3D Lightweight Cryptosystem Design for IoT Applications Based on Composite S-Box

The world is already on the way of connecting everything (objects) to the internet, from refrigerators to sprinkler systems. This interconnection of objects to the internet is new computing paradigm called the Internet of Things (IoT) networks. The internet of things within the broader domains of security also requires algorithms that are secure and are able to protect the gadgets connected to the internet. There are problems concerning security, especially on the algorithms used on the IoT. This study, we managed to; (1) Collecting existing block cryptographic algorithms (maximum of ten) for authentication and encryption from different devices used on Internet of Things; (2) Analyze their avalanche effect and speed of collected cryptographic algorithms from step one if they give efficient authentication on Internet of Things; (3) Improving their speed and avalanche effect by designing a mathematical model that strengthens the avalanche effect of the algorithms. This was done by using an initial vector XORed with plaintext and final vector XORed with cipher text (4) Testing the new mathematical model if it really enhances the avalanche effect and speed on each and every algorithm tested in step one.

Since the Internet of Things (IoT) will be entwined with everything we use in our daily life, the consequence of security flaws escalates. Smart objects will govern most of the home appliances and car engines yielding potential disaster scenarios. In this context, successful attacks could lead to chaos and scary scenarios (www.darkreading.com). Unprotected personal information may expose sensitive and embarrassing data to the public and attacks may threaten not only our computers and smart devices, but our intimacy and perhaps our lives too. Because persons and objects will be bonded with each other, user consent becomes critical. Therefore, thing, object, and user Identity will be the focus of future IoT security solutions, yielding a Trust, Security, and Privacy (TSP) paradigm, which may constitute the Achilles' heel of IoT. While security issues are quite straightforward, mainly from background knowledge, privacy issues are far more complex. Privacy constitutes a rather challenging task, even for the m...

Delivering information from Internet of Things (IoT) devices to a cloud server possesses several security issues, e.g. information eavesdropping, modification, and theft. Therefore, communication between IoT devices and the cloud server should be protected by encryption methods. However, there are few encryption techniques options that are suitable for the need for lightweight communication as demanded by the IoT devices. Due to these circumstances, the NSA launched an encryption algorithm for IoT named Simon and Speck, which are maximally efficient while still providing the advertised level of security, as determined by the key size. This study aims to test and compare the Simon-Speck and AES encryption algorithms and their effect on networking performance on IoT devices. The parameters in this test are delay, throughput, the efficiency of memory usage from the encryption algorithm, and the value of the avalanche effect. Experimental results show that the Speck algorithm outperforms the Simon and the AES algorithms in terms of communication delay and memory usage. Regarding the avalanche effect values, the Simon algorithm possesses the highest avalanche effect value on average against the Speck and the AES algorithms.

The paper describes security issues of Internet of Things (IoT)-based applications like healthcare application systems. In recent years, because of increased usage of IoT devices the IoT networks are becoming prone to various security attacks. In this paper, a comprehensive study on security and privacy issues in IoT networks is provided. The IoT which has become a popular technology in recent days is a concept reflecting a connected set of anyone, anything, anytime, anyplace, any service and any network. The IoT builds smart objects, the ultimate devices in the development of healthcare information system. The usage of IoT technologies is a boon to the modern healthcare environment. Since IoT is the next stage of technological revolution, it has become a necessity to incorporate it in the medical field for the convenience it provides. Further, this paper surveys intelligent collaborative security model to minimise security risk. As opposed to the traditional Internet, in addition to humans, an IoT connects a large number of machines mobile, tablet, pc, resource-constrained devices and sensors using heterogeneous wired and wireless networks. An IoT typically has three conceptual layers consisting of perception, network and application layers.

Remote correspondence frameworks are exceedingly disposed to security perils. The critical usages of remote correspondence frameworks are in military, business, human administrations, retail, and transportations. These structures use wired, cell, or ad hoc frameworks. Remote sensor frameworks, actuator frameworks, and vehicular frameworks have gotten a fantastic thought in the open eye and industry. Of late, the Internet of things (IoT) has become broad research thought. The IoT is considered as possible destiny of the Web. In future, IoT will accept a vital activity and change our living styles, standards, similarly to game plans. The use of IoT in different applications is required to rise rapidly in the coming years. The IoT grants billions of devices, society, and organizations to connect with others and exchange information. Due to the extended usage of IoT contraptions, the IoT frameworks are slanted to various security strikes. The presence of successful security and assurance shows that IoT frameworks are incredibly expected to ensure protection, get the chance to control, and decency, among others. In this chapter, a complete assessment on security and insurance issues in IoT frameworks is provided.

