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2021-05-13
Yu, Chen, Chen, Liquan, Lu, Tianyu.  2020.  A Direct Anonymous Attestation Scheme Based on Mimic Defense Mechanism. 2020 International Conference on Internet of Things and Intelligent Applications (ITIA). :1—5.
Machine-to-Machine (M2M) communication is a essential subset of the Internet of Things (IoT). Secure access to communication network systems by M2M devices requires the support of a secure and efficient anonymous authentication protocol. The Direct Anonymous Attestation (DAA) scheme in Trustworthy Computing is a verified security protocol. However, the existing defense system uses a static architecture. The “mimic defense” strategy is characterized by active defense, which is not effective against continuous detection and attack by the attacker. Therefore, in this paper, we propose a Mimic-DAA scheme that incorporates mimic defense to establish an active defense scheme. Multiple heterogeneous and redundant actuators are used to form a DAA verifier and optimization is scheduled so that the behavior of the DAA verifier unpredictable by analysis. The Mimic-DAA proposed in this paper is capable of forming a security mechanism for active defense. The Mimic-DAA scheme effectively safeguard the unpredictability, anonymity, security and system-wide security of M2M communication networks. In comparison with existing DAA schemes, the scheme proposed in this paper improves the safety while maintaining the computational complexity.
Whaiduzzaman, Md, Oliullah, Khondokar, Mahi, Md. Julkar Nayeen, Barros, Alistair.  2020.  AUASF: An Anonymous Users Authentication Scheme for Fog-IoT Environment. 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT). :1—7.
Authentication is a challenging and emerging issue for Fog-IoT security paradigms. The fog nodes toward large-scale end-users offer various interacted IoT services. The authentication process usually involves expressing users' personal information such as username, email, and password to the Authentication Server (AS). However, users are not intended to express their identities or information over the fog or cloud servers. Hence, we have proposed an Anonymous User Authentication Scheme for Fog-IoT (AUASF) to keep the anonymity existence of the IoT users and detect the intruders. To provide anonymity, the user can send encrypted credentials such as username, email, and mobile number through the Cloud Service Provider (CSP) for registration. IoT user receives the response with a default password and a secret Id from the CSP. After that, the IoT user submits the default password for first-time access to Fog Service Provider (FSP). The FSP assigns a One Time Password (OTP) to each user for further access. The developed scheme is equipped with hash functions, symmetric encryptions, and decryptions for security perceptions across fog that serves better than the existing anonymity schemes.
Zhao, Haining, Chen, Liquan.  2020.  Artificial Intelligence Security Issues and Responses. 2020 IEEE 6th International Conference on Computer and Communications (ICCC). :2276—2283.
As a current disruptive and transformative technology, artificial intelligence is constantly infiltrating all aspects of production and life. However, with the in-depth development and application of artificial intelligence, the security challenges it faces have become more and more prominent. In the real world, attacks against intelligent systems such as the Internet of Things, smart homes, and driverless cars are constantly appearing, and incidents of artificial intelligence being used in cyber-attacks and cybercrimes frequently occur. This article aims to discuss artificial intelligence security issues and propose some countermeasures.
Lit, Yanyan, Kim, Sara, Sy, Eric.  2021.  A Survey on Amazon Alexa Attack Surfaces. 2021 IEEE 18th Annual Consumer Communications Networking Conference (CCNC). :1–7.
Since being launched in 2014, Alexa, Amazon's versatile cloud-based voice service, is now active in over 100 million households worldwide [1]. Alexa's user-friendly, personalized vocal experience offers customers a more natural way of interacting with cutting-edge technology by allowing the ability to directly dictate commands to the assistant. Now in the present year, the Alexa service is more accessible than ever, available on hundreds of millions of devices from not only Amazon but third-party device manufacturers. Unfortunately, that success has also been the source of concern and controversy. The success of Alexa is based on its effortless usability, but in turn, that has led to a lack of sufficient security. This paper surveys various attacks against Amazon Alexa ecosystem including attacks against the frontend voice capturing and the cloud backend voice command recognition and processing. Overall, we have identified six attack surfaces covering the lifecycle of Alexa voice interaction that spans several stages including voice data collection, transmission, processing and storage. We also discuss the potential mitigation solutions for each attack surface to better improve Alexa or other voice assistants in terms of security and privacy.
2021-05-05
Osaretin, Charles Aimiuwu, Zamanlou, Mohammad, Iqbal, M. Tariq, Butt, Stephen.  2020.  Open Source IoT-Based SCADA System for Remote Oil Facilities Using Node-RED and Arduino Microcontrollers. 2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). :0571—0575.
An open source and low-cost Supervisory Control and Data Acquisition System based on Node-RED and Arduino microcontrollers is presented in this paper. The system is designed for monitoring, supervision, and remotely controlling motors and sensors deployed for oil and gas facilities. The Internet of Things (IoT) based SCADA system consists of a host computer on which a server is deployed using the Node-RED programming tool and two terminal units connected to it: Arduino Uno and Arduino Mega. The Arduino Uno collects and communicates the data acquired from the temperature, flowrate, and water level sensors to the Node-Red on the computer through the serial port. It also uses a local liquid crystal display (LCD) to display the temperature. Node-RED on the computer retrieves the data from the voltage, current, rotary, accelerometer, and distance sensors through the Arduino Mega. Also, a web-based graphical user interface (GUI) is created using Node-RED and hosted on the local server for parsing the collected data. Finally, an HTTP basic access authentication is implemented using Nginx to control the clients' access from the Internet to the local server and to enhance its security and reliability.
Bazari, Aditya Shyam, Singh, Aditya, Khan, Abdul Ahad, Jindal, Rajni.  2020.  Filter Based Scalable Blockchain for Domestic Internet of Things. 2020 5th International Conference on Communication and Electronics Systems (ICCES). :1051—1056.

