Security Measures in IOT based 5G Networks

Heterogeneous Internet of Things (IoT) and multi-access mobile edge computing (MA-MEC) are believed as supporting technologies for building a smart city. The advancement and flourish of IoT are facilitating the entry of human society into the Internet of Everything era, which lay the foundation of the smart city. To address the conflict between computation capability and low-cost mobile devices in IoT, the MA-MEC is available for supporting the resource-limited and computation-sensitive services and applications by computation offloading and distributed content delivery/caching. However, deploying cloud computing capability within the radio access network may face serious security threats, which stem from not only the existing technologies and networks but also the MA-MEC-based IoT itself. Therefore, in this paper, the solutions to address the security threats are investigated from physical layer perspectives, since physical layer security technologies have the advantages of achieving perfect secrecy, low-computational complexity, and resource consumption, and good adaptation for channel changes. Specifically, we investigate the secure wiretap coding, resource allocation, signal processing, and multi-node cooperation, along with physical layer key generation and authentication, to cope with the emerging security challenges. Finally, the paper is concluded with some possible future research directions.

The Internet of Things (IoT)services and application were increasing during the last years in several life fields causes need to provide a secure identifier for protecting sensing data passing between IoT sensors/devices and embedded-subsystem connected by networks. This paper was proposed an algorithm for helping in IoT communication security can used in different IOT entities used in unofficial industrial machine to machine (M2M) communications, smart energy-grids, home or buildings and other computing devices. 
 This paper proposed a secure system using new proposed 4D chaotic system combined with the modified lightweight Advanced Encryption Standard (AES). The proposed 4-dimension (4D) chaos system Lyapunov was tested and pass for many initial periods and get a super chaos system (4 positive Lyapunov). Generated chaos keys (used JORN) were used in the lightweight AES and the Secure Hash Algorithm version 3 (SHA3-256). The Lightweight AES was design in case to reduce CPU computation cycles and complexity of AES. Results show that computation time for proposed system decreased (has 145% speedup more). The output of modified lightweight AES encryption System has the good statistical tests near to original AES that can avoid many attacks.

Background: The increasing number of Internet of Things (IoT) devices has raised worries about their susceptibility to different cyber threats. Although there have been improvements in software-level security, hardware measures continue to be essential for strong protection. Objective: The purpose of this study is to thoroughly analyze different architectural methods for ensuring hardware security in IoT devices, assessing how effective and practical they are. Methods: The study conducted a comparative investigation of different hardware security mechanisms, such as Trusted Platform Modules (TPMs), Physical Unclonable Functions (PUFs), and hardware security modules (HSMs). Information was gathered from several Internet of Things (IoT) implementations in industrial, healthcare, and consumer industries. Results: The results suggest that PUFs have notable benefits in terms of distinctiveness and protection against physical tampering, while TPMs offer extensive security capabilities but at a greater expense and level of complexity. High-security modules (HSMs) were determined to be the most effective choice for environments with high stakes that demand strict security measures. Conclusion: The selection of a suitable security method for IoT applications depends on the particular requirements and hazards associated with each application, as there is no one-size-fits-all hardware security mechanism. This paper establishes a fundamental structure for choosing and executing hardware security measures in IoT designs, improving the durability of devices against advancing cyber threats.

Security of the data is a major challenge in the deployment and management of the Internet of Things (IoT) systems in the heterogeneous environment, where data gets transferred very widely and rapidly in multiple modes across the globe. Concomitant with the advancement of the technology, the number of devices and systems which are involved in transferring the image data has increased in the heterogeneous IoT environment. At present, image processing devices have become an integral part of the IoT edge devices which can collect the images and automatically share with the network. Because of the multifaceted usage of images in multimedia applications in the IoT environment, it is essential to protect the data from unauthorized access. The Advanced Encryption Standard (AES) is a well-established cryptography algorithm used in numerous applications to protect digital data. In this paper, we present a Hardware-Software Co-Simulation with Xilinx System Generator of an AES-128 bit encryption and decryption for IoT Edge devices. Hardware Co-Simulation makes it possible to integrate a design running in an FPGA directly into Simulink simulation. AES-128 bit algorithm has been implemented on the SPARTAN-6 (XC6SLX45-CSG324) FPGA board with XILINXISE software. Authors can get the successful results for image encryption and decryption both while implementing on grey and colored images. For Hardware Co-Simulation of AES-128 bit algorithm with Xilinx system generator, a point-to-point Ethernet approach is used. This implementation is done using Xilinx ISE14.2 and MATLAB 2011a for both grey image and colored image of size 448*298.

Together with the popularity of internet of things (IoT), the information security in IoT is becoming an urgent issue. In this paper, a cryptographic coprocessor is designed to provide security for IoT sensor nodes. This design incorporates the application-specific instruction set to support popular cryptography algorithms like advanced encryption standard (AES) and elliptic curve cryptography (ECC). The tailored instruction provides good flexibility, high energy efficiency and low latency. Local instruction and data ram is integrated into our coprocessor to reduce the instruction transfer between embedded processor and the coprocessor. Our work was synthesized under TSMC 65 nm technology. The measurement results show that our design consumes 32.7 uJ for each ECC point multiplication and 3 nJ for each AES encryption and decryption when working at 10 MHz.