Wireless communication networks are highly prone to security threats. The major applications of wireless communication networks are in military, business, healthcare, retail, and transportations. These systems use wired, cellular, or adhoc networks. Wireless sensor networks, actuator networks, and vehicular networks have received a great attention in society and industry. In recent years, the Internet of Things (IoT) has received considerable research attention. The IoT is considered as future of the internet. In future, IoT will play a vital role and will change our living styles, standards, as well as business models. The usage of IoT in different applications is expected to rise rapidly in the coming years. The IoT allows billions of devices, peoples, and services to connect with others and exchange information. Due to the increased usage of IoT devices, the IoT networks are prone to various security attacks. The deployment of efficient security and privacy protocols in IoT networks is extremely needed to ensure confidentiality, authentication, access control, and integrity, among others. In this paper, an extensive comprehensive study on security and privacy issues in IoT networks is provided.

A lightweight attribute-based encryption scheme for the Internet of Things

Elderly population in the Asian countries is increasing at a very fast rate. Lack of healthcare resources and infrastructure in many countries makes the task of provding proper healthcare difficult. Internet of things (IoT) in healthcare can address the problem effectively. Patient care is possible at home using IoT devices. IoT devices are used to collect different types of data. Various algorithms may be used to analyse data. IoT devices are connected to the internet and all the data of the patients with various health reports are available online and hence security issues arise. IoT sensors, IoT communication technologies, IoT gadgets, components of IoT, IoT layers, cloud and fog computing, benefits of IoT, IoT-based algorithms, IoT security issues, and IoT challenges are discussed in the chapter. Nowadays global epidemic COVID19 has demolished the economy and health services of all the countries worldwide. Usefulness of IoT in COVID19-related issues is explained here.

Recently, the internet of things (IoT) has evolved into a breakthrough for creating intelligent settings. Any technology's reliance on the IoT model is seen as having major security and privacy issues. The various conceivable attacks carried out by intruders give rise to privacy and security considerations. Therefore, creating an intrusion detection system is crucial for identifying attacks and anomalies in the IoT system. In this work, a deep belief network (DBN) algorithm model for the intrusion detection system has been proposed. The CICIDS 2017 dataset is used for the performance analysis of the current IDS model in terms of assaults and anomaly detection. Accuracy, recall, precision, F1-score, detection rate, and other characteristics were all improved by the proposed method. IoT technology has revolutionized how healthcare is provided to patients. Medical institutions are very concerned about IoT security because of the network enabled IoT devices' integration with healthcare network infrastructure.

Motivated by the recent explosion of interest around the Internet of Things (IoT), this paper is focused on the dynamics of its security. It is a fact that at present, there is a dearth of consolidated and methodical visions for assuring the security of IoT. This owes to its unique characteristics like interdependence of IoT devices and services, device heterogeneity, mobility, affinity to owners, pervasiveness, and unattended nature. The constraints of energy, memory, bandwidth and computability further complicate this picture. The strategies available in the literature today do not entirely consider this intricate nature of IoT environments. Moreover, uncertainty is not adequately acknowledged by the researchers while designing the security procedures for IoT, even though most of the IoT related security problems stem from an uncertain environment. This paper focuses on addressing this uncertainty, along with the other major security issues of IoT. It gives detailed categorization of the attacks in IoT. To this end, a Fuzzy Logic and Fog based Secure Architecture for IoT (FLFSIoT) has been proposed in this paper that works in real-time. In FLFSIoT, fuzzy logic has been used to alleviate the uncertainty of belonging to one crisp cluster of an edge node and for detecting various classical attacks. The Fog supported IoT architecture has been used to make FLFSIoT intrinsically more secure in comparison to the cloud-supported IoT by omitting the latency and other issues. As such, this work feeds the benefits of fuzzy log and fog computing into the carving of a generic solution to the IoT’s security problem. The efficiency of FLFSIoT has been evaluated against the Distributed Denial of Service (DDoS) and Collusion attacks, and it has been observed that it gives more accurate results than the existing benchmarks.