With the advancements in technology, the ease of interconnectedness among devices has increased manifold, leading to the widespread usage of Internet of Things. Internet of Things has also reached our homes, often referred to as domestic Internet of Things. However, the security aspect of domestic Internet of Things has largely been under question as the increase in inter-device communication renders the system more vulnerable to adversaries. Largely popular blockchain technology is being extensively researched for integration into the Internet of Things framework in order to improve the security aspect of the framework. Blockchain, being a cryptographically linked set of data, has a few barriers which prevent it from being successfully integrated to Internet of Things. One of the major barrier is the high computational requirements and time latency associated with it. This work tries to address this research gap and proposes a novel scalable blockchain optimization for domestic Internet of Things. The proposed blockchain model uses a flow based filtering technique as an added security layer to facilitate the scenario. This work then evaluates the performance of the proposed model in various scenarios and compares it with that of traditional blockchain. The work presents a largely encompassing evaluation, explanation and assessment of the proposed model.

2021-05-03
Takita, Yutaka, Miyabe, Masatake, Tomonaga, Hiroshi, Oguchi, Naoki.  2020.  Scalable Impact Range Detection against Newly Added Rules for Smart Network Verification. 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC). :1471–1476.
Technological progress in cloud networking, 5G networks, and the IoT (Internet of Things) are remarkable. In addition, demands for flexible construction of SoEs (Systems on Engagement) for various type of businesses are increasing. In such environments, dynamic changes of network rules, such as access control (AC) or packet forwarding, are required to ensure function and security in networks. On the other hand, it is becoming increasingly difficult to grasp the exact situation in such networks by utilizing current well-known network verification technologies since a huge number of network rules are complexly intertwined. To mitigate these issues, we have proposed a scalable network verification approach utilizing the concept of "Packet Equivalence Class (PEC)," which enable precise network function verification by strictly recognizing the impact range of each network rule. However, this approach is still not scalable for very large-scale networks which consist of tens of thousands of routers. In this paper, we enhanced our impact range detection algorithm for practical large-scale networks. Through evaluation in the network with more than 80,000 AC rules, we confirmed that our enhanced algorithm can achieve precise impact range detection in under 600 seconds.
Gelenbe, Erol.  2020.  Machine Learning for Network Routing. 2020 9th Mediterranean Conference on Embedded Computing (MECO). :1–1.
Though currently a “hot topic”, over the past fifteen years [1][2], there has been significant work on the use of machine learning to design large scale computer-communication networks, motivated by the complexity of the systems that are being considered and the unpredictability of their workloads. A topic of great concern has been security [3] and novel techniques for detecting network attacks have been developed based on Machine Learning [8]. However the main challenge with Machine Learning methods in networks has concerned their compatibility with the Internet Protocol and with legacy systems, and a major step forward has come from the establishment of Software Defined Networks (SDN) [4] which delegate network routing to specific SDN routers [4]. SDN has become an industry standard for concentrating network management and routing decisions within specific SDN routers that download the selected paths periodically to network routers, which operate otherwise under the IP protocol. In this paper we describe our work on real-time control of Security and Privacy [7], Energy Consumption and QoS [6] of packet networks using Machine Learning based on the Cognitive Packet Network [9] principles and their application to the H2020 SerIoT Project [5].
