Pub Date : 2025-11-06DOI: 10.1016/j.jnca.2025.104370
Wanbanker Khongbuh , Goutam Saha
The Internet of Things (IoT) and software-defined networks (SDN) have opened up new opportunities for innovation. Many of the limitations of the IoT system can be rectified with the SDN concepts. Thus, the combination of SDN and IoT has tremendous potential in various application domains. As the number of IoT devices is increasing with time, the scalability issues need to be further improved. Another significant challenge in IoT environments is mobility. Maintaining seamless mobility and persistent connectivity for IoT devices operating over large-scale or geographically dispersed environments presents a significant research challenge. But scalability and mobility are complex challenges. Developing scalable, mobile, and adaptive network architectures is crucial for SDN-enabled IoT ecosystems. Using SDN-enabled IoT networks, we introduced a comprehensive approach to address these challenges. Here, a new protocol based on OpenFlow of SDN and 6LoWPAN of the IoT system, namely, 6LoWSD has been proposed. In this investigation, emphasis has been placed on techniques on how the proposed 6LoWSD can improve scalability and mobility issues. In this study, experiments with the proposed protocol were performed using physical devices and a simulated platform. The results were compared with the 6LoWPAN counterpart and were found to be satisfactory.
{"title":"A comprehensive study of the 6LoWSD protocol architecture with respect to scalability and mobility for SDN-enabled IoT networks","authors":"Wanbanker Khongbuh , Goutam Saha","doi":"10.1016/j.jnca.2025.104370","DOIUrl":"10.1016/j.jnca.2025.104370","url":null,"abstract":"<div><div>The Internet of Things (IoT) and software-defined networks (SDN) have opened up new opportunities for innovation. Many of the limitations of the IoT system can be rectified with the SDN concepts. Thus, the combination of SDN and IoT has tremendous potential in various application domains. As the number of IoT devices is increasing with time, the scalability issues need to be further improved. Another significant challenge in IoT environments is mobility. Maintaining seamless mobility and persistent connectivity for IoT devices operating over large-scale or geographically dispersed environments presents a significant research challenge. But scalability and mobility are complex challenges. Developing scalable, mobile, and adaptive network architectures is crucial for SDN-enabled IoT ecosystems. Using SDN-enabled IoT networks, we introduced a comprehensive approach to address these challenges. Here, a new protocol based on OpenFlow of SDN and 6LoWPAN of the IoT system, namely, 6LoWSD has been proposed. In this investigation, emphasis has been placed on techniques on how the proposed 6LoWSD can improve scalability and mobility issues. In this study, experiments with the proposed protocol were performed using physical devices and a simulated platform. The results were compared with the 6LoWPAN counterpart and were found to be satisfactory.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"245 ","pages":"Article 104370"},"PeriodicalIF":8.0,"publicationDate":"2025-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145461588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-04DOI: 10.1016/j.jnca.2025.104373
Riccardo Venanzi, Giuseppe Di Modica, Luca Foschini, Paolo Bellavista
According to both academic and industry perspectives, the Fourth Industrial Revolution has brought about a paradigm shift in the manufacturing sector enabling companies to enhance their competitiveness in the global market. To achieve this goal, manufacturing companies will need to undertake a deep digital transformation, primarily by introducing advanced Information Technology (IT) into traditionally less digitalized departments, such as shop floors, where Operational Technology (OT) currently dominate. For the full achievement of Industry 4.0 revolution objectives, practitioners believe in the strong requirement of a progressive and tight integration between IT and OT departments. In the depicted scenario, communication technologies are expected to play a pivotal role in facilitating the integration process, but other more recent and advanced IT have also proven helpful. In particular, the topic of IT/OT integration has attracted significant attention from various research communities that have sought to identify both the opportunities and challenges associated with its implementation. Although some good surveys of those works have appeared in the literature, to the best of our knowledge, no comprehensive review has yet been conducted that is fully dedicated to the topic of IT/OT convergence. In this paper, we propose a holistic approach to examine the various dimensions of IT/OT integration, which we classify into five interconnected realms, Communication, IT-Driven Support to OT, Human Centricity, Advanced Industrial Control Systems, and cybersecurity. Furthermore, we develop a realm-oriented taxonomy to organize the surveyed works in a structured manner, offering readers a clear overview of the current state of the literature, along with insights into unexplored opportunities and future directions for IT/OT integration.
