Yu Han, Xiaolei Wang, Yi Zhang, Gang Yang · 5 authors
In the context of the development of UAVs towards clustering, intelligence, and autonomy, it is necessary to ensure that multiple UAVs and ground control stations can communicate and share information securely in real-time so that UAV swarms can make real-time and effective decisions and collaborations. These factors pose challenges to the security, robustness, and operational efficiency of UAV swarm communication networks. This paper combines blockchain technology with a UAV swarm communication network, proposes a new UAV swarm communication network architecture based on consortium blockchain, and describes the network structure and transaction process in detail. The performance analysis shows that the security mechanism of the architecture can meet the security requirements of the UAV swarm communication network. And this solution is superior to existing solutions based on blockchain technology such as Ethereum in performance and is a technical solution with both security and usability.
Internet of Things (IoT) has massively adopted the market due to the current era demanding fully intelligent and autonomous services. The IoT industry is flourishing in terms of Internet of healthcare things, Internet of vehicles and autonomous driving, unmanned aerial vehicles, satellite and industrial Internet of things smart homes, etc. IoT can be enabled by employing connected devices such as sensors, continuously communicating, storing, and disseminating data. Data dissemination through energy-constrained low-power IoT sensors suffers from issues such as security and privacy of data. Traditional solutions using single-layer or multi-layer cryptographic algorithms do not suffice the need for security and privacy. Thus, we have proposed a blockchain-based secure onion routing protocol for a trusted and anonymous data dissemination framework for sensor communication in IoT environment. We have employed machine learning (ML) algorithms to classify adversarial and non-adversarial data fed to the onion router to reduce computational time. Our proposed framework uses a Random Forest (RF) classifier outperforming with 93.65% accuracy compared to other ML algorithms. Also, we have achieved low data storage cost, low latency, and high scalability by employing Inter Planetary File System (IPFS) and a 6G network, respectively.
Hongjian Yin, E Chen, Yan Zhu, Rongquan Feng · 5 authors
In this paper, we address the problem of secure decision of membership. We present a Zero-Knowledge Dual Membership Proof (ZKDMP) protocol, which can support positive and negative (Pos-and-Neg) membership decisions simultaneously. To do it, two secure aggregation functions are used to compact an arbitrarily-sized subset into an element in a cryptographic space. By using these aggregation functions, a subset can achieve a secure representation, and the representation size of the subsets is reduced to the theoretical lower limit. Moreover, the zeros-based and poles-based secure representation of the subset are used to decide Pos-and-Neg membership, respectively. We further verify the feasibility of combining these two secure representations of the subset, so this result is used to construct our dual membership decision cryptosystem. Specifically, our ZKDMP protocol is proposed for dual membership decisions, which can realize a cryptographic proof of strict Pos-and-Neg membership simultaneously. Furthermore, the zero-knowledge property of our construction ensures that the information of the tested element will not be leaked during the implementation of the protocol. In addition, we provide detailed security proof of our ZKDMP protocol, including positive completeness, negative completeness, soundness and zero-knowledge.
Paola Torrico Morón, Salma Salimi, Jorge Peña Queralta, Tomi Westerlund
Systems for relative localization in multi-robot systems based on ultra-wideband (UWB) ranging have recently emerged as robust solutions for GNSS-denied environments. Scalability remains one of the key challenges, particularly in ad-hoc deployments. Recent solutions include dynamic allocation of active and passive localization modes for different robots or nodes in the system. With larger-scale systems becoming more distributed, key research questions arise in the areas of security and trustability of such localization systems. This paper studies the potential integration of collaborative-decision making processes with distributed ledger technologies. Specifically, we investigate the design and implementation of a methodology for running an UWB role allocation algorithm within smart contracts in a blockchain. In previous works, we have separately studied the integration of ROS2 with the Hyperledger Fabric blockchain, and introduced a new algorithm for scalable UWB-based localization. In this paper, we extend these works by (i) running experiments with larger number of mobile robots switching between different spatial configurations and (ii) integrating the dynamic UWB role allocation algorithm into Fabric smart contracts for distributed decision-making in a system of multiple mobile robots. This enables us to deliver the same functionality within a secure and trustable process, with enhanced identity and data access management. Our results show the effectiveness of the UWB role allocation for continuously varying spatial formations of six autonomous mobile robots, while demonstrating a low impact on latency and computational resources of adding the blockchain layer that does not affect the localization process.