Luo, Lan, Zhang, Yue, Zou, Cliff, Shao, Xinhui, Ling, Zhen, Fu, Xinwen.  2020.  On Runtime Software Security of TrustZone-M Based IoT Devices. GLOBECOM 2020 - 2020 IEEE Global Communications Conference. :1–7.
Internet of Things (IoT) devices have been increasingly integrated into our daily life. However, such smart devices suffer a broad attack surface. Particularly, attacks targeting the device software at runtime are challenging to defend against if IoT devices use resource-constrained microcontrollers (MCUs). TrustZone-M, a TrustZone extension for MCUs, is an emerging security technique fortifying MCU based IoT devices. This paper presents the first security analysis of potential software security issues in TrustZone-M enabled MCUs. We explore the stack-based buffer overflow (BOF) attack for code injection, return-oriented programming (ROP) attack, heap-based BOF attack, format string attack, and attacks against Non-secure Callable (NSC) functions in the context of TrustZone-M. We validate these attacks using the Microchip SAM L11 MCU, which uses the ARM Cortex-M23 processor with the TrustZone-M technology. Strategies to mitigate these software attacks are also discussed.
2021-04-28
Westphall, J., Loffi, L., Westphall, C. M., Martina, J. Everson.  2020.  CoAP + DTLS: A Comprehensive Overview of Cryptographic Performance on an IOT Scenario. 2020 IEEE Sensors Applications Symposium (SAS). :1—6.
Internet of things (IoT) and Fog computing applications deal with sensitive data and need security tools to be protected against attackers. CoAP (Constrained Application Protocol), combined with DTLS (Datagram Transport Layer Security), provides security to IoT/Fog applications. However, processing times need to be considered when using this combination due to IoT/Fog environment constraints. Our work presents a CoAP with DTLS application and analyzes the performance of Raspberry Pi 3 during DTLS handshakes, data encryption and data decryption with the most relevant cipher suites. The performance of confirmable and non-confirmable CoAP POST requests is also measured and discussed in our work. We discovered that cipher suites that use RSA as an authentication method on handshake are slightly faster than cipher suites that use ECDSA, while symmetric key encryption with AES256(128)GCM are 40% faster than AES256(128) default modes. Our study also suggests CoAP modifications to obtain higher efficiency, and it might help future IoT/Fog application developers to understand CoAP and DTLS union, providing an application example and performance metrics.
Shere, A. R. K., Nurse, J. R. C., Flechais, I..  2020.  "Security should be there by default": Investigating how journalists perceive and respond to risks from the Internet of Things. 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :240—249.
Journalists have long been the targets of both physical and cyber-attacks from well-resourced adversaries. Internet of Things (IoT) devices are arguably a new avenue of threat towards journalists through both targeted and generalised cyber-physical exploitation. This study comprises three parts: First, we interviewed 11 journalists and surveyed 5 further journalists, to determine the extent to which journalists perceive threats through the IoT, particularly via consumer IoT devices. Second, we surveyed 34 cyber security experts to establish if and how lay-people can combat IoT threats. Third, we compared these findings to assess journalists' knowledge of threats, and whether their protective mechanisms would be effective against experts' depictions and predictions of IoT threats. Our results indicate that journalists generally are unaware of IoT-related risks and are not adequately protecting themselves; this considers cases where they possess IoT devices, or where they enter IoT-enabled environments (e.g., at work or home). Expert recommendations spanned both immediate and longterm mitigation methods, including practical actions that are technical and socio-political in nature. However, all proposed individual mitigation methods are likely to be short-term solutions, with 26 of 34 (76.5%) of cyber security experts responding that within the next five years it will not be possible for the public to opt-out of interaction with the IoT.
2021-04-27
Beckwith, E., Thamilarasu, G..  2020.  BA-TLS: Blockchain Authentication for Transport Layer Security in Internet of Things. 2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS). :1—8.