{"title":"Towards IT/OT integration in industry digitalization: A comprehensive survey","authors":"Riccardo Venanzi, Giuseppe Di Modica, Luca Foschini, Paolo Bellavista","doi":"10.1016/j.jnca.2025.104373","DOIUrl":"10.1016/j.jnca.2025.104373","url":null,"abstract":"<div><div>According to both academic and industry perspectives, the Fourth Industrial Revolution has brought about a paradigm shift in the manufacturing sector enabling companies to enhance their competitiveness in the global market. To achieve this goal, manufacturing companies will need to undertake a deep digital transformation, primarily by introducing advanced Information Technology (IT) into traditionally less digitalized departments, such as shop floors, where Operational Technology (OT) currently dominate. For the full achievement of Industry 4.0 revolution objectives, practitioners believe in the strong requirement of a progressive and tight integration between IT and OT departments. In the depicted scenario, communication technologies are expected to play a pivotal role in facilitating the integration process, but other more recent and advanced IT have also proven helpful. In particular, the topic of IT/OT integration has attracted significant attention from various research communities that have sought to identify both the opportunities and challenges associated with its implementation. Although some good surveys of those works have appeared in the literature, to the best of our knowledge, no comprehensive review has yet been conducted that is fully dedicated to the topic of IT/OT convergence. In this paper, we propose a holistic approach to examine the various dimensions of IT/OT integration, which we classify into five interconnected realms, Communication, IT-Driven Support to OT, Human Centricity, Advanced Industrial Control Systems, and cybersecurity. Furthermore, we develop a realm-oriented taxonomy to organize the surveyed works in a structured manner, offering readers a clear overview of the current state of the literature, along with insights into unexplored opportunities and future directions for IT/OT integration.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"245 ","pages":"Article 104373"},"PeriodicalIF":8.0,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145441548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-30DOI: 10.1016/j.jnca.2025.104374
Faisal Murad , Jie Cui , Muhammad Aurangzeb Khan , Depeng Chen
<div><div>Website fingerprinting aims to infer visited websites from encrypted network traffic. Conventional approaches predominantly assume single-tab browsing, limiting their applicability under realistic multi-tab conditions, where concurrent flows introduce inter-tab interference, temporal overlap, and attribution ambiguity that degrade classification accuracy. This paper presents Adaptive Context-Aware Multi-Tab Fingerprinting, a dynamic framework designed for multi-tab website fingerprinting through context-driven feature modeling and attention adaptation. ACMF integrates three coordinated modules. (1) CBAM employs an attention-augmented LSTM that processes sequences of packet direction, size, and inter-arrival time with tab-switch indicators, producing a session context vector <span><math><mi>c</mi></math></span>. A self-attention state <span><math><msub><mrow><mi>z</mi></mrow><mrow><mi>t</mi></mrow></msub></math></span> modulates recurrent dynamics, and multi-scale temporal aggregation yields <span><math><mrow><mi>c</mi><mo>=</mo><msub><mrow><mo>∑</mo></mrow><mrow><mi>ℓ</mi></mrow></msub><msub><mrow><mi>ω</mi></mrow><mrow><mi>ℓ</mi></mrow></msub><msup><mrow><mi>h</mi></mrow><mrow><mrow><mo>(</mo><mi>ℓ</mi><mo>)</mo></mrow></mrow></msup></mrow></math></span>. (2) DTAM uses a Transformer encoder with per-slot gating for variable tab cardinality. For each slot feature <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span>, a gate <span><math><mrow><msub><mrow><mi>g</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>=</mo><mi>σ</mi><mrow><mo>(</mo><msubsup><mrow><mi>w</mi></mrow><mrow><mi>g</mi></mrow><mrow><mo>⊤</mo></mrow></msubsup><mrow><mo>[</mo><mi>c</mi><mo>;</mo><msub><mrow><mi>f</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>]</mo></mrow><mo>+</mo><msub><mrow><mi>b</mi></mrow><mrow><mi>g</mi></mrow></msub><mo>)</mo></mrow></mrow></math></span> scales multi-head attention outputs, normalized by <span><math><mrow><msub><mrow><mo>∑</mo></mrow><mrow><mi>i</mi></mrow></msub><msub><mrow><mi>g</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>+</mo><mi>ϵ</mi></mrow></math></span> and followed by a position-wise feed-forward network to produce representation <span><math><mi>F</mi></math></span>. (3) HMLFE combines dilated 1D CNNs to capture local temporal motifs with a GNN that builds a similarity graph using edge weights <span><math><mrow><mo>exp</mo><mrow><mo>(</mo><mo>−</mo><mo>‖</mo><msub><mrow><mi>u</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>−</mo><msub><mrow><mi>u</mi></mrow><mrow><mi>j</mi></mrow></msub><msup><mrow><mo>‖</mo></mrow><mrow><mn>2</mn></mrow></msup><mo>/</mo><mi>τ</mi><mo>)</mo></mrow></mrow></math></span> and performs attention-based message passing. A graph readout operation generates <span><math><msub><mrow><mi>h</mi></mrow><mrow><mi>G</mi></mrow></msub></math></span>, and the final representation <span><math><mrow><mi>r</mi><mo>=</mo><mrow><mo>[</mo><mi>F</mi><mo>∥</mo><msub><mrow><mi>h</mi></mrow><