The Internet of Things makes it possible to exchange information between people, things and things, people and things, and makes information security more and more important. However, there are few standards in the field of information security of the Internet of Things. Therefore, based on the characteristics and application requirements of the Internet of Things environment, this paper optimizes the Advanced Encryption Standard (AES) and builds the data encryption standard DESI(Data Encryption Standard in IoT) in the Internet of Things environment.. The analysis shows that DESI has better security and is therefore suitable for encrypting data in the IoT environment. Keywords: Internet of Things, encryption standard, AES, DESI, information security.

Physical-layer key generation (PKG) establishes cryptographic keys from highly correlated measurements of wireless channels, which relies on reciprocal channel characteristics between uplink and downlink, is a promising wireless security technique for Internet of Things (IoT). However, it is challenging to extract common features in frequency-division duplexing (FDD) systems as uplink and downlink transmissions operate at different frequency bands whose channel frequency responses are not reciprocal anymore. Existing PKG methods for FDD systems have many limitations, i.e., high overhead and security problems. This article proposes a novel PKG scheme that uses the feature mapping function between different frequency bands obtained by deep learning to make two users generate highly similar channel features in FDD systems. In particular, this is the first time to apply deep learning for PKG in FDD systems. We first prove the existence of the band feature mapping function for a given environment and a feedforward network with a single hidden layer can approximate the mapping function. Then, a key generation neural network (KGNet) is proposed for reciprocal channel feature construction, and a key generation scheme based on the KGNet is also proposed. Numerical results verify the excellent performance of the KGNet-based key generation scheme in terms of randomness, key generation ratio, and key error rate. Besides, the overhead analysis shows that the method proposed in this article can be used for resource-constrained IoT devices in FDD systems.

Purpose – The purpose of this paper is to study lightweight security scheme for Internet of Things (IoT) applications using Constrained Application Protocol (CoAP). Resource-constrained characteristics of IoT systems have ushered in compelling requirements for lightweight application protocol and security suites. CoAP has already been established as the candidate protocol for IoT systems. However, low overhead security scheme for CoAP is still an open problem. Existing security solutions like Datagram Transport Layer Security (DTLS) is not suitable, particularly due to its expensive handshaking, public key infrastructure (PKI)-based authentication and lengthy ciphersuite agreement process. Design/methodology/approach – This paper proposes a lightweight security scheme in CoAP using Advanced Encryption Standard (AES) 128 symmetric key algorithm. The paper presents an object security (payload embedded)-based robust authentication mechanism with integrated key management. The paper introduces few unique modifications to CoAP header to optimize security operation and minimize communication cost. Findings – It is resilient to number of security attacks like replay attack, meet-in-the-middle attack and secure under chosen plaintext attack. This scheme is generic in nature, applicable for gamut of IoT applications. The paper proves efficacy of our proposed scheme for vehicle tracking application in emulated laboratory setup. Specifically, it compares with DTLS-enabled CoAP to establish the lightweight feature of our proposed solution. Research limitations/implications – This paper mainly focuses on implementing in-vehicle tracking systems as an IoT application and used CoAP as the application protocol. Practical implications – Such a lightweight security scheme would provide immense benefit in IoT systems so that resource constraint-sensing devices and nodes can be made secure. This would impact IoT eco systems to a large extent. Originality/value – Such kind of security suite that provides both robustness and lightweight feature is hitherto not known to the authors, particularly in CoAP for IoT applications.

Physical Layer Key Generation (PKG) has evolved as a promising technique to circumvent the problems faced by the classical symmetric key production schemes. It exploits channel reciprocity and spatial decorrelation provided by wireless medium. This paper systematically reviews the evolution of PKG technologies, discussing their working principles, performance metrics, and implementations under various scenarios such as slow-fading channels, low SNR, and multi-user environments. With recent advancements introduced—intelligent reflecting surfaces (RIS/STAR-RIS), optimization powered by AI/ML, and their integration with massive MIMO and terahertz communications—chaos, robustness, and scalability enhancements are investigated. Further exploration involves application domains from IoT and healthcare to Industry 4.0 and 6G networks, this focus shifting from proof of feasibility to full-fledged implementation. The concluded findings show that PKG is inclined to become a key security primitive for next-generation wireless systems to enjoin lightweight and efficient friendly key management schemes.