Numerous resource-constrained Internet of Things (IoT) devices make the edge IoT consisting of unmanned aerial vehicles (UAVs) vulnerable to network intrusion. Therefore, it is critical to design an effective intrusion detection system (IDS). However, the differences in local data sets among UAVs show small samples and uneven distribution, further reducing the detection accuracy of network intrusion. This article proposes a conditional generative adversarial net (CGAN)-based collaborative intrusion detection algorithm with blockchain-empowered distributed federated learning to solve the above problems. This study introduces long short-term memory (LSTM) into the CGAN training to improve the effect of generative networks. Based on the feature extraction ability of LSTM networks, the generated data with CGAN are used as augmented data and applied in the detection and classification of intrusion data. Distributed federated learning with differential privacy ensures data security and privacy and allows collaborative training of CGAN models using multiple distributed data sets. Blockchain stores and shares the training models to ensure security when the global model’s aggregation and updating. The proposed method has good generalization ability, which can greatly improve the detection of intrusion data.
Victor Youdom Kemmoe, Yongseok Kwon, Rasheed Hussain, Sunghyun Cho · 5 authors
Group Key Exchange (GKE) is an important tool to develop secure multi-user applications such as group text messages, ad-hoc networks, and so on. Most of the currently deployed GKE schemes are synchronous, i.e., they require all the participants to be online during their execution. However, with more battery-powered devices being used in such applications, the synchronicity requirement is challenging to fulfill. To fill the gaps, asynchronous GKE schemes have been introduced in the literature. Nevertheless, the currently available asynchronous and synchronous GKE schemes rely on Trusted Third Parties (TTPs) for key establishment and management. To this end, reliance on TTPs is a serious shortcoming since TTPs are well known to be the single point of failure. Furthermore, the existing GKE schemes require participants to perform all computations, which can degrade the performance of resource-constrained devices such as Internet of Things (IoT) devices. To solve these problems, in this paper, we propose an asynchronous GKE scheme that uses blockchain and smart contracts to store the security keys-related material and reduce the computational load of the participants. Furthermore, our proposed scheme provides Perfect Forward Secrecy (PFS) and Post-Compromised Security (PCS). Our implementation on Ethereum shows that the proposed scheme can scale to more than 100 participants when combined with a distributed storage system.
Security is a challenging issue for M2M/IoT applications due to the deployment, decentralization and heterogeneity of M2M and IoT devices. Typical security solutions may not be suitable for M2M/IoT systems regarding the difficulties encountered for their implementation on resource-constrained devices. In this paper, we discuss the architectures deployed for M2M communications and the security challenges, as well as the vulnerabilities and solutions to counter possible attacks. We present a lightweight design based on a private blockchain to secure wireless M2M communications at the device domain level. Blockchain integration provides secure storage of data while preserving integrity traceability and availability. Besides, the evaluation and experimentations under NS3 simulator of the proposed scheme show that the authentication mechanism is lightweight, and presents better performances comparatively to other protocols in terms of key parameters as communication and computational overheads, average delay and energy consumption.