网站指纹识别旨在从加密的网络流量中推断访问过的网站。传统方法主要假设单标签浏览,限制了它们在实际多标签条件下的适用性,并发流会引入标签间干扰、时间重叠和属性模糊,从而降低分类准确性。本文介绍了自适应上下文感知多标签指纹,这是一个通过上下文驱动的特征建模和注意力适应为多标签网站指纹识别设计的动态框架。ACMF集成了三个协调的模块。(1) CBAM采用一种注意力增强LSTM,该LSTM利用标签切换指示器处理数据包方向、大小和间隔到达时间序列,产生会话上下文向量c。自关注状态zt调节循环动态,多尺度时间聚合产生c=∑r ω r h(r)。(2) DTAM使用变压器编码器,每个插槽对可变选项卡基数进行门控。对于每个槽型特征fi,栅极gi=σ(wg∞[c;fi]+bg)缩放多头注意力输出,通过∑igi+ λ进行归一化,然后通过位置前馈网络生成表示f。(3)HMLFE将扩展1D cnn与使用边权exp(−‖ui−uj‖2/τ)构建相似图的GNN结合起来捕获局部时间主题,并执行基于注意力的消息传递。图形读出操作生成hG,最终表示r=[F∥hG]用于分类。对MultiTab网站指纹数据集的评估达到95.6%的训练准确率和90.5%的验证准确率,超过了并发标签条件下最先进的基线。
{"title":"Adaptive context-aware multi-tab website fingerprinting using hierarchical deep learning","authors":"Faisal Murad , Jie Cui , Muhammad Aurangzeb Khan , Depeng Chen","doi":"10.1016/j.jnca.2025.104374","DOIUrl":"10.1016/j.jnca.2025.104374","url":null,"abstract":"<div><div>Website fingerprinting aims to infer visited websites from encrypted network traffic. Conventional approaches predominantly assume single-tab browsing, limiting their applicability under realistic multi-tab conditions, where concurrent flows introduce inter-tab interference, temporal overlap, and attribution ambiguity that degrade classification accuracy. This paper presents Adaptive Context-Aware Multi-Tab Fingerprinting, a dynamic framework designed for multi-tab website fingerprinting through context-driven feature modeling and attention adaptation. ACMF integrates three coordinated modules. (1) CBAM employs an attention-augmented LSTM that processes sequences of packet direction, size, and inter-arrival time with tab-switch indicators, producing a session context vector <span><math><mi>c</mi></math></span>. A self-attention state <span><math><msub><mrow><mi>z</mi></mrow><mrow><mi>t</mi></mrow></msub></math></span> modulates recurrent dynamics, and multi-scale temporal aggregation yields <span><math><mrow><mi>c</mi><mo>=</mo><msub><mrow><mo>∑</mo></mrow><mrow><mi>ℓ</mi></mrow></msub><msub><mrow><mi>ω</mi></mrow><mrow><mi>ℓ</mi></mrow></msub><msup><mrow><mi>h</mi></mrow><mrow><mrow><mo>(</mo><mi>ℓ</mi><mo>)</mo></mrow></mrow></msup></mrow></math></span>. (2) DTAM uses a Transformer encoder with per-slot gating for variable tab cardinality. For each slot feature <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span>, a gate <span><math><mrow><msub><mrow><mi>g</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>=</mo><mi>σ</mi><mrow><mo>(</mo><msubsup><mrow><mi>w</mi></mrow><mrow><mi>g</mi></mrow><mrow><mo>⊤</mo></mrow></msubsup><mrow><mo>[</mo><mi>c</mi><mo>;</mo><msub><mrow><mi>f</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>]</mo></mrow><mo>+</mo><msub><mrow><mi>b</mi></mrow><mrow><mi>g</mi></mrow></msub><mo>)</mo></mrow></mrow></math></span> scales multi-head attention outputs, normalized by <span><math><mrow><msub><mrow><mo>∑</mo></mrow><mrow><mi>i</mi></mrow></msub><msub><mrow><mi>g</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>+</mo><mi>ϵ</mi></mrow></math></span> and followed by a position-wise feed-forward network to produce representation <span><math><mi>F</mi></math></span>. (3) HMLFE combines dilated 1D CNNs to capture local temporal motifs with a GNN that builds a similarity graph using edge weights <span><math><mrow><mo>exp</mo><mrow><mo>(</mo><mo>−</mo><mo>‖</mo><msub><mrow><mi>u</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>−</mo><msub><mrow><mi>u</mi></mrow><mrow><mi>j</mi></mrow></msub><msup><mrow><mo>‖</mo></mrow><mrow><mn>2</mn></mrow></msup><mo>/</mo><mi>τ</mi><mo>)</mo></mrow></mrow></math></span> and performs attention-based message passing. A graph readout operation generates <span><math><msub><mrow><mi>h</mi></mrow><mrow><mi>G</mi></mrow></msub></math></span>, and the final representation <span><math><mrow><mi>r</mi><mo>=</mo><mrow><mo>[</mo><mi>F</mi><mo>∥</mo><msub><mrow><mi>h</mi></mrow><","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"245 ","pages":"Article 104374"},"PeriodicalIF":8.0,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145404578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-30DOI: 10.1016/j.jnca.2025.104369
Xinyu Fan , Shiyuan Xu , Yibo Cao , Xue Chen , Yu Chen , Tianrun Xu