The purpose of the present study is presenting a model for the use of Internet of Things in Iranian knowledge companies. This research from propose point of view is an applied research and in terms of exploration and data collection is qualitative and quantitative research. The main approach for achieving the model of using the Internet of Things is the grounded theory methodology which is based on a paradigmatic model. The research population for the qualitative sector is comprised of 25 executives and practitioners of knowledge-based companies who are somehow specialized in Internet of Things topics. They were selected by snowball method and for a small portion of all managers and technology experts working in knowledge companies. Cochran's formula for finite communities was used to select the samples. After careful analysis of the interviews, 59 extracted concepts were identified in 5 main categories and 13 subcategories. Management requirements, customer requirements, and resistance economics give rise to the Internet of Things in knowledge-based companies. The characteristics of the company, the characteristics of the human resources and the characteristics of the managers can provide a suitable ground for using the Internet of Things. And the conditions in the country, international pressures and international cooperation can be among the intermediary factors influencing the use of the Internet of Things. Raw materials and infrastructure can also be effective strategies for using the Internet of Things. Using Internet of Things, customer-related factors, international collaborations, and expected results can be expected in knowledge-based companies.

Outbreak of coronavirus (COVID-19) has resulted in lockdowns and many healthcare systems around the world getting overwhelmed. In time of pandemic, Internet of Things (IoT) and, especially, Internet of Medical Things (IoMT) can be leveraged to ease the strain put onto local hospitals and healthcare providers through preventive medicine and telemedicine. This paper offers state-of-the-art review of current use of Internet of Things within healthcare systems in the context of tackling COVID-19. It also suggests future research for battling COVID-19 through IoT, using it for purposes such as social distancing, contact tracing, health monitoring, and early diagnosing.

Multimedia communication is revolutionizing all major spheres of human life. The advent of IoT and its applications in many fields like sensing, healthcare and industry, result exponential increase in multimedia data, that needs to be shared over insecure networks. IoT driven setups are however constrained in terms of resources as a result of their small size. From data security point of view a conventional algorithms cannot be used for data encryption on an IoT platform given the resource constraints. The work presented in this paper studies the performance of SIMON cryptographic algorithm and proposes a light-weight-cryptography algorithm based on SIMON for its possible use in an IoT driven setup. The focus is on speed enhancement benefitting from software prospective, making it different than common studies mostly reflecting hardware implementations. To achieve performance in practical prospective, the contribution looks into SIMON cipher’s characteristics considering utilizing it for internet of things (IoT) healthcare applications. The paper suggests further improvement to implement the original SIMON cryptography in order to reduce the encryption time and maintain the practical trade-off between security and performance. The proposed work has been compared to Advanced Encryption Standard (AES) and the original SIMON block cipher algorithms in terms of execution time, memory consumption. The results show that the proposed work is suitable for securing data in an IoT driven setup.

Physical layer key generation is a promising privacy protection technique suitable for devices with limited computational ability. In this work, we design a key generation algorithm based on orthogonal frequency-division multiplexing (OFDM) waveforms and implement the algorithm on a testbed. By exploiting the holistic channel state information (CSI), we improve the key generation rate (KGR) significantly. The performance of the algorithm and the secrecy of generated keys are evaluated by experimentation. Then, we design a cross-layer encryption protocol based on our key generation algorithm and the Advanced Encryption Standard (AES). We provide a mathematical framework to show that the secrecy of the encryption is enhanced compared to traditional encryption schemes with one pre-shared key (e.g., WPA2-PSK), even when some generated keys are leaked to the eavesdropper. The results lead to practical and robust applications of physical layer key generation.

Daily activities have been increasingly supported by intelligent devices and applications. Smart devices are constantly communicating through the Internet of Things (IoT) networks, either by sending collected data and notifying the actions taken or by receiving instructions for actions to be taken. Most of this communication requires the confidentiality of data through the usage of encryption algorithms, being the Advanced Encryption Standard (AES) algorithm one of the most used. However, how do the operation modes of AES algorithm perform in a resource-constraint device? This paper aims to evaluate the impact on the time to encrypt and decrypt different sized messages in IoT devices when using each one of the five AES modes of operation and the three key sizes defined. The test scenario was implemented using two programming languages, running on a Raspberry Pi device. The results achieved infers that Python was quicker and had a more homogeneous result set than JavaScript implementation in most AES operation modes. These results help to understand the trade-off between IoT devices' security needs and delays in communication caused by the selection of the AES algorithm operation mode.

Smart grid is the upgradation of the existing grid in terms of cost, communication infrastructure, internet of things and reliable technologies. In ambitious flagship programme of digital India-project an initiative of India, the potential fields of the missions are identified in the area are smart energy, smart grids, smart homes and smart cities. More than 100 smart cities are planned for information and communication technology driven solutions with big data analytics in India. The exponential growth in smart grids has given certain security risks, cyber threats and protection of stored data as Nation security. Smart Grids, comprising of several communication, monitoring intelligent, metering and electrical equipment used in power grid, have a greater exposure to grid security and cyber-attacks which are potentially disrupt distribution in a city. The paper discusses the electrical grid, challenges in smart grid and the use of Advanced Encryption Standard (AES) algorithm enable with field-programmable gate array (FPGA) hardware in smart grids. The AES encryption and decryption chip is designed in Xilinx ISE 14.2 software, synthesized on SPARTAN-3E FPGA and verified with some test cases to ensure that AES can be employed in smart grid security and communication infrastructure.