In the era of Industry 4.0, the Industrial Internet of Things (IIoT) has been applied to help physical entities to access real-time data in the network and share critical information. However, both the decentralization of IIoT and the heterogeneity of different devices constituting IIoT also pose a serious threat to secure communication between entities. Although the encryption technologies can ensure the confidentiality of communication data, the security of key becomes more important for devices in IIoT. Recently, some asymmetric group key agreement (AGKA) protocols have been proposed to negotiate a common encryption key for group members, and each group member holds its decryption key. However, the existing AGKA protocols fail to effectively control the access of agreement participants in IIoT. To solve this problem, in this article, we propose an AGKA protocol based on blockchain and attribute for IIoT. The proposed protocol not only realizes the access control of agreement participants but also realizes the automation of access control, the tamper resistance, and the nonrepudiation of the agreement process. The security and performance analysis of the proposed protocol show that it is more secure and effective compared with the existing AGKA protocols.
When given a cryptographic public verification key, a receiver needs to be sure about the authenticity of the sender. Whenever an adversary is able to replace a well-intended public verification key of one of two participants within a communication relationship, she is able to send maliciously signed messages, using her own secret key, thereby compromising the whole authorization system. To overcome these issues for small to medium-sized distributed sensor networks, we previously proposed the NFC-Key Exchange protocol. Using the NFC-KE challenge-response authorization scheme, an attacker will not be able to intercept any communication unless she is authorized by a centrally trusted authority. Though, the NFC-KE protocol considers only local file storages for the storing operations of the authorized public-keys. This approach is inherently vulnerable to any zero-day exploits that enable an attacker to infiltrate the filesystem. Additionally, once the central authority component is restarted or becomes corrupted, every previously exchanged key needs to be reauthenticated. By using the Distributed Ledger Technology (DLT) framework Hyperledger Fabric, this paper proposes a new extension concept for the NFC-KE protocol in order to enhance the security of the public-key store. By using this extension, the NFC-KE protocol gains increased tamper-resistance and outage resilience, due to the decentralized nature of the DLT.
Yuling Chen, Xiong Yang, Tao Li, Yi Ren · 5 authors
Wireless Sensor Network (WSN) is a distributed sensor network composed a large number of nodes with low cost, low performance and self-management. The special structure of WSN brings both convenience and vulnerability. For example, a malicious participant can launch attacks by capturing a physical device. Therefore, node authentication that can resist malicious attacks is very important to network security. Recently, blockchain technology has shown the potential to enhance the security of the Internet of Things (IoT). In this paper, we propose a Blockchain-empowered Authentication Scheme (BAS) for WSN. In our scheme, all nodes are managed by utilizing the identity information stored on the blockchain. Besides, the simulation experiment about worm detection is executed on BAS, and the security is evaluated from detection and infection rate. The experiment results indicate that the proposed scheme can effectively inhibit the spread and infection of worms in the network.
This research aims to compare the performance between the Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) methods in predicting the Bitcoin exchange rate against the US Dollar (BTC-USD). The data used comes from Yahoo Finance for the period 2017-2022. Each model is built with a comparable architecture and evaluated using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), coefficient of determination (R²), and prediction accuracy metrics. The results show that the LSTM model performed better on the test data with a MAPE of 3.80% and an accuracy of 96.20%, while the GRU model achieved a MAPE of 5.13% and an accuracy of 94.87%. Although the GRU model performed better on the training data, the LSTM model showed better generalization ability on the testing data. This research provides important insights into the selection of the optimal recurrent neural network architecture for Bitcoin exchange rate prediction which is known for its high volatility.