The rapid development of intelligent transportation systems (ITS) has raised higher requirements for traffic data sharing and collaboration. As an effective solution, vehicular ad-hoc network (VANET) has emerged to support real-time data transfer between vehicles and infrastructure. However, VANET faces the challenges of data security and privacy. To alleviate these, many conditional privacy-preserving authentication (CPPA) schemes have been proposed. CPPA utilizes signature technology to ensure message authenticity while enabling the effective tracing of malicious vehicles. Unfortunately, traditional CPPA schemes fail to consider the security of secret keys stored in tamper-proof devices (TPDs). Additionally, most existing schemes still suffer from excessive computational and communication overhead. In this paper, we propose CPPA-SKU, an efficient CPPA scheme with message recovery for VANET. CPPA-SKU introduces a secret key update method using a secure pseudo-random function and Shamir’s secret sharing to prevent key leakage issues in TPDs. Additionally, CPPA-SKU enables the recovery of relevant messages, eliminating the need to embed messages in signatures, thereby reducing the communication overhead. Furthermore, CPPA-SKU is implemented based on the elliptic curve cryptosystem, which avoids expensive bilinear pairing operations while ensuring the security of signatures. We also formally prove the security of CPPA-SKU in the random oracle model. Comprehensive performance evaluations indicate that CPPA-SKU reduces computational overhead by approximately 1.3–2.8 and communication overhead by approximately 1.5-3.5.
{"title":"CPPA-SKU: Towards efficient conditional privacy-preserving authentication protocol with secret key update in VANET","authors":"Xinyu Fan , Shiyuan Xu , Yibo Cao , Xue Chen , Yu Chen , Tianrun Xu","doi":"10.1016/j.jnca.2025.104369","DOIUrl":"10.1016/j.jnca.2025.104369","url":null,"abstract":"<div><div>The rapid development of intelligent transportation systems (ITS) has raised higher requirements for traffic data sharing and collaboration. As an effective solution, vehicular ad-hoc network (VANET) has emerged to support real-time data transfer between vehicles and infrastructure. However, VANET faces the challenges of data security and privacy. To alleviate these, many conditional privacy-preserving authentication (CPPA) schemes have been proposed. CPPA utilizes signature technology to ensure message authenticity while enabling the effective tracing of malicious vehicles. Unfortunately, traditional CPPA schemes fail to consider the security of secret keys stored in tamper-proof devices (TPDs). Additionally, most existing schemes still suffer from excessive computational and communication overhead. In this paper, we propose CPPA-SKU, an efficient CPPA scheme with message recovery for VANET. CPPA-SKU introduces a secret key update method using a secure pseudo-random function and Shamir’s secret sharing to prevent key leakage issues in TPDs. Additionally, CPPA-SKU enables the recovery of relevant messages, eliminating the need to embed messages in signatures, thereby reducing the communication overhead. Furthermore, CPPA-SKU is implemented based on the elliptic curve cryptosystem, which avoids expensive bilinear pairing operations while ensuring the security of signatures. We also formally prove the security of CPPA-SKU in the random oracle model. Comprehensive performance evaluations indicate that CPPA-SKU reduces computational overhead by approximately 1.3<span><math><mo>×</mo></math></span>–2.8<span><math><mo>×</mo></math></span> and communication overhead by approximately 1.5<span><math><mo>×</mo></math></span>-3.5<span><math><mo>×</mo></math></span>.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"245 ","pages":"Article 104369"},"PeriodicalIF":8.0,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145404577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-30DOI: 10.1016/j.jnca.2025.104371
Wenhui Yu , Jinyao Liu , Xiaoqiang Di , Pei Xiao , Hui Qi
The diversity of network forms and services poses challenges to the TCP protocol in achieving good performance. The current XQUIC implementation of the QUIC protocol still adopts TCP’s heuristic congestion control mechanisms, resulting in limited performance gains. In recent years, reinforcement learning-based congestion control has emerged as an effective alternative to traditional strategies, but existing algorithms are not optimized for dynamic network characteristics. In this paper, we propose a deep reinforcement learning-based congestion control algorithm, Dynamic Network Congestion Control for QUIC Based on PPO (DNCCQ-PPO). To address the heterogeneity of dynamic network training environments, we introduce a novel sampling interaction mechanism, action space, and reward function, and propose an asynchronous distributed training scheme. Additionally, we develop a generalized reinforcement learning framework for congestion control algorithm development that supports XQUIC, and verify the performance of DNCCQ-PPO within this framework. Experimental results demonstrate the algorithm’s fast convergence and excellent training performance. In performance tests, DNCCQ-PPO achieves throughput comparable to that of CUBIC while reducing latency by 54.78%. In multi-stream fairness tests, it outperforms several mainstream algorithms. In satellite network simulations, DNCCQ-PPO maintains high throughput while reducing latency by 69.58% and 72.77% compared to CUBIC and PCC, respectively.
