A Proof of Concept SRAM-based Physically Unclonable Function (PUF) Key Generation Mechanism for IoT Devices

Current research in Internet of Things (IoT) is focused on the security enhancements to every communicated message in the network. Keeping this thought in mind, researcher in this work emphasizes on a security oriented cryptographic solution. Commonly used security cryptographic solutions are heavy in nature considering their key size, operations, and mechanism they follow to secure a message. This work first determines the benefit of applying lightweight security cryptographic solutions in IoT. The existing lightweight counterparts are still vulnerable to attacks and also consume calculative more power. Therefore, this research work proposes a new hybrid lightweight logical security framework for offering security in IoT (LLSFIoT). The operations, key size, and mechanism used in the proposed framework make its lightweight. The proposed framework is divided into three phases: registration, authentication, and light data security (LDS). LDS offers security by using unique keys at each round bearing small size. Key generation mechanism used is comparatively fast making the compromise of keys as a difficult task. These steps followed in the proposed algorithm design make it lightweight and a better solution for IoT-based networks as compared to the existing solutions that are relatively heavy weight in nature.

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Evaluation of Physical Layer Secret Key Generation for IoT Devices

2019 IEEE 20th Wireless and Microwave Technology Conference (WAMICON) ◽

10.1109/wamicon.2019.8765465 ◽

2019 ◽

Cited By ~ 1

Author(s):

Marko Jacovic ◽

Martin Kraus ◽

Geoffrey Mainland ◽

Kapil R. Dandekar

Keyword(s):

Physical Layer ◽

Key Generation ◽

Secret Key ◽

Secret Key Generation ◽

Iot Devices

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A Simple Secret Key Generation by Using a Combination of Pre-Processing Method with a Multilevel Quantization

Entropy ◽

10.3390/e21020192 ◽

2019 ◽

Vol 21 (2) ◽

pp. 192 ◽

Cited By ~ 4

Author(s):

Mike Yuliana ◽

Wirawan ◽

Suwadi

Keyword(s):

Physical Layer Security ◽

Processing Method ◽

Communication Security ◽

Key Generation ◽

Secret Key ◽

Secret Key Generation ◽

Information Reconciliation ◽

Security Challenges ◽

Iot Devices ◽

Multilevel Quantization

Limitations of the computational and energy capabilities of IoT devices provide new challenges in securing communication between devices. Physical layer security (PHYSEC) is one of the solutions that can be used to solve the communication security challenges. In this paper, we conducted an investigation on PHYSEC which utilizes channel reciprocity in generating a secret key, commonly known as secret key generation (SKG) schemes. Our research focused on the efforts to get a simple SKG scheme by eliminating the information reconciliation stage so as to reduce the high computational and communication cost. We exploited the pre-processing method by proposing a modified Kalman (MK) and performing a combination of the method with a multilevel quantization, i.e., combined multilevel quantization (CMQ). Our approach produces a simple SKG scheme for its significant increase in reciprocity so that an identical secret key between two legitimate users can be obtained without going through the information reconciliation stage.

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Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model

Sensors ◽

10.3390/s19214642 ◽

2019 ◽

Vol 19 (21) ◽

pp. 4642

Author(s):

Roberto Casado-Vara ◽

Angel Canal-Alonso ◽

Angel Martin-del Rey ◽

Fernando De la Prieta ◽

Javier Prieto

Keyword(s):

