Zero-Knowledge and Identity-Based Authentication, Authorization, Access Control, and Key Exchange for Publish/Subscribe in Internet of Things

The article examines methods and information technologies aimed at ensuring the secure integration of the Ethereum blockchain with Internet of Things (IoT) systems. The relevance of the study is driven by the rapid development of IoT, which is accompanied by increasing cybersecurity threats, including unauthorized data access, man-in-the-middle (MITM) attacks, device identifier spoofing, and the low transparency of centralized systems. The use of Ethereum blockchain technology, particularly smart contracts, opens new opportunities for creating decentralized security management models for IoT devices, enhancing trust levels, automating processes, and minimizing third-party interference risks. The “Problem statement” section outlines the key challenges in securing IoT networks, including the vulnerabilities of centralized solutions, limited computational resources of devices, and the need to develop autonomous access control systems. The “Analysis of Recent Research and Publications” section summarizes modern approaches to integrating Ethereum blockchain into the IoT field, including tokenized identification mechanisms, access control, and transaction processing using smart contracts. It is noted that leading researchers suggest Layer-2 solutions (state channels, zk-rollups, Plasma) aimed at reducing the load on the main blockchain and improving scalability. The aim of the article is to systematize modern methods of integrating the Ethereum blockchain with IoT and develop recommendations for their implementation, considering the limited resources of devices. The “Research results” section presents a secure IoT system architecture concept based on decentralized account management, local storage of cryptographic keys on devices, the use of optimized transaction signing algorithms, and the introduction of a hybrid data storage model based on IPFS. The proposed model minimizes the risk of unauthorized access, increases transparency in the interaction between IoT devices, and reduces computational resource costs. The “Conclusions and prospects for further research” section emphasizes that the implementation of the Ethereum blockchain in IoT promotes the development of secure decentralized platforms. However, it requires addressing issues such as energy consumption, transaction costs, and optimizing client applications for low-performance devices. Future research should focus on developing effective scalability tools, adapting smart contracts to IoT specifics, and improving integration with cloud computing platforms for storing large data sets.

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...

Zero conf protocols date from 1999. They provide plug and play mechanisms to set up networks without having to conFigure DNS or DHCP servers. Almost every device (PCs, printers, scanners, etc.) nowadays “speaks” one of these protocols, sometimes without its owner being even aware of it. The booming IoT ecosystem, in particular, relies heavily on them. Unfortunately, these protocols offer a number of different ways to run, so called, man in the middle attacks (MITM). Some previous publications have mentioned and have taken advantage of one or another of these design flaws. In this paper, we provide a deep dive into the various issues at hand and show the extent of the problem. We consider that the growing reliance of networks on these protocols represent an underestimated and ill covered threat. We have run a number of experiments (300) to test various implementations and discuss our results. We also propose means to detect these attacks thanks to Zeek (aka Bro). We make the attack code as well as the Zeek scripts available to the research community in a format that makes replication of our results possible by researchers while not easy to use by script kiddies.

Cyber security of distribution power systems is of an increasing and pressing importance due to the fast modernisation of current systems. Cyber attacks on distribution power systems may aim to operate the system inefficiently, steal private smart meter data or cause intentional false tripping of few or all feeders. In this paper, a Man in The Middle (MiTM) attack on a power factor correction unit is implemented and demonstrated to overload a distribution feeder and cause an intentional false tripping of the entire feeder causing regional blackout. Experimental implementation of the attack is carried out in a laboratory-scale setup using commercial power equipment under different loading conditions to demonstrate the effectiveness of this attack.

The integration of Internet of Things (IoT) into energy management systems has been changed energy grids and energy technologies; with technological advancement increase in cybersecurity concerns has been introduced significantly. Observation and manipulation of sensor data has become easier particularly through cyber-attacks such as man in the middle attack (MITM), Due to this cyber-attacks credibility of sensor data is been affected which can result into drastic disruption in energy grid and energy technologies operations. Through this paper challenges in IoT system used in energy management and energy monitoring will be observed. A testbed is set up using a PLC (Programmable Logic Controller) is established using Raspberry Pi as hardware and Open PLC Library as software to run ladder logic. A sensor DHT11 record temperature value of heating element which is controlled by PLC, using machine learning algorithms model has been trained in such a way that any abrupt change in reading or manipulation can be detected. To validate this ML model Ettercap tool has been used for manipulation of sensor reading. To increase the accuracy of model camera feed is also included to check the status of heating element. Overall model gives successful implementation of ML model and detection of manipulation in sensor reading when system is compromised in Modbus TCP/IP communication.

In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

PurposeThe purpose of this paper Computing is a recent emerging cloud model that affords clients limitless facilities, lowers the rate of customer storing and computation and progresses the ease of use, leading to a surge in the number of enterprises and individuals storing data in the cloud. Cloud services are used by various organizations (education, medical and commercial) to store their data. In the health-care industry, for example, patient medical data is outsourced to a cloud server. Instead of relying onmedical service providers, clients can access theirmedical data over the cloud.Design/methodology/approachThis section explains the proposed cloud-based health-care system for secure data storage and access control called hash-based ciphertext policy attribute-based encryption with signature (hCP-ABES). It provides access control with finer granularity, security, authentication and user confidentiality of medical data. It enhances ciphertext-policy attribute-based encryption (CP-ABE) with hashing, encryption and signature. The proposed architecture includes protection mechanisms to guarantee that health-care and medical information can be securely exchanged between health systems via the cloud. Figure 2 depicts the proposed work's architectural design.FindingsFor health-care-related applications, safe contact with common documents hosted on a cloud server is becoming increasingly important. However, there are numerous constraints to designing an effective and safe data access method, including cloud server performance, a high number of data users and various security requirements. This work adds hashing and signature to the classic CP-ABE technique. It protects the confidentiality of health-care data while also allowing for fine-grained access control. According to an analysis of security needs, this work fulfills the privacy and integrity of health information using federated learning.Originality/valueThe Internet of Things (IoT) technology and smart diagnostic implants have enhanced health-care systems by allowing for remote access and screening of patients’ health issues at any time and from any location. Medical IoT devices monitor patients’ health status and combine this information into medical records, which are then transferred to the cloud and viewed by health providers for decision-making. However, when it comes to information transfer, the security and secrecy of electronic health records become a major concern. This work offers effective data storage and access control for a smart healthcare system to protect confidentiality. CP-ABE ensures data confidentiality and also allows control on data access at a finer level. Furthermore, it allows owners to set up a dynamic patients health data sharing policy under the cloud layer. hCP-ABES proposed fine-grained data access, security, authentication and user privacy of medical data. This paper enhances CP-ABE with hashing, encryption and signature. The proposed method has been evaluated, and the results signify that the proposed hCP-ABES is feasible compared to other access control schemes using federated learning.

Federated Learning (FL) enables cooperative model training across dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. In the Internet of Things (IoT), federated learning enables cooperative model training among dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. Nevertheless, Federated Learning’s local model sharing approach makes it susceptible to Man-in-the-Middle (MITM) attacks. In FL, attackers have the ability to manipulate local models. As a result, a global model produced from the altered local models may be inaccurate. In this paper, we suggest a blockchain-based FL architecture to prevent intermediaries from readily altering the FL parameters throughout the transmission process. All of the clients' parameters are combined by a cloud server, which is acting as the federated parameter server. By integrating blockchain technology into the overall architecture, we link all cloud and edge servers. This paper uses a PoC algorithm based on the SHA-256 hashing function in order to validate the data. The results and comparison analysis show that the suggested framework has a low false-positive rate and a high accuracy in detecting MITM attacks in their early stages, with a detection rate ranging from 98 to 100%.

With rapid advancements in the technology, almost all the devices around are becoming smart and contribute to the Internet of Things (IoT) network. When a new IoT device is added to the network, it is important to verify the authenticity of the device before allowing it to communicate with the network. Hence, access control is a crucial security mechanism that allows only the authenticated node to become the part of the network. An access control mechanism also supports confidentiality, by establishing a session key that accomplishes secure communications in open public channels. Recently, blockchain has been implemented in access control protocols to provide a better security mechanism. The foundation of this survey article is laid on IoT, where a detailed description on IoT, its architecture and applications is provided. Further, various security challenges and issues, security attacks possible in IoT and their countermeasures are also provided. We emphasize on the blockchain technology and its evolution in IoT. A detailed description on existing consensus mechanisms and how blockchain can be used to overpower IoT vulnerabilities is highlighted. Moreover, we provide a comprehensive description on access control protocols. The protocols are classified into certificate-based, certificate-less and blockchain-based access control mechanisms for better understanding. We then elaborate on each use case like smart home, smart grid, health care and smart agriculture while describing access control mechanisms. The detailed description not only explains the implementation of the access mechanism, but also gives a wider vision on IoT applications. Next, a rigorous comparative analysis is performed to showcase the efficiency of all protocols in terms of computation and communication costs. Finally, we discuss open research issues and challenges in a blockchain-envisioned IoT network.