Traditional security solutions that rely on public key infrastructure present scalability and transparency challenges when deployed in Internet of Things (IoT). In this paper, we develop a blockchain based authentication mechanism for IoT that can be integrated into the traditional transport layer security protocols such as Transport Layer Security (TLS) and Datagram Transport Layer Security (DTLS). Our proposed mechanism is an alternative to the traditional Certificate Authority (CA)-based Public Key Infrastructure (PKI) that relies on x.509 certificates. Specifically, the proposed solution enables the modified TLS/DTLS a viable option for resource constrained IoT devices where minimizing memory utilization is critical. Experiments show that blockchain based authentication can reduce dynamic memory usage by up to 20%, while only minimally increasing application image size and time of execution of the TLS/DTLS handshake.

Vishwakarma, L., Das, D..  2020.  BSS: Blockchain Enabled Security System for Internet of Things Applications. 2020 IEEE 19th International Symposium on Network Computing and Applications (NCA). :1—4.

In the Internet of Things (IoT), devices can interconnect and communicate autonomously, which requires devices to authenticate each other to exchange meaningful information. Otherwise, these things become vulnerable to various attacks. The conventional security protocols are not suitable for IoT applications due to the high computation and storage demand. Therefore, we proposed a blockchain-enabled secure storage and communication scheme for IoT applications, called BSS. The scheme ensures identification, authentication, and data integrity. Our scheme uses the security advantages of blockchain and helps to create safe zones (trust batch) where authenticated objects interconnect securely and do communication. A secure and robust trust mechanism is employed to build these batches, where each device has to authenticate itself before joining the trust batch. The obtained results satisfy the IoT security requirements with 60% reduced computation, storage and communication cost compared with state-of-the-art schemes. BSS also withstands various cyberattacks such as impersonation, message replay, man-in-the-middle, and botnet attacks.

Yang, H., Bai, Y., Zou, Z., Zhang, Q., Wang, B., Yang, R..  2020.  Research on Data Security Sharing Mechanism of Power Internet of Things Based on Blockchain. 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC). 9:2029—2032.

The rapid growth of power Internet of Things devices has led to traditional data security sharing mechanisms that are no longer suitable for attribute and permission management of massive devices. In response to this problem, this article proposes a blockchain-based data security sharing mechanism for the power Internet of Things, which reduces the risk of data leakage through decentralization in the architecture and promotes the integration of multiple information and methods.

2021-04-09
Soni, G., Sudhakar, R..  2020.  A L-IDS against Dropping Attack to Secure and Improve RPL Performance in WSN Aided IoT. 2020 7th International Conference on Signal Processing and Integrated Networks (SPIN). :377—383.