{"title":"DNCCQ-PPO: A dynamic network congestion control algorithm based on deep reinforcement learning for XQUIC","authors":"Wenhui Yu , Jinyao Liu , Xiaoqiang Di , Pei Xiao , Hui Qi","doi":"10.1016/j.jnca.2025.104371","DOIUrl":"10.1016/j.jnca.2025.104371","url":null,"abstract":"<div><div>The diversity of network forms and services poses challenges to the TCP protocol in achieving good performance. The current XQUIC implementation of the QUIC protocol still adopts TCP’s heuristic congestion control mechanisms, resulting in limited performance gains. In recent years, reinforcement learning-based congestion control has emerged as an effective alternative to traditional strategies, but existing algorithms are not optimized for dynamic network characteristics. In this paper, we propose a deep reinforcement learning-based congestion control algorithm, Dynamic Network Congestion Control for QUIC Based on PPO (DNCCQ-PPO). To address the heterogeneity of dynamic network training environments, we introduce a novel sampling interaction mechanism, action space, and reward function, and propose an asynchronous distributed training scheme. Additionally, we develop a generalized reinforcement learning framework for congestion control algorithm development that supports XQUIC, and verify the performance of DNCCQ-PPO within this framework. Experimental results demonstrate the algorithm’s fast convergence and excellent training performance. In performance tests, DNCCQ-PPO achieves throughput comparable to that of CUBIC while reducing latency by 54.78%. In multi-stream fairness tests, it outperforms several mainstream algorithms. In satellite network simulations, DNCCQ-PPO maintains high throughput while reducing latency by 69.58% and 72.77% compared to CUBIC and PCC, respectively.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"245 ","pages":"Article 104371"},"PeriodicalIF":8.0,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145404579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-30DOI: 10.1016/j.jnca.2025.104372
Naveen Kumar, Ankit Chaudhary
The adoption of Unmanned Aerial Vehicles (UAVs) or Drone technology is increasing from miliary to civilian domains because of its effectiveness in performing difficult operations. UAV communicates with Ground Control Station (GCS) in presence of open wireless channel which is insecure. The communication is susceptible to various security attacks because of open nature of wireless channel. A number of traditional cryptographic solutions are provided to mitigate these attacks, but there is need of large amount of computational resources. The UAVs are equipped with limited resources, so a lightweight mechanism is required. So, in this paper, a lightweight authentication and key agreement protocol is proposed that makes use of Physical Unclonable Function (PUF) technology along with the hash function and XOR operations to secure the communication. The proposed scheme ensures the robust authentication along with session key update mechanism. The security of proposed mechanism is validated and verified by formal security analysis using Scyther simulation tool, Burrows-Abadi-Needham (BAN) logic and Real-or-Random (ROR) model. The comprehensive analysis demonstrates that the scheme effectively mitigates known security attacks. The efficiency of proposed protocol is demonstrated by performing the experiments and by comparing it with the state-of-the-art schemes in terms of computation cost, communication cost, energy consumption and security requirements.
{"title":"LiteWTAKA: Authenticating UAV-GCS and UAV–UAV communication using secure and lightweight mechanism based on PUF","authors":"Naveen Kumar, Ankit Chaudhary","doi":"10.1016/j.jnca.2025.104372","DOIUrl":"10.1016/j.jnca.2025.104372","url":null,"abstract":"<div><div>The adoption of Unmanned Aerial Vehicles (UAVs) or Drone technology is increasing from miliary to civilian domains because of its effectiveness in performing difficult operations. UAV communicates with Ground Control Station (GCS) in presence of open wireless channel which is insecure. The communication is susceptible to various security attacks because of open nature of wireless channel. A number of traditional cryptographic solutions are provided to mitigate these attacks, but there is need of large amount of computational resources. The UAVs are equipped with limited resources, so a lightweight mechanism is required. So, in this paper, a lightweight authentication and key agreement protocol is proposed that makes use of Physical Unclonable Function (PUF) technology along with the hash function and XOR operations to secure the communication. The proposed scheme ensures the robust authentication along with session key update mechanism. The security of proposed mechanism is validated and verified by formal security analysis using Scyther simulation tool, Burrows-Abadi-Needham (BAN) logic and Real-or-Random (ROR) model. The comprehensive analysis demonstrates that the scheme effectively mitigates known security attacks. The efficiency of proposed protocol is demonstrated by performing the experiments and by comparing it with the state-of-the-art schemes in terms of computation cost, communication cost, energy consumption and security requirements.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"245 ","pages":"Article 104372"},"PeriodicalIF":8.0,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145382976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accurate network traffic prediction is critical for efficient network planning and routing, especially in large-scale and dynamic environments. Traditional approaches rely on full-scale measurements, which are often impractical due to cost, scalability, and privacy concerns. Sparse measurements offer a more feasible alternative but lead to incomplete traffic data, posing significant challenges for accurate prediction. To address this, we propose Mamba-NTP, a novel end-to-end Mamba-based Network Traffic Prediction framework designed for sparse measurement settings. Leveraging the recent Mamba state-space model, Mamba-NTP captures long-range spatiotemporal dependencies with linear time complexity, enabling efficient and scalable prediction. Furthermore, Mamba-NTP employs a multi-task learning paradigm — comprising Traffic Completion, Graph Learning, and Traffic Prediction tasks — to extract shared traffic representations and enhance prediction robustness. In addition, the graph learning task in Mamba-NTP leverages graph learning techniques to infer intrinsic traffic correlations and model the inner traffic dependencies among network nodes. Extensive experiments on real-world datasets demonstrate that Mamba-NTP consistently outperforms state-of-the-art methods in both accuracy and efficiency under various levels of measurement sparsity.
{"title":"Mamba-NTP: Mamba-based network traffic prediction with sparse measurements","authors":"Chengzhe Xu , Yingya Guo , Huan Luo , Yue Yu , Zebo Huang","doi":"10.1016/j.jnca.2025.104364","DOIUrl":"10.1016/j.jnca.2025.104364","url":null,"abstract":"<div><div>Accurate network traffic prediction is critical for efficient network planning and routing, especially in large-scale and dynamic environments. Traditional approaches rely on full-scale measurements, which are often impractical due to cost, scalability, and privacy concerns. Sparse measurements offer a more feasible alternative but lead to incomplete traffic data, posing significant challenges for accurate prediction. To address this, we propose Mamba-NTP, a novel end-to-end Mamba-based Network Traffic Prediction framework designed for sparse measurement settings. Leveraging the recent Mamba state-space model, Mamba-NTP captures long-range spatiotemporal dependencies with linear time complexity, enabling efficient and scalable prediction. Furthermore, Mamba-NTP employs a multi-task learning paradigm — comprising Traffic Completion, Graph Learning, and Traffic Prediction tasks — to extract shared traffic representations and enhance prediction robustness. In addition, the graph learning task in Mamba-NTP leverages graph learning techniques to infer intrinsic traffic correlations and model the inner traffic dependencies among network nodes. Extensive experiments on real-world datasets demonstrate that Mamba-NTP consistently outperforms state-of-the-art methods in both accuracy and efficiency under various levels of measurement sparsity.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104364"},"PeriodicalIF":8.0,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145364130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-22DOI: 10.1016/j.jnca.2025.104368
Bin Song , Bin Sun , Qiang Fu , Hao Li
Cloud services are increasingly generating a large amount of Internet traffic. Much of it such as rich media and gaming traffic is not highly sensitive but prefers some protection. The traditional end-to-end encryption such as Transport Layer Security Protocol (TLS) is costly and has its own issues, such as increased latency, while the simple anonymity solutions cannot resist traffic analysis attacks. In this paper, we propose FlowShredder, a protocol-independent and in-network service to secure such traffic in the cloud. FlowShredder aims to break the association between the packets, the data flow, and the hosts by obfuscating the packet header (and some payload if needed). Without the context of the flow and the hosts, these packets are of little value to the adversary. The operation is carried out at cloud gateways, without encrypting the payload. Its simple logic can therefore be executed within a single pipeline of the Tofino programmable switch, to ensure wire-speed performance without the scalability issue. Being protocol-independent and operating in-network at wire speed make FlowShredder a practical and generic security service to protect the cloud traffic. In addition, FlowShredder can work with end-to-end encryption such as 0-RTT TLS (e.g., Quick UDP Internet Connections Protocol, QUIC) for enhanced protection, ideal for web browsing or real-time communications. We implement FlowShredder in Programming Protocol-Independent Packet Processors Language (P4) switches. Experiments in synthetic and real scenarios show that FlowShredder can effectively resist the traffic analysis attack with supervised learning techniques, and realize the wire-speed performance over a 100Gbps network while incurring minor overhead.
{"title":"A protocol-independent in-network security service for cloud applications","authors":"Bin Song , Bin Sun , Qiang Fu , Hao Li","doi":"10.1016/j.jnca.2025.104368","DOIUrl":"10.1016/j.jnca.2025.104368","url":null,"abstract":"<div><div>Cloud services are increasingly generating a large amount of Internet traffic. Much of it such as rich media and gaming traffic is not highly sensitive but prefers some protection. The traditional end-to-end encryption such as Transport Layer Security Protocol (TLS) is costly and has its own issues, such as increased latency, while the simple anonymity solutions cannot resist traffic analysis attacks. In this paper, we propose FlowShredder, a protocol-independent and in-network service to secure such traffic in the cloud. FlowShredder aims to break the association between the packets, the data flow, and the hosts by obfuscating the packet header (and some payload if needed). Without the context of the flow and the hosts, these packets are of little value to the adversary. The operation is carried out at cloud gateways, without encrypting the payload. Its simple logic can therefore be executed within a single pipeline of the Tofino programmable switch, to ensure wire-speed performance without the scalability issue. Being protocol-independent and operating in-network at wire speed make FlowShredder a practical and generic security service to protect the cloud traffic. In addition, FlowShredder can work with end-to-end encryption such as 0-RTT TLS (<em>e.g.</em>, Quick UDP Internet Connections Protocol, QUIC) for enhanced protection, ideal for web browsing or real-time communications. We implement FlowShredder in Programming Protocol-Independent Packet Processors Language (P4) switches. Experiments in synthetic and real scenarios show that FlowShredder can effectively resist the traffic analysis attack with supervised learning techniques, and realize the wire-speed performance over a 100Gbps network while incurring minor overhead.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104368"},"PeriodicalIF":8.0,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145364208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-20DOI: 10.1016/j.jnca.2025.104367
Junhao Li, Qiang Nong, Ziyu Liu
Vehicular Fog Computing (VFC) extends the fog computing paradigms to empower the Internet of Vehicles (IoV) by delivering ubiquitous computing and ultra-low latency-features critical to applications such as autonomous driving and collision avoidance. However, the dynamic and open nature of this architecture presents significant challenges in implementing robust security measures, ensuring the integrity of data, and safeguarding user privacy. Furthermore, most existing solutions fail to adequately prioritize the distinct requirements of safety-critical and non-safety-critical IoV services, thereby limiting their adaptability across heterogeneous application scenarios. Consequently, there is a growing need to develop flexible and resilient dynamic security mechanisms that optimize resource utilization in latency-sensitive and computationally intensive IoV systems. Additionally, IoVs systems must be equipped with defenses against evolving threats, including the emerging risk of quantum computing attacks. To address these challenges, this paper proposes a Quantum-resistant Blockchain-Assisted Generalized Signcryption (QBGS) protocol for vehicular fog computing. It synergizes post-quantum cryptography with adaptive trust orchestration, tailored specifically for next-generation IoV systems that require decentralized trust management and service-differentiated security. Unlike conventional static security methods, QBGS dynamically adjusts cryptographic operations such as encryption, signature, and signcryption to evolving environmental factors such as traffic density and threat severity. This enables context-aware security adjustments that enhance both efficiency and resilience. Moreover, QBGS incorporates a blockchain-integrated fog layer that supports lightweight protocols designed to curb the dissemination of false information. Through extensive theoretical analysis and systematic simulations based on an urban traffic case study, we demonstrate the practicality of QBGS for post-quantum secure IoV.
{"title":"A resilient fog-enabled IoV architecture: Adaptive post-quantum security framework with generalized signcryption and blockchain-enhanced trust management","authors":"Junhao Li, Qiang Nong, Ziyu Liu","doi":"10.1016/j.jnca.2025.104367","DOIUrl":"10.1016/j.jnca.2025.104367","url":null,"abstract":"<div><div>Vehicular Fog Computing (VFC) extends the fog computing paradigms to empower the Internet of Vehicles (IoV) by delivering ubiquitous computing and ultra-low latency-features critical to applications such as autonomous driving and collision avoidance. However, the dynamic and open nature of this architecture presents significant challenges in implementing robust security measures, ensuring the integrity of data, and safeguarding user privacy. Furthermore, most existing solutions fail to adequately prioritize the distinct requirements of safety-critical and non-safety-critical IoV services, thereby limiting their adaptability across heterogeneous application scenarios. Consequently, there is a growing need to develop flexible and resilient dynamic security mechanisms that optimize resource utilization in latency-sensitive and computationally intensive IoV systems. Additionally, IoVs systems must be equipped with defenses against evolving threats, including the emerging risk of quantum computing attacks. To address these challenges, this paper proposes a Quantum-resistant Blockchain-Assisted Generalized Signcryption (QBGS) protocol for vehicular fog computing. It synergizes post-quantum cryptography with adaptive trust orchestration, tailored specifically for next-generation IoV systems that require decentralized trust management and service-differentiated security. Unlike conventional static security methods, QBGS dynamically adjusts cryptographic operations such as encryption, signature, and signcryption to evolving environmental factors such as traffic density and threat severity. This enables context-aware security adjustments that enhance both efficiency and resilience. Moreover, QBGS incorporates a blockchain-integrated fog layer that supports lightweight protocols designed to curb the dissemination of false information. Through extensive theoretical analysis and systematic simulations based on an urban traffic case study, we demonstrate the practicality of QBGS for post-quantum secure IoV.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104367"},"PeriodicalIF":8.0,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145364128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-18DOI: 10.1016/j.jnca.2025.104365
Mu Liang , Chen Zhang , Tao Huang
Flexible Ethernet (FlexE) technology represents a groundbreaking solution for addressing diverse service requirements and network slicing demands in 5G networks, enabling high-bandwidth, low-latency, and efficient multi-service transmission. However, the current FlexE technology suffers from inefficient bandwidth adjustment, primarily due to its slow overhead insertion mechanism, particularly evident in metro transport networks (MTNs). This inefficiency not only prolongs service reconfiguration time but also leads to significant bandwidth resource wastage along end-to-end network paths. Furthermore, the latency overhead configuration necessitates substantial buffer capacity at network nodes to store pending data, imposing considerable storage pressure on network equipment. In this study, we propose an innovative overhead frame insertion mechanism that addresses these critical limitations while maintaining full compliance with FlexE standards. The proposed method features a streamlined overhead block structure that enables simultaneous and continuous transmission of all overhead information, significantly accelerating service-to-timeslot mapping and reducing link establishment time. Moreover, the proposed mechanism seamlessly integrates with the alignment marker insertion in Physical Coding Sublayer (PCS) and maintains full compatibility with IEEE 802.3 standard, simplifying overhead block extraction and data processing at the receiving end. Simulation results demonstrate that compared to existing FlexE technology, our solution achieves up to a 20-fold improvement in bandwidth adjustment time while substantially reducing buffer requirements and optimizing bandwidth utilization across the entire network infrastructure.
{"title":"Enhancement and optimization of FlexE technology within metro transport networks","authors":"Mu Liang , Chen Zhang , Tao Huang","doi":"10.1016/j.jnca.2025.104365","DOIUrl":"10.1016/j.jnca.2025.104365","url":null,"abstract":"<div><div>Flexible Ethernet (FlexE) technology represents a groundbreaking solution for addressing diverse service requirements and network slicing demands in 5G networks, enabling high-bandwidth, low-latency, and efficient multi-service transmission. However, the current FlexE technology suffers from inefficient bandwidth adjustment, primarily due to its slow overhead insertion mechanism, particularly evident in metro transport networks (MTNs). This inefficiency not only prolongs service reconfiguration time but also leads to significant bandwidth resource wastage along end-to-end network paths. Furthermore, the latency overhead configuration necessitates substantial buffer capacity at network nodes to store pending data, imposing considerable storage pressure on network equipment. In this study, we propose an innovative overhead frame insertion mechanism that addresses these critical limitations while maintaining full compliance with FlexE standards. The proposed method features a streamlined overhead block structure that enables simultaneous and continuous transmission of all overhead information, significantly accelerating service-to-timeslot mapping and reducing link establishment time. Moreover, the proposed mechanism seamlessly integrates with the alignment marker insertion in Physical Coding Sublayer (PCS) and maintains full compatibility with IEEE 802.3 standard, simplifying overhead block extraction and data processing at the receiving end. Simulation results demonstrate that compared to existing FlexE technology, our solution achieves up to a 20-fold improvement in bandwidth adjustment time while substantially reducing buffer requirements and optimizing bandwidth utilization across the entire network infrastructure.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104365"},"PeriodicalIF":8.0,"publicationDate":"2025-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145364131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}