Sana Amjad, Shahid Abbas, Zain Abubaker, Mohammed H. Alsharif · 6 authors
This paper proposes a blockchain-based node authentication model for the Internet of sensor things (IoST). The nodes in the network are authenticated based on their credentials to make the network free from malicious nodes. In IoST, sensor nodes gather the information from the environment and send it to the cluster heads (CHs) for additional processing. CHs aggregate the sensed information. Therefore, their energy rapidly depletes due to extra workload. To solve this issue, we proposed distance, degree, and residual energy-based low-energy adaptive clustering hierarchy (DDR-LEACH) protocol. DDR-LEACH is used to replace CHs with the ordinary nodes based on maximum residual energy, degree, and minimum distance from BS. Furthermore, storing a huge amount of data in the blockchain is very costly. To tackle this issue, an external data storage, named as interplanetary file system (IPFS), is used. Furthermore, for ensuring data security in IPFS, AES 128-bit is used, which performs better than the existing encryption schemes. Moreover, a huge computational cost is required using a proof of work consensus mechanism to validate transactions. To solve this issue, proof of authority (PoA) consensus mechanism is used in the proposed model. The simulation results are carried out, which show the efficiency and effectiveness of the proposed system model. The DDR-LEACH is compared with LEACH and the simulation results show that DDR-LEACH outperforms LEACH in terms of energy consumption, throughput, and improvement in network lifetime with CH selection mechanism. Moreover, transaction cost is computed, which is reduced by PoA during data storage on IPFS and service provisioning. Furthermore, the time is calculated in the comparison of AES 128-bit scheme with existing scheme. The formal security analysis is performed to check the effectiveness of smart contract against attacks. Additionally, two different attacks, MITM and Sybil, are induced in our system to show our system model's resilience against cyber attacks.
Alberto Carelli, Andrea Palmieri, Antonio Vilei, Fabien Castanier · 5 authors
Internet-of-Things (IoT) and sensor technologies have enabled the collection of data in a distributed fashion for analysis and evidence-based decision making. However, security concerns regarding the source, confidentiality and integrity of the data arise. The most common method of protecting data transmission in sensor systems is Transport Layer Security (TLS) or its datagram counterpart (DTLS) today, but exist an alternative option based on Distributed Ledger Technology (DLT) that promise strong security, ease of use and potential for large scale integration of heterogeneous sensor systems. A DLT such as the IOTA Tangle offers great potential to improve sensor data exchange. This paper presents L2Sec, a cryptographic protocol which is able to secure data exchanged over the IOTA Tangle. This protocol is suitable for implementation on constrained devices, such as common IoT devices, leading to greater scalability. The first experimental results evidence the effectiveness of the approach and advocate for the integration of an hardware secure element to improve the overall security of the protocol. The L2Sec source code is released as open source repository on GitHub.
In this paper, an encryption and trust evaluation model is proposed on the basis of a blockchain in which the identities of the Aggregator Nodes (ANs) and Sensor Nodes (SNs) are stored. The authentication of ANs and SNs is performed in public and private blockchains, respectively. However, inauthentic nodes utilize the network's resources and perform malicious activities. Moreover, the SNs have limited energy, transmission range and computational capabilities, and are attacked by malicious nodes. Afterwards, the malicious nodes transmit wrong information of the route and increase the number of retransmissions due to which the SNs' energy is rapidly consumed. The lifespan of the wireless sensor network is reduced due to the rapid energy dissipation of the SNs. Furthermore, the throughput increases and packet loss increase with the presence of malicious nodes in the network. The trust values of SNs are computed to eradicate the malicious nodes from the network. Secure routing in the network is performed considering residual energy and trust values of the SNs. Moreover, the Rivest-Shamir-Adleman (RSA), a cryptosystem that provides asymmetric keys, is used for securing data transmission. The simulation results show the effectiveness of the proposed model in terms of high packet delivery ratio.
Shahid Abbas, Hina Nasir, Ahmad Almogren, Ayman Altameem · 5 authors
Internet of Underwater Things (IoUT) Networks are used to sense different aquatic parameters like temperature, pressure, pollution, etc. They are also used to forecast the ocean’s weather to collect information about natural disasters. However, they are easily compromised by attackers due to deployment in unattended environments. To overcome these issues, security is required in IoUT networks to avoid unauthorized access and ensure network credibility. This work proposes an authentication and a malicious node detection mechanism to restrict the unauthorized external nodes from accessing the network and the internal nodes from acting maliciously, respectively. Moreover, blockchain stores the hashes of sensor nodes’ credentials during the registration process to make the system secure and traceable. Meanwhile, a weighted trust evaluation mechanism is implemented for data aggregation and detection of malicious nodes. Moreover, an additive increase multiplicative decrease algorithm puts malicious nodes in an intensive observation queue to verify the data of malicious nodes before aggregating. Moreover, weights are assigned to sensor nodes based on their behaviour. If the weight of a sensor node becomes zero, it is revoked by the blockchain. The simulation results show the efficiency of our proposed malicious node detection mechanism in terms of energy consumption and propagation delay.
Nowadays, sensor networks are one of the hottest scientific issues. A lot of research has been done to improve their efficiency. Wireless Sensor Networks (WSN) are applied as an important and efficient technology in many industries such as military operations, security systems, intelligent transportation systems, medics, agriculture, and many others. Key agreement is a challenging point in the security of these networks. Sensor nodes connect to each other using cryptography techniques, however, use of the classic key management techniques such as key distribution center is inefficient because of resource-constrained nature of the sensor nodes. This paper proposes a hierarchical multiple key agreement scheme. In the proposed scheme, two nodes can produce multiple session keys, just with only one run of the key agreement protocol by two nodes in the hierarchical system. As well as its efficiency, this new scheme is based on identity and non-interactive protocol. Being zero-knowledge proof is another advantage of the scheme.
Distributed key generation (DKG) is widely used in multi-party computation and decentralized applications. DKG has two phases, namely sharing and reconstruction. Most of the prior DKG protocols need at least 2 rounds for the sharing phase, in case some party raises a dispute. The existing 1-round DKG protocol [Fouqueet al., PKC’01], built based on a publicly verifiable secret sharing (PVSS) scheme, assumes a static adversary model and its reconstruction phase requires$O(n^{2})$communication complexity. Motivated by the observation that a ciphertext-policy attribute-based encryption (CP-ABE) scheme hides secret sharing (SS) in ciphertext, we utilize decentralized CP-ABE to achieve the first adaptively secure 1-round DKG protocol. Firstly, a CP-ABE scheme enables the ciphertexts in DKG to be externally decrypted, making our protocol superior to the PVSS-based DKG protocol in reconstruction. The communication and computation complexities are both lowered to$O(n)$thanks to the constant-sized decryption key and the proposed batch decryption. The use of CP-ABE also makes our DKG protocol storage-friendly, i.e., the parties store no ciphertext after the sharing phase. Secondly, we add non-interactive zero-knowledge (NIZK) proofs to make the CP-ABE ciphertext publicly verifiable by leveraging the sigma protocol and the Fiat-Shamir heuristic. Thirdly, we demonstrate our protocol’s feasibility by presenting a proof-of-concept implementation over Ethereum, which is used as a public channel and a trustworthy computation platform. The implementation is a non-trivial task due to Ethereum’s incompatibility with the bilinear mapping group.
The classical blockchain developed for the Bitcoin cryptocurrency has evolved since its introduction more than a decade ago. Blockchain exists in different forms for different purposes and operational contexts. There has been a significant growth in the business use cases of blockchain which is based on the unique attributes of the distributed ledger technology. Blockchain provides peer-to-peer distribution of data in a traceable and decentralized architecture that attains data authentication using consensus protocols. Blockchain as a distributed ledger is the fusion of cryptography, peer-to-peer networking technology, distributed system technology, and consensus mechanism to assure information security and digital asset management. Consensus mechanisms are applied to the distributed ledger that operates in a peer-to-peer network where message transmission between peers is validated and stored across all active peers. Reaching an agreement to validate message transmission and maintaining the correctness of the state of data in a network for critical wireless sensor networks have become a necessary requirement for networks that span several subsystems covering a large operational area. Due to the resource constrained nature of the active actors of wireless sensor networks, any cryptographic solution to be adopted must be lightweight and efficient as well. This paper proposes a blockchain-based decentralized mechanism for authentication of node data for storage onto a distributed ledger. The coloured Petri net was used to model and simulate by detailing the critical attributes of the workings of the system that is based on cyber-physical IoT architecture.