In the Internet of Things (IoT), it is feasible to interconnect networks of different devices and all these different devices, such as smartphones, sensor devices, and vehicles, are controlled according to a particular user. These different devices are delivered and accept the information on the network. This thing is to motivate us to do work on IoT and the devices used are sensor nodes. The validation of data delivery completely depends on the checks of count data forwarding in each node. In this research, we propose the Link Hop Value-based Intrusion Detection System (L-IDS) against the blackhole attack in the IoT with the assist of WSN. The sensor nodes are connected to other nodes through the wireless link and exchange data routing, as well as data packets. The LHV value is identified as the attacker's presence by integrating the data delivery in each hop. The LHV is always equivalent to the Actual Value (AV). The RPL routing protocol is used IPv6 to address the concept of routing. The Routing procedure is interrupted by an attacker by creating routing loops. The performance of the proposed L-IDS is compared to the RPL routing security scheme based on existing trust. The proposed L-IDS procedure is validating the presence of the attacker at every source to destination data delivery. and also disables the presence of the attacker in the network. Network performance provides better results in the existence of a security scheme and also fully represents the inoperative presence of black hole attackers in the network. Performance metrics show better results in the presence of expected IDS and improve network reliability.

2021-04-08
Ameer, S., Benson, J., Sandhu, R..  2020.  The EGRBAC Model for Smart Home IoT. 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI). :457–462.
The Internet of Things (IoT) is enabling smart houses, where multiple users with complex social relationships interact with smart devices. This requires sophisticated access control specification and enforcement models, that are currently lacking. In this paper, we introduce the extended generalized role based access control (EGRBAC) model for smart home IoT. We provide a formal definition for EGRBAC and illustrate its features with a use case. A proof-of-concept demonstration utilizing AWS-IoT Greengrass is discussed in the appendix. EGRBAC is a first step in developing a comprehensive family of access control models for smart home IoT.
2021-03-30
Khan, W. Z., Arshad, Q.-u-A., Hakak, S., Khan, M. K., Saeed-Ur-Rehman.  2020.  Trust Management in Social Internet of Things: Architectures, Recent Advancements and Future Challenges. IEEE Internet of Things Journal. :1—1.

Social Internet of Things (SIoT) is an extension of Internet of Things (IoT) that converges with Social networking concepts to create Social networks of interconnected smart objects. This convergence allows the enrichment of the two paradigms, resulting into new ecosystems. While IoT follows two interaction paradigms, human-to-human (H2H) and thing-to-thing (T2T), SIoT adds on human-to-thing (H2T) interactions. SIoT enables smart “Social objects” that intelligently mimic the social behavior of human in the daily life. These social objects are equipped with social functionalities capable of discovering other social objects in the surroundings and establishing social relationships. They crawl through the social network of objects for the sake of searching for services and information of interest. The notion of trust and trustworthiness in social communities formed in SIoT is still new and in an early stage of investigation. In this paper, our contributions are threefold. First, we present the fundamentals of SIoT and trust concepts in SIoT, clarifying the similarities and differences between IoT and SIoT. Second, we categorize the trust management solutions proposed so far in the literature for SIoT over the last six years and provide a comprehensive review. We then perform a comparison of the state of the art trust management schemes devised for SIoT by performing comparative analysis in terms of trust management process. Third, we identify and discuss the challenges and requirements in the emerging new wave of SIoT, and also highlight the challenges in developing trust and evaluating trustworthiness among the interacting social objects.

2021-03-29
Luecking, M., Fries, C., Lamberti, R., Stork, W..  2020.  Decentralized Identity and Trust Management Framework for Internet of Things. 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC). :1—9.

Today, Internet of Things (IoT) devices mostly operate in enclosed, proprietary environments. To unfold the full potential of IoT applications, a unifying and permissionless environment is crucial. All IoT devices, even unknown to each other, would be able to trade services and assets across various domains. In order to realize those applications, uniquely resolvable identities are essential. However, quantifiable trust in identities and their authentication are not trivially provided in such an environment due to the absence of a trusted authority. This research presents a new identity and trust framework for IoT devices, based on Distributed Ledger Technology (DLT). IoT devices assign identities to themselves, which are managed publicly and decentralized on the DLT's network as Self Sovereign Identities (SSI). In addition to the Identity Management System (IdMS), the framework provides a Web of Trust (WoT) approach to enable automatic trust rating of arbitrary identities. For the framework we used the IOTA Tangle to access and store data, achieving high scalability and low computational overhead. To demonstrate the feasibility of our framework, we provide a proof-of-concept implementation and evaluate the set objectives for real world applicability as well as the vulnerability against common threats in IdMSs and WoTs.