Wide Spectrum ◽

Ecosystem Model ◽

Volterra Model ◽

Volterra Equations ◽

Proof Of Concept ◽

Smart Buildings ◽

Smart Building ◽

Iot Devices ◽

Living Organisms ◽

The Relationship

Internet of Things (IoT) is the paradigm that has largely contributed to the development of smart buildings in our society. This technology makes it possible to monitor all aspects of the smart building and to improve its operation. One of the main challenges encountered by IoT networks is that the the data they collect may be unreliable since IoT devices can lose accuracy for several reasons (sensor wear, sensor aging, poorly constructed buildings, etc.). The aim of our work is to study the evolution of IoT networks over time in smart buildings. The hypothesis we have tested is that, by amplifying the Lotka–Volterra equations as a community of living organisms (an ecosystem model), the reliability of the system and its components can be predicted. This model comprises a set of differential equations that describe the relationship between an IoT network and multiple IoT devices. Based on the Lotka–Volterra model, in this article, we propose a model in which the predators are the non-precision IoT devices and the prey are the precision IoT devices. Furthermore, a third species is introduced, the maintenance staff, which will impact the interaction between both species, helping the prey to survive within the ecosystem. This is the first Lotka–Volterra model that is applied in the field of IoT. Our work establishes a proof of concept in the field and opens a wide spectrum of applications for biology models to be applied in IoT.

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Semantic Framework for Energy-Aware Resource Management of IoT in Business Processes

International Journal of Systems and Service-Oriented Engineering ◽

10.4018/ijssoe.2018010102 ◽

2018 ◽

Vol 8 (1) ◽

pp. 21-43 ◽

Cited By ~ 2

Author(s):

Kunal Suri ◽

Walid Gaaloul ◽

Arnaud Cuccuru ◽

Sebastien Gerard

Keyword(s):

Business Processes ◽

Reference Model ◽

Optimal Management ◽

Semantic Technologies ◽

Semantic Model ◽

Proof Of Concept ◽

Energy Aware ◽

Semantic Framework ◽

Resource Conflicts ◽

Iot Devices

Recently, IoT adoption has increased in several domains. IoT devices are multi-modal and heterogeneous due to their varied properties, standards, and manufactures. This leads to interoperability issues, which can be solved using semantic technologies. Likewise, these devices participate in numerous cross-organizational business processes (BPs). Being resource-constrained, they must be managed in an energy-aware manner to avoid BP failures. However, due to lack of a common ontology and formalization of energy-related concepts impedes their optimal management in BPs. To bridge this gap, the authors capitalize on existing semantic models such as FIESTA-IoT and IoT-BPO. They propose the following: (i) formalization of IoT concepts in BPs related to energy, their properties and constraints, and (ii) resolving resource conflicts based on strategies. The feasibility of this framework is illustrated by evaluating the semantic model for its coverage of concepts from IoT-A reference model, along with proof of concept tools that allows ontology-based support for process modeling.

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Proof of Concept of Scalable Integration of Internet of Things and Blockchain in Healthcare

Sensors ◽

10.3390/s20051389 ◽

2020 ◽

Vol 20 (5) ◽

pp. 1389 ◽

Cited By ~ 4

Author(s):

Krishna Prasad Satamraju ◽

Malarkodi B

Keyword(s):

Internet Of Things ◽

Data Storage ◽

Data Integrity ◽

Security Threats ◽

Proof Of Concept ◽

Power Performance ◽

Privacy And Security ◽

Physical Threat ◽

Iot Devices ◽

Performance Results

The advent of Internet of Things (IoT) brought innovation along with unprecedented benefits of convenience and efficacy in many operations that were otherwise very cumbersome. This innovation explosion has surfaced a new dimension of vulnerability and physical threat to the data integrity of IoT networks. Implementing conventional cryptographic algorithms on IoT devices is not future-proof as these devices are constrained in terms of computational power, performance, and memory. In this paper, we are proposing a novel framework, a unique model that integrates IoT networks with a blockchain to address potential privacy and security threats for data integrity. Smart contracts are instrumental in this integration process and they are used to handle device authentication, authorization and access-control, and data management. We further share a new design model for interfaces to integrate both platforms while highlighting its performance results over the existing models. With the incorporation of off-chain data storage into the framework, overall scalability of the system can be increased. Finally, our research concludes how the proposed framework can be fused virtually into any existing IoT applications with minimal modifications.

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