Designing Novel Hardware Security Primitives for Smart Computing Devices

Smart computing devices are miniaturized electronics devices that can sense their surroundings, communicate, and share information autonomously with other devices to work cohesively. Smart devices have played a major role in improving quality of the life and boosting the global economy. They are ubiquitously present, smart home, smart city, smart girds, industry, healthcare, controlling the hazardous environment, and military, etc. However, we have witnessed an exponential rise in potential threat vectors and physical attacks in recent years. The conventional software-based security approaches are not suitable in the smart computing device, therefore, hardware-enabled security solutions have emerged as an attractive choice. Developing hardware security primitives, such as True Random Number Generator (TRNG) and Physically Unclonable Function (PUF) from electrical properties of the sensor could be a novel research direction. Secondly, the Lightweight Cryptographic (LWC) ciphers used in smart computing devices are found vulnerable against Correlation Power Analysis (CPA) attack. The CPA performs statistical analysis of the power consumption of the cryptographic core and reveals the encryption key. The countermeasure against CPA results in an increase in energy consumption, therefore, they are not suitable for battery operated smart computing devices. The primary goal of this dissertation is to develop novel hardware security primitives from existing sensors and energy-efficient LWC circuit implementation with CPA resilience. To achieve these. we focus on developing TRNG and PUF from existing photoresistor and photovoltaic solar cell sensors in smart devices Further, we explored energy recovery computing (also known as adiabatic computing) circuit design technique that reduces the energy consumption compared to baseline CMOS logic design and same time increasing CPA resilience in low-frequency applications, e.g. wearable fitness gadgets, hearing aid and biomedical instruments. The first contribution of this dissertation is to develop a TRNG prototype from the uncertainty present in photoresistor sensors. The existing sensor-based TRNGs suffer a low random bit generation rate, therefore, are not suitable in real-time applications. The proposed prototype has an average random bit generation rate of 8 kbps, 32 times higher than the existing sensor-based TRNG. The proposed lightweight scrambling method results in random bit entropy close to ideal value 1. The proposed TRNG prototype passes all 15 statistical tests of the National Institute of Standards and Technology (NIST) Statistical Test Suite with quality performance. The second contribution of this dissertation is to develop an integrated TRNG-PUF designed using photovoltaic solar cell sensors. The TRNG and PUF are mutually independent in the way they are designed, therefore, integrating them as one architecture can be beneficial in resource-constrained computing devices. We propose a novel histogram-based technique to segregate photovoltaic solar cell sensor response suitable for TRNG and PUF respectively. The proposed prototype archives approximately 34\% improvement in TRNG output. The proposed prototype achieves an average of 92.13\% reliability and 50.91\% uniformity performance in PUF response. The proposed sensor-based hardware security primitives do not require additional interfacing hardware. Therefore, they can be ported as a software update on existing photoresistor and photovoltaic sensor-based devices. Furthermore, the sensor-based design approach can identify physically tempered and faulty sensor nodes during authentication as their response bit differs. The third contribution is towards the development of a novel 2-phase sinusoidal clocking implementation, 2-SPGAL for existing Symmetric Pass Gate Adiabatic Logic (SPGAL). The proposed 2-SPGAL logic-based LWC cipher PRESENT shows an average of 49.34\% energy saving compared to baseline CMOS logic implementation. Furthermore, the 2-SPGAL prototype has an average of 22.76\% better energy saving compared to 2-EE-SPFAL (2-phase Energy-Efficient-Secure Positive Feedback Adiabatic Logic). The proposed 2-SPGAL was tested for energy-efficiency performance for the frequency range of 50 kHz to 250 kHz, used in healthcare gadgets and biomedical instruments. The proposed 2-SPGAL based design saves 16.78\% transistor count compared to 2-EE-SPFAL counterpart. The final contribution is to explore Clocked CMOS Adiabatic Logic (CCAL) to design a cryptographic circuit. Previously proposed 2-SPGAL and 2-EE-SPFAL uses two complementary pairs of the transistor evaluation network, thus resulting in a higher transistor count compared to the CMOS counterpart. The CCAL structure is very similar to CMOS and unlike 2-SPGAL and 2-EE-SPFAL, it does not require discharge circuitry to improve security performance. The case-study implementation LWC cipher PRESENT S-Box using CCAL results into 45.74\% and 34.88\% transistor count saving compared to 2-EE-SPFAL and 2-SPGAL counterpart. Furthermore, the case-study implementation using CCAL shows more than 95\% energy saving compared to CMOS logic at frequency range 50 kHz to 125 kHz, and approximately 60\% energy saving at frequency 250 kHz. The case study also shows 32.67\% and 11.21\% more energy saving compared to 2-EE-SPFAL and 2-SPGAL respectively at frequency 250 kHz. We also show that 200 fF of tank capacitor in the clock generator circuit results in optimum energy and security performance in CCAL