Moreno, R. T., Rodríguez, J. G., López, C. T., Bernabe, J. B., Skarmeta, A..  2020.  OLYMPUS: A distributed privacy-preserving identity management system. 2020 Global Internet of Things Summit (GIoTS). :1—6.

Despite the latest initiatives and research efforts to increase user privacy in digital scenarios, identity-related cybercrimes such as identity theft, wrong identity or user transactions surveillance are growing. In particular, blanket surveillance that might be potentially accomplished by Identity Providers (IdPs) contradicts the data minimization principle laid out in GDPR. Hence, user movements across Service Providers (SPs) might be tracked by malicious IdPs that become a central dominant entity, as well as a single point of failure in terms of privacy and security, putting users at risk when compromised. To cope with this issue, the OLYMPUS H2020 EU project is devising a truly privacy-preserving, yet user-friendly, and distributed identity management system that addresses the data minimization challenge in both online and offline scenarios. Thus, OLYMPUS divides the role of the IdP among various authorities by relying on threshold cryptography, thereby preventing user impersonation and surveillance from malicious or nosy IdPs. This paper overviews the OLYMPUS framework, including requirements considered, the proposed architecture, a series of use cases as well as the privacy analysis from the legal point of view.

Amin, A. H. M., Abdelmajid, N., Kiwanuka, F. N..  2020.  Identity-of-Things Model using Composite Identity on Permissioned Blockchain Network. 2020 Seventh International Conference on Software Defined Systems (SDS). :171—176.

The growing prevalence of Internet-of-Things (IoT) technology has led to an increase in the development of heterogeneous smart applications. Smart applications may involve a collaborative participation between IoT devices. Participation of IoT devices for specific application requires a tamper-proof identity to be generated and stored, in order to completely represent the device, as well as to eliminate the possibility of identity spoofing and presence of rogue devices in a network. In this paper, we present a composite Identity-of-Things (IDoT) approach on IoT devices with permissioned blockchain implementation for distributed identity management model. Our proposed approach considers both application and device domains in generating the composite identity. In addition, the use of permissioned blockchain for identity storage and verification allows the identity to be immutable. A simulation has been carried out to demonstrate the application of the proposed identity management model.

Grundy, J..  2020.  Human-centric Software Engineering for Next Generation Cloud- and Edge-based Smart Living Applications. 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID). :1—10.

Humans are a key part of software development, including customers, designers, coders, testers and end users. In this keynote talk I explain why incorporating human-centric issues into software engineering for next-generation applications is critical. I use several examples from our recent and current work on handling human-centric issues when engineering various `smart living' cloud- and edge-based software systems. This includes using human-centric, domain-specific visual models for non-technical experts to specify and generate data analysis applications; personality impact on aspects of software activities; incorporating end user emotions into software requirements engineering for smart homes; incorporating human usage patterns into emerging edge computing applications; visualising smart city-related data; reporting diverse software usability defects; and human-centric security and privacy requirements for smart living systems. I assess the usefulness of these approaches, highlight some outstanding research challenges, and briefly discuss our current work on new human-centric approaches to software engineering for smart living applications.

Bogdan-Iulian, C., Vasilică-Gabriel, S., Alexandru, M. D., Nicolae, G., Andrei, V..  2020.  Improved Secure Internet of Things System using Web Services and Low Power Single-board Computers. 2020 International Conference on e-Health and Bioengineering (EHB). :1—5.