Internet of Medical Things (IoMT) has revolutionized the modern healthcare by integrating medical devices and real-time patient monitoring into it. However, the limited resource environment in IoMT devices makes the deployment of strong security mechanisms a great challenge. In this paper, lightweight cryptography-based security mechanisms particularly for node authentication and access control in IoMT systems are analyzed. The particular security needs of IoMT systems are considered, and reviewed the new developments in lightweight cryptography for defending against specific cyber-attacks including impersonation, replay and unauthorized access. A comparison of current authentication protocols and access control technologies which evaluates computational cost, scalability, and attack tolerance is presented. The recent trends and future research directions on improving the resilience of IoMT networks with minimal overhead is also discussed. With the proliferation of IoMT usage, it is more important than ever for patient data to remain confidential and for the medical systems to function correctly. This paper focuses on the security versus device trade-offs, and presents cryptography tools that achieve a good trade-off between the strength obtained and the power, memory, and processing limitations. By examining the present situation and open challenges, this research work is an attempt to pave the way for designing next-generation lightweight cryptography for secure and efficient IoMT systems. This research is helpful for numerous scholars and medical experts to analyse the advantages and limitations of traditional authentication and access control models in IoMT and to design innovative solutions.

Internet of Things (IoT) has become an information bridge between societies. Wireless sensor networks (WSNs) are one of the emergent technologies that work as the main force in IoT. Applications based on WSN include environment monitoring, smart healthcare, user legitimacy authentication, and data security. Recently, many multifactor user authentication schemes for WSNs have been proposed using smart cards, passwords, as well as biometric features. Unfortunately, these schemes are shown to be susceptible towards several attacks and these includes password guessing attack, impersonation attack, and Man-in-the-middle (MITM) attack due to non-uniform security evaluation criteria. In this paper, we propose a lightweight multifactor authentication scheme using only hash function of the timestamp (TS) and One Time Password (OTP). Furthermore, public key and private key is incorporated to secure the communication channel. The security analysis shows that the proposed scheme satisfies all the security requirement and insusceptible towards some well-known attack (password guessing attack, impersonation attack and MITM).

The Internet of things (IoT) is an active, real-world area in need of more investigation. One of the top weaknesses in security challenges that IoTs face, the centralized access control server, which can be a single point of failure. In this paper, Dynamic-IoTrust, a decentralized access control smart contract based aims to overcome distrusted, dynamic, trust and authentication issues for access control in IoT. It also integrates dynamic trust value to evaluate users based on behavior. In particular, the Dynamic-IoTrust contains multiple Main Smart Contract, one Register Contract, and one Judging Contract to achieve efficient distributed access control management. Dynamic-IoTrust provides both static access rights by allowing predefined access control policies and also provides dynamic access rights by checking the trust value and the behavior of the user. The system also provides to detected user misbehavior and make a decision for user trust value and penalty. There are several levels of trusted users to access the IoTs device. Finally, the case study demonstrates the feasibility of the Dynamic-IoTrust model to offer a dynamic decentralized access control system with trust value attribute to evaluate the internal user used IoTs devices.

The open stack communication protocol of the internet of things always in security threats. The vulnerability of protocol faces a problem of man in middle attacks and loss of integrity of communication. Cryptography plays a vital role in security authentication on IoT based enable communication system. IoT devices' limited resource constraints cannot offer any security mechanism on the physical level and network level. The key generation methods uplift the security provision in IoT enables communication model. The process of key generation applied three types of cryptography algorithm, symmetric, asymmetric and hybrid algorithm. The complexity of key generation methods needs more computational time and memory; this is the limitation of IoT devices. So various authors proposed a lightweight key generation algorithm for security and authentication. This paper analyzed the performance of key generation methods based on different cryptography approaches and measured their security strength. For the analysis process, use MATLAB software and sample text data file for the communication of two parties. Some ADHOC methods apply to measure protocol weakness during the communication network compromised with a man in the middle attack. The variable key size also reflects the security strength of IoTs enable devices.

Advances on networked ehealth information access and sharing: Status, challenges and prospects