Security of IoT in 5G Cellular Networks: A Review of Current Status, Challenges and Future Directions

The Internet of Things (IoT) refers to a global network that integrates real life physical objects with the virtual world through the Internet for making intelligent decisions. In a pervasive computing environment, thousands of smart devices, that are constrained in storage, battery backup and computational capability, are connected with each other. In such an environment, cellular networks that are evolving from 4G to 5G, are set to play a crucial role. Distinctive features like high bandwidth, wider coverage, easy connectivity, in-built billing mechanism, interface for M2M communication, etc., makes 5G cellular network a perfect candidate to be adopted as a backbone network for the future IoT. However, due to resource constrained nature of the IoT devices, researchers have anticipated several security and privacy issues in IoT deployments over 5G cellular network. Off late, several schemes and protocols have been proposed to handle these issues. This paper performs a comprehensive review of such schemes and protocols proposed in recent times. Different open security issues, challenges and future research direction are also summarized in this review paper

Measuring Performances of a White-Box Approach in the IoT Context

The internet of things (IoT) refers to all the smart objects that are connected to other objects, devices or servers and that are able to collect and share data, in order to "learn" and improve their functionalities. Smart objects suffer from lack of memory and computational power, since they are usually lightweight. Moreover, their security is weakened by the fact that smart objects can be placed in unprotected environments, where adversaries are able to play with the symmetric-key algorithm used and the device on which the cryptographic operations are executed. In this paper, we focus on a family of white-box symmetric ciphers substitution-permutation network (SPN)box, extending and improving our previous paper on the topic presented at WIDECOM2019. We highlight the importance of white-box cryptography in the IoT context, but also the need to have a fast black-box implementation (server-side) of the cipher. We show that, modifying an internal layer of SPNbox, we are able to increase the key length and to improve the performance of the implementation. We measure these improvements (a) on 32/64-bit architectures and (b) in the IoT context by encrypting/decrypting 10,000 payloads of lightweight messaging protocol Message Queuing Telemetry Transport (MQTT)

Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses

The ongoing deployment of the fifth generation (5G) wireless networks constantly reveals limitations concerning its original concept as a key driver of Internet of Everything (IoE) applications. These 5G challenges are behind worldwide efforts to enable future networks, such as sixth generation (6G) networks, to efficiently support sophisticated applications ranging from autonomous driving capabilities to the Metaverse. Edge learning is a new and powerful approach to training models across distributed clients while protecting the privacy of their data. This approach is expected to be embedded within future network infrastructures, including 6G, to solve challenging problems such as resource management and behavior prediction. This survey article provides a holistic review of the most recent research focused on edge learning vulnerabilities and defenses for 6G-enabled IoT. We summarize the existing surveys on machine learning for 6G IoT security and machine learning-associated threats in three different learning modes: centralized, federated, and distributed. Then, we provide an overview of enabling emerging technologies for 6G IoT intelligence. Moreover, we provide a holistic survey of existing research on attacks against machine learning and classify threat models into eight categories, including backdoor attacks, adversarial examples, combined attacks, poisoning attacks, Sybil attacks, byzantine attacks, inference attacks, and dropping attacks. In addition, we provide a comprehensive and detailed taxonomy and a side-by-side comparison of the state-of-the-art defense methods against edge learning vulnerabilities. Finally, as new attacks and defense technologies are realized, new research and future overall prospects for 6G-enabled IoT are discussed

Internet of Things Architectures, Technologies, Applications, Challenges, and Future Directions for Enhanced Living Environments and Healthcare Systems: A Review

Internet of Things (IoT) is an evolution of the Internet and has been gaining increased attention from researchers in both academic and industrial environments. Successive technological enhancements make the development of intelligent systems with a high capacity for communication and data collection possible, providing several opportunities for numerous IoT applications, particularly healthcare systems. Despite all the advantages, there are still several open issues that represent the main challenges for IoT, e.g., accessibility, portability, interoperability, information security, and privacy. IoT provides important characteristics to healthcare systems, such as availability, mobility, and scalability, that o er an architectural basis for numerous high technological healthcare applications, such as real-time patient monitoring, environmental and indoor quality monitoring, and ubiquitous and pervasive information access that benefits health professionals and patients. The constant scientific innovations make it possible to develop IoT devices through countless services for sensing, data fusing, and logging capabilities that lead to several advancements for enhanced living environments (ELEs). This paper reviews the current state of the art on IoT architectures for ELEs and healthcare systems, with a focus on the technologies, applications, challenges, opportunities, open-source platforms, and operating systems. Furthermore, this document synthesizes the existing body of knowledge and identifies common threads and gaps that open up new significant and challenging future research directions.info:eu-repo/semantics/publishedVersio

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems