• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2255-2281
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• 2021

Channel characteristic-based physical layer authentication is one potential identity authentication scheme in wireless communication, such as used in a fog computing environment. While existing channel characteristic-based physical layer authentication schemes may be efficient when deployed in the conventional wireless network environment, they may be less efficient and practical for the industrial wireless communication environment due to the varying requirements. We observe that this is a topic that is understudied, and therefore in this paper, we review the constructions and performance of several commonly used test statistics and analyze their performance in typical industrial wireless networks using simulation experiments. The findings from the simulations show a number of limitations in existing channel characteristic-based physical layer authentication schemes. Therefore, we believe that it is a good idea to combine machine learning and multiple test statistics for identity authentication in future industrial wireless network deployment. Four machine learning methods prove that the scheme significantly improves the authentication accuracy and solves the challenge of choosing a threshold.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.323-342
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• 2021

Personal health records (PHRs) is an electronic medical system that enables patients to acquire, manage and share their health data. Nevertheless, data confidentiality and user privacy in PHRs have not been handled completely. As a fine-grained access control over health data, ciphertext-policy attribute-based encryption (CP-ABE) has an ability to guarantee data confidentiality. However, existing CP-ABE solutions for PHRs are facing some new challenges in access control, such as policy privacy disclosure and dynamic policy update. In terms of addressing these problems, we propose a privacy protection and dynamic share system (PPADS) based on CP-ABE for PHRs, which supports full policy hiding and flexible access control. In the system, attribute information of access policy is fully hidden by attribute bloom filter. Moreover, data user produces a transforming key for the PHRs Cloud to change access policy dynamically. Furthermore, relied on security analysis, PPADS is selectively secure under standard model. Finally, the performance comparisons and simulation results demonstrate that PPADS is suitable for PHRs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4224-4243
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• 2021

Cognitive radio (CR) is a feasible intelligent technology and can be used as an effective solution to spectrum scarcity and underutilization. As the key function of CR, cooperative spectrum sensing (CSS) is able to effectively prevent the harmful interference with primary users (PUs) and identify the available spectrum resources by exploiting the spatial diversity of multiple secondary users (SUs). However, the open nature of the cognitive radio networks (CRNs) framework makes CSS face many security threats, such as, the malicious user (MU) launches Byzantine attack to undermine CRNs. For this aim, we make an in-depth analysis of the motive and purpose from the MU's perspective in the interweave CR system, aiming to provide the future guideline for defense strategies. First, we formulate a dynamic Byzantine attack model by analyzing Byzantine behaviors in the process of CSS. On the basis of this, we further make an investigation on the condition of making the fusion center (FC) blind when the fusion rule is unknown for the MU. Moreover, the throughput and interference to the primary network are taken into consideration to evaluate the impact of Byzantine attack on the interweave CR system, and then analyze the optimal strategy of Byzantine attack when the fusion rule is known. Finally, theoretical proofs and simulation results verify the correctness and effectiveness of analyses about the impact of Byzantine attack strategy on the throughput and interference.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.609-631
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• 2022

The main goal of VANETs is to improve the safety of all road users. Therefore, the accuracy and trustworthiness of messages transmitted in VANETs are essential, given that life may rely on them. VANETs are provided with basic security services through the use of public key infrastructure-based authentication. However, the trust of users is still an open issue in VANETs. It is important to prevent bogus message attacks from internal vehicles as well as protect vehicle privacy. In this paper, we propose a trust management scheme that ensures trust in VANETs while maintaining vehicle privacy. The trust scheme establishes trust between vehicles where a trust value is assigned to every vehicle based on its behavior and messages are accepted only from vehicles whose trust value is greater than a threshold, therefore, protecting VANETs from malicious vehicles and eliminating bogus messages. If a traffic event happens, vehicles upload event messages to the reachable roadside unit (RSU). Once the RSU has confirmed that the event happened, it announces the event to vehicles in its vicinity and records it into the blockchain. Using this mechanism, RSUs are prevented from sending fake or unverified event notifications. Simulations are carried out in the context of bogus message attacks to evaluate the trust scheme's reliability and efficiency. The results of the simulation indicate that the proposed scheme outperforms the compared schemes and is highly resistant to bogus message attacks.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.240-257
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• 2023

The industrial Internet of Things (IIoT) is characterized by intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. The heterogeneous IIoT devices require a high data rate, high reliability, high coverage, and low delay, thus posing a significant challenge to information security. High-performance edge and cloud servers are a good backup solution for IIoT devices with limited capabilities. However, privacy leakage and network attack cases may occur in heterogeneous IIoT environments. Cloud-based multi-party computing is a reliable privacy-protecting technology that encourages multiparty participation in joint computing without privacy disclosure. However, the default cloud selection method does not meet the heterogeneous IIoT requirements. The server can be dishonest, significantly increasing the probability of multi-party computation failure or inefficiency. This paper proposes a blockchain and smart contract-based optimized cloud node selection framework. Different participants choose the best server that meets their performance demands, considering the communication delay. Smart contracts provide a progressive request mechanism to increase participation. The simulation results show that our framework improves overall multi-party computing efficiency by up to 44.73%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.91-97
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• 2023

Recent research shows that latent directions can be used to image process towards certain attributes. However, controlling the generation process of generative model is very difficult. Though the latent directions are used to image process for certain attributes, many restrictions are required to enhance the attributes received the latent vectors according to certain text and prompts and other attributes largely unaffected. This study presents a generative model having certain restriction to the latent vectors for image generation and manipulation. The suggested method requires only few minutes per manipulation, and the simulation results through Tensorflow Variational Auto-encoder show the effectiveness of the suggested approach with extensive results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1450-1470
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• 2023

In a Vehicular Cloud (VC) network, an announcement protocol plays a critical role in promoting safety and efficiency by enabling vehicles to disseminate safety-related messages. The reliability of message exchange is essential for improving traffic safety and road conditions. However, verifying the message authenticity could lead to the potential compromise of vehicle privacy, presenting a significant security challenge in the VC network. In contrast, if any misbehavior occurs, the accountable vehicle must be identifiable and removed from the network to ensure public safety. Addressing this conflict between message reliability and privacy requires a secure protocol that satisfies accountability properties while preserving user privacy. This paper presents a novel announcement protocol for secure communication in VC networks that utilizes group signature to achieve seemingly contradictory goals of reliability, privacy, and accountability. We have developed the first comprehensive announcement protocol for VC using group signature, which has been shown to improve the performance efficiency and feasibility of the VC network through performance analysis and simulation results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1728-1742
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• 2023

In this paper, we extended a hierarchical clustering technique, which is the most researched in the sensor network field, and studied a dynamic differential clustering technique to minimize energy consumption and ensure equal lifespan of all sensor nodes while considering the mobility of sinks. In a sensor network environment with mobile sinks, clusters close to the sinks tend to consume more forwarding energy. Therefore, clustering that considers forwarding energy consumption is desired. Since all clusters form a hierarchical tree, the number of levels of the tree must be considered based on the size of the cluster so that the cluster size is not growing abnormally, and the energy consumption is not concentrated within specific clusters. To verify that the proposed DDC protocol satisfies these requirements, a simulation using Matlab was performed. The FND (First Node Dead), LND (Last Node Dead), and residual energy characteristics of the proposed DDC protocol were compared with the popular clustering protocols such as LEACH and EEUC. As a result, it was shown that FND appears the latest and the point at which the dead node count increases is delayed in the DDC protocol. The proposed DDC protocol presents 66.3% improvement in FND and 13.8% improvement in LND compared to LEACH protocol. Furthermore, FND improved 79.9%, but LND declined 33.2% when compared to the EEUC. This verifies that the proposed DDC protocol can last for longer time with more number of surviving nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.903-921
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• 2024

Industry 5.0 puts forward higher requirements for smart cities, including low-carbon, sustainable, and people-oriented, which pose challenges to the design of smart cities. In response to the above challenges, this study introduces the cyber-physical-social system (CPSS) and parallel system theory into the design of smart cities, and constructs a smart city framework based on parallel system theory. On this basis, in order to enhance the security of smart cities, a sustainable patrol subsystem for smart cities has been established. The intelligent patrol system uses a drone platform, and the trajectory planning of the drone is a key problem that needs to be solved. Therefore, a mathematical model was established that considers various objectives, including minimizing carbon emissions, minimizing noise impact, and maximizing coverage area, while also taking into account the flight performance constraints of drones. In addition, an improved metaheuristic algorithm based on ant colony optimization (ACO) algorithm was designed for trajectory planning of patrol drones. Finally, a digital environmental map was established based on real urban scenes and simulation experiments were conducted. The results show that compared with the other three metaheuristic algorithms, the algorithm designed in this study has the best performance.

• Journal of Internet of Things and Convergence
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• v.7 no.1
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• pp.9-19
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• 2021

The data mining design incorporated with big data based cloud computing system is investigated for the nuclear terrorism prevention where the conventional physical protection system (PPS) is modified. The networking of terror related bodies is modeled by simulation study for nuclear forensic incidents. It is needed for the government to detect the terrorism and any attempts to attack to innocent people without illegal tapping. Although the mathematical algorithm of the study can't give the exact result of the terror incident, the potential possibility could be obtained by the simulations. The result shows the shape oscillation by time. In addition, the integration of the frequency of each value can show the degree of the transitions of the results. The value increases to -2.61741 in 63.125th hour. So, the terror possibility is highest in later time.