The Internet of Things (IoT), describing the Machine Type Communications (MTC), is in the center of many new technical studies and industrial projects. It is also a central topic for the future 5G technologies standardization. Pending the new generation of cellular networks, the 3rd Generation Partnership Project (3GPP) has already standardized in May 2016, an evolution of the 2G and 4G networks to include IoT features. EC-GSM-IoT, the standard for the 2G technologies including the MTC, uses several technical evolutions to obtain a 20 dB improvement of the legacy Maximum Coupling Loss (MCL) of GPRS. One of them is the use of blind repetitions, and of combination techniques in the receiver. In a previous work [1], the Bit Error Rate (BER) performance of several time diversity combining mechanisms in a classical GSM receiver were studied in simulation. The present paper focuses on two of these combination techniques and leads a novel analytical study of their performances under a time variant multipath Rayleigh fading channel. The impact of the time correlation of the channels on the average Signal to Noise and Interference Ratio (SINR) is enlightened. Simulation results are compared to the theoretical curves and confirm the analytical work. This analytical investigation allows us to foresee the consequences on the final BER of the system. To the best of our knowledge, this is the first analytical study of the performance of such time diversity combining mechanisms under time variant multipath Rayleigh fading channels.

PurposeAs the number of devices that connect to the Internet of Things (IoT) has grown, privacy and security issues have come up. Because IoT devices collect so much sensitive information, like user names, locations, phone numbers and even how they usually use energy, it is very important to protect users' privacy and security. IoT technology will be hard to use on the client side because IoT-enabled devices do not have clear privacy and security controls.Design/methodology/approachIoT technology would be harder to use on the client side if the IoT did not offer enough well-defined ways to protect users’ privacy and security. The goal of this research is to protect people's privacy in the IoT by using the oppositional artificial flora optimization (EGPKC-OAFA) algorithm to generate the best keys for the ElGamal public key cryptosystem (EGPKC). The EGPKC-OAFA approach puts the most weight on the IEEE 802.15.4 standard for MAC, which is the most important part of the standard. The security field is part of the MAC header of this standard. In addition, the MAC header includes EGPKC, which makes it possible to make authentication keys as quickly as possible.FindingsWith the proliferation of IoT devices, privacy and security have become major concerns in the academic world. Security and privacy are of the utmost importance due to the large amount of personally identifiable information acquired by IoT devices, such as name, location, phone numbers and energy use. Client-side deployment of IoT technologies will be hampered by the absence of well-defined privacy and security solutions afforded by the IoT. The purpose of this research is to present the EGPKC with optimum key generation using the EGPKC-OAFA algorithm for the purpose of protecting individual privacy within the context of the IoT. The EGPKC-OAFA approach is concerned with the MAC standard defined by the IEEE 802.15.4 standard, which includes the security field in its MAC header. Also, the MAC header incorporates EGPKC, which enables the fastest possible authentication key generation. In addition, the best methodology award goes to the OAFA strategy, which successfully implements the optimum EGPKC selection strategy by combining opposition-based (OBL) and standard AFA ideas. The EGPKC-OAFA method has been proved to effectively analyze performance in a number of simulations, with the results of various functions being identified.Originality/valueIn light of the growing prevalence of the IoT, an increasing number of people are becoming anxious about the protection and confidentiality of the personal data that they save online. This is especially true in light of the fact that more and more things are becoming connected to the internet. The IoT is capable of gathering personally identifiable information such as names, addresses and phone numbers, as well as the quantity of energy that is used. It will be challenging for customers to adopt IoT technology because of worries about the security and privacy of the data generated by users. In this work, the EGPKC is paired with adversarial artificial flora, which leads in an increase to the privacy security provided by EGPKC for the IoT (EGPKC-OAFA). The MAC security field that is part of the IEEE 802.15.4 standard is one of the areas that the EGPKC-OAFA protocol places a high focus on. The Authentication Key Generation Protocol Key Agreement, also known as EGPKCA, is used in MAC headers. The abbreviation for this protocol is EGPKCA. The OAFA technique, also known as the combination of OBL and AFA, is the most successful method for selecting EGPKCs. This method is recognized by its acronym, OAFA. It has been shown via a variety of simulations that the EGPKC-OAFA technique is a very useful instrument for carrying out performance analysis.

Internet of Things (IoT) have opened the door to a world of unlimited possibilities for implementations in varied sectors in society, but it also has many challenges. One of those challenges is security and privacy. IoT devices are more susceptible to security threats and attacks. Due to constraints of the IoT devices such as area, power, memory, etc., there is a lack of security solutions that are compatible with IoT devices and applications, which is leading this world of securely connected things to the “internet of insecure things.” A promising solution to this problem is going beyond the standard or classical techniques to implementing the security solutions in the hardware of the IoT device. The integration of emerging technologies in IoT networks, such as machine learning, blockchain, fog/edge/cloud computing, and quantum computing have added more vulnerable points in the network. This paper introduces a comprehensive study on IoT security threats and solutions. Additionally, this survey outlines how emerging technologies such as machine learning and blockchain are integrated in IoT, challenges resulted from this integration, and potential solutions to these challenges. The paper utilizes the 4-layer IoT architecture as a reference to identify security issues with corresponding solutions.

LoRa has been widely used in the Internet of Things (IoT) recently for its advantages of long distance and low power consumption. However, the security problem restricts its practical application scenarios. The existing Advanced Encryption Standard (AES) technology has high computational complexity and high energy consumption for LoRa terminals with limited hardware resources. Therefore, this letter proposes a novel physical layer encryption algorithm based on LoRa modulation characteristics, which is suitable for low-cost LoRa terminals. The algorithm combines the secret key extraction approach based on Received Signal Strength Indicator (RSSI) with the secret sharing scheme based on Chinese Remainder Theorem (CRT). Simulation results show that the proposed algorithm can protect the LoRa transmission bits from eavesdroppers. While, compared with the conventional LoRa without security, the proposed algorithm has no bit error rate (BER) performance loss with different SNR and will not cause more serious spectrum leakage under different synchronization offsets.

The Internet of Things (IoT) is a network of sensors that helps collect data 24/7 without human intervention. However, the network may suffer from problems such as the low battery, heterogeneity, and connectivity issues due to the lack of standards. Even though these problems can cause several performance hiccups, security issues need immediate attention because hackers access vital personal and financial information and then misuse it. These security issues can allow hackers to hijack IoT devices and then use them to establish a Botnet to launch a Distributed Denial of Service (DDoS) attack. Blockchain technology can provide security to IoT devices by providing secure authentication using public keys. Similarly, Smart Contracts (SCs) can improve the performance of the IoT–blockchain network through automation. However, surveyed work shows that the blockchain and SCs do not provide foolproof security; sometimes, attackers defeat these security mechanisms and initiate DDoS attacks. Thus, developers and security software engineers must be aware of different techniques to detect DDoS attacks. In this survey paper, we highlight different techniques to detect DDoS attacks. The novelty of our work is to classify the DDoS detection techniques according to blockchain technology. As a result, researchers can enhance their systems by using blockchain-based support for detecting threats. In addition, we provide general information about the studied systems and their workings. However, we cannot neglect the recent surveys. To that end, we compare the state-of-the-art DDoS surveys based on their data collection techniques and the discussed DDoS attacks on the IoT subsystems. The study of different IoT subsystems tells us that DDoS attacks also impact other computing systems, such as SCs, networking devices, and power grids. Hence, our work briefly describes DDoS attacks and their impacts on the above subsystems and IoT. For instance, due to DDoS attacks, the targeted computing systems suffer delays which cause tremendous financial and utility losses to the subscribers. Hence, we discuss the impacts of DDoS attacks in the context of associated systems. Finally, we discuss Machine-Learning algorithms, performance metrics, and the underlying technology of IoT systems so that the readers can grasp the detection techniques and the attack vectors. Moreover, associated systems such as Software-Defined Networking (SDN) and Field-Programmable Gate Arrays (FPGA) are a source of good security enhancement for IoT Networks. Thus, we include a detailed discussion of future development encompassing all major IoT subsystems.