT deployments, with potential applications extending beyond environmental monitoring to include industrial and urban settings. The incorporation of dynamic secret management with HashiCorp Vault and secure authentication with OpenID Connect provides a blueprint for developing resilient IoT architectures capable of supporting high-security and high-availability applications. In conclusion, this article contributes to the expanding body of knowledge in IoT and environmental monitoring and establishes a strong foundation for future work. These outcomes suggest promising directions for further research in secure IoT applications and present practical implications for the deployment of secure and scalable IoT solutions in critical infrastructures.

IoT Security in the Era of Ubiquitous Computing: A Multidisciplinary Approach to Addressing Vulnerabilities and Promoting Resilience

The Internet of Things (IoT) has rapidly become a pivotal, transformative force, seamlessly integrating billions of physical devices through sophisticated networks of embedded sensors, software, and internet connectivity. This expansive and interconnected ecosystem offers a broad spectrum of applications, significantly benefiting urban infrastructure with innovative solutions, enhancing industrial operations through optimization, and enriching consumer experiences with smart devices for safety and convenience. Despite the numerous benefits, the widespread adoption of IoT technologies has challenges, particularly in security and privacy. The proliferation of IoT devices has opened up new avenues for potential cyber threats, posing risks of data breaches and privacy violations. An in-depth analysis of notable IoT security incidents, such as the 2015 Jeep Hack, the Owlet WiFi Baby Heart Monitor Hack, and the TRENDnet Webcam Hack, highlights the critical vulnerabilities inherent in many IoT systems.
 Organizations must adopt comprehensive and robust security measures to address these security concerns, including implementing advanced encryption protocols, deploying effective firewalls stringent access control mechanisms, and conducting regular security audits. A multi-layered security architecture becomes essential in mitigating such threats and ensuring the integrity of IoT networks. Furthermore, integrating blockchain technology presents a promising enhancement to IoT security and privacy protocols. Blockchain's inherent features of decentralization, transparency, and immutability offer an additional layer of security, making it more difficult for unauthorized entities to compromise IoT systems.
 Equally crucial is the need to elevate IoT security awareness among organizations; this can be achieved through persistent research, fostering collaborations with security experts, and promoting best practices in IoT security. By actively addressing these security challenges, organizations can not only harness the full potential of IoT but also protect their reputations, build trust with stakeholders, and ensure the privacy and safety of their data. Therefore, while IoT presents an array of opportunities for innovation and efficiency, the importance of vigilance in security cannot be overstated. Balancing the benefits of IoT with robust security measures will be vital to realizing its full potential safely and reliably.

Security-Level Improvement of IoT-Based Systems Using Biometric Features

The Internet of Things (IoT) is reported as a main research topic in the current decade. It will be possible to connect smart devices to each other using IoT, a platform such as the Internet. However, the expansion and intrusion of such a large network raises some new security issues and risks related to the disclosure of user confidential information where these devices are subject to hacker threats and intrusions. Traditional security systems were password based. In this paper, after reviewing the actions taken in this regard, the improvement level of biometric security compared with traditional password-based methods will be proven in section three using the Markov model. By considering the results of the evaluation, the probability of occurrence of security problems is decreased by 90.71% by applying biometric features. Then, multi-layer security architecture with biometric features and coding systems is suggested to increase security. In the first layer, the fingerprint recognition algorithm is dependent on the module, and the U.are.U 5100 module provides more security than others. In the second layer, the Hash mechanism of the MD5 algorithm is, on average, 63.21% more efficient. By determining the properties of the first two architectural layers and ultimately for the IoT application layer, empirical methods and hardware platforms for the Internet of things are used. Concerning the simulation results, the suggested mechanism enhances the system security by 120.38% on average, which is 106.23, 110.45, and 144.46% of relative improvement compared with IoT sensors, controller layer mechanisms, and application layer mechanisms, respectively.

FACIAL CAPTURE AS A MEASURE TO SOLVING CBT EXAMINATION MALPRACTICES

The adoption of Computer Based Testing (CBT) by Nigerian Tertiary Education Institutions has helped to address some of the challenges relating to the conduct of examinations and results processing. The most prominent of these challenges is the impersonation and to tackle these eventualities, multi-layered security architecture is implemented to ensure the authenticity of the student participating in the CBT. The architecture will assist Nigerian University administrators to effectively plan the conduct of CBT and develop in-house solution that will engender the reduction in the examination malpractices in CBT. The introduction of the facial capture reduced the intents of the students in engaging in the act of impersonation. The first security layer is the profiling of the registered students that are eligible to partake in the test, the second layer is the biometric capture to identify and authenticate that the student is the original person to partake in the test. The third layer is the facial capture on the system before the commencement of the test. The proposed system will be designed and implemented using algorithmic approach and a web-based application which will be deployed on the LAN of the institution. Therefore, this research presents the implementation of the multi-tiered layered security in mitigating the incidences of impersonation during CBT.

Free-space optical channel estimation for physical layer security.

We present experimental data on message transmission in a free-space optical (FSO) link at an eye-safe wavelength, using a testbed consisting of one sender and two receiver terminals, where the latter two are a legitimate receiver and an eavesdropper. The testbed allows us to emulate a typical scenario of physical-layer (PHY) security such as satellite-to-ground laser communications. We estimate information-theoretic metrics including secrecy rate, secrecy outage probability, and expected code lengths for given secrecy criteria based on observed channel statistics. We then discuss operation principles of secure message transmission under realistic fading conditions, and provide a guideline on a multi-layer security architecture by combining PHY security and upper-layer (algorithmic) security.

A Multi-Layer Security Architecture for Wireless Cognitive Sensor Networks in Smart Grids

Wireless sensor networks have been extensively deployed in the electric power systems for sensing, transmission and control, which provide more opportunities for wireless low power radios to operate. As the next generation electricity system, the smart grid should possess the capability to transmit reliable and real-time information to the control centers of the utilities. In order to solve the issues such as heterogeneous coexistence, spectrum scarcity, tremendous data processing and Security guarantees, revolutionary communication architecture is urgently demanded. In this paper, after analyzing the hierarchical structure of smart grid and illustrating the principle of WCSN in smart grids, we propose the security architecture of wireless sensor networks based on cognitive radio for smart grids, which can be used as a reference to design and develop the Wireless Cognitive Sensor Network (WCSN) security schemes in the electric power systems.

A Detailed Analysis of the Issues and Solutions for Securing Data in Cloud

Cloud computing, the next generation architecture of IT enterprises, offers us with a flexible computing environment. In cloud, the virtualized resources are provided as a service over the internet. Typical applications that have already been thought of are SaaS (Software as a Service), PaaS (Platform as a Service), IaaS (Infrastructure as a Service) etc., which may provide common business applications online that is to be accessed from a web browser. Unlike traditional computing, the cloud moves the application software and databases to a set of networked resources. This enables the data to be accessed from anywhere and anybody simultaneously. Due to the fast growing markets of the cloud and also because of its unique nature, data security in cloud is an important concern. In order to secure the data in cloud, we have to ensure that the data is protected in every level during its flow and also during its storage. In this paper we identify and classify different threats to the data residing in a cloud and also provide separate solutions to these attacks. We also propose a multi-layered security architecture which can ensure the data security aspects and protect the data as it flows from browser to server level.