Internet of Things (IoT) systems are becoming widely used, which makes them to be a high-value target for both hackers and crackers. From gaining access to sensitive information to using them as bots for complex attacks, the variety of advantages after exploiting different security vulnerabilities makes the security of IoT devices to be one of the most challenging desideratum for cyber security experts. In this paper, we will propose a new IoT system, designed to ensure five data principles: confidentiality, integrity, availability, authentication and authorization. The innovative aspects are both the usage of a web-based communication and a custom dynamic data request structure.

Juyal, S., Sharma, S., Harbola, A., Shukla, A. S..  2020.  Privacy and Security of IoT based Skin Monitoring System using Blockchain Approach. 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). :1—5.

Remote patient monitoring is a system that focuses on patients care and attention with the advent of the Internet of Things (IoT). The technology makes it easier to track distance, but also to diagnose and provide critical attention and service on demand so that billions of people are safer and more safe. Skincare monitoring is one of the growing fields of medical care which requires IoT monitoring, because there is an increasing number of patients, but cures are restricted to the number of available dermatologists. The IoT-based skin monitoring system produces and store volumes of private medical data at the cloud from which the skin experts can access it at remote locations. Such large-scale data are highly vulnerable and otherwise have catastrophic results for privacy and security mechanisms. Medical organizations currently do not concentrate much on maintaining safety and privacy, which are of major importance in the field. This paper provides an IoT based skin surveillance system based on a blockchain data protection and safety mechanism. A secure data transmission mechanism for IoT devices used in a distributed architecture is proposed. Privacy is assured through a unique key to identify each user when he registers. The principle of blockchain also addresses security issues through the generation of hash functions on every transaction variable. We use blockchain consortiums that meet our criteria in a decentralized environment for controlled access. The solutions proposed allow IoT based skin surveillance systems to privately and securely store and share medical data over the network without disturbance.

Dorri, A., Jurdak, R..  2020.  Tree-Chain: A Fast Lightweight Consensus Algorithm for IoT Applications. 2020 IEEE 45th Conference on Local Computer Networks (LCN). :369–372.
Blockchain has received tremendous attention in non-monetary applications including the Internet of Things (IoT) due to its salient features including decentralization, security, auditability, and anonymity. Most conventional blockchains rely on computationally expensive validator selection and consensus algorithms, have limited throughput, and high transaction delays. In this paper, we propose tree-chain a scalable fast blockchain instantiation that introduces two levels of randomization among the validators: i) transaction level where the validator of each transaction is selected randomly based on the most significant characters of the hash function output (known as consensus code), and ii) blockchain level where validator is randomly allocated to a particular consensus code based on the hash of their public key. Tree-chain introduces parallel chain branches where each validator commits the corresponding transactions in a unique ledger.
Liu, W., Niu, H., Luo, W., Deng, W., Wu, H., Dai, S., Qiao, Z., Feng, W..  2020.  Research on Technology of Embedded System Security Protection Component. 2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications( AEECA). :21—27.

With the development of the Internet of Things (IoT), it has been widely deployed. As many embedded devices are connected to the network and massive amounts of security-sensitive data are stored in these devices, embedded devices in IoT have become the target of attackers. The trusted computing is a key technology to guarantee the security and trustworthiness of devices' execution environment. This paper focuses on security problems on IoT devices, and proposes a security architecture for IoT devices based on the trusted computing technology. This paper implements a security management system for IoT devices, which can perform integrity measurement, real-time monitoring and security management for embedded applications, providing a safe and reliable execution environment and whitelist-based security protection for IoT devices. This paper also designs and implements an embedded security protection system based on trusted computing technology, containing a measurement and control component in the kernel and a remote graphical management interface for administrators. The kernel layer enforces the integrity measurement and control of the embedded application on the device. The graphical management interface communicates with the remote embedded device through the TCP/IP protocol, and provides a feature-rich and user-friendly interaction interface. It implements functions such as knowledge base scanning, whitelist management, log management, security policy management, and cryptographic algorithm performance testing.