Ad Hoc Networks最新文献_第5页

A survey on security of UAV and deep reinforcement learning 无人机安全与深度强化学习调查

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2024-08-30 DOI: 10.1016/j.adhoc.2024.103642

{"title":"A survey on security of UAV and deep reinforcement learning","authors":"","doi":"10.1016/j.adhoc.2024.103642","DOIUrl":"10.1016/j.adhoc.2024.103642","url":null,"abstract":"<div><p>Recently, the use of unmanned aerial vehicles (UAV)s for accomplishing various tasks has gained a significant interest from both civilian and military organizations due to their adaptive, autonomous, and flexibility nature in different environments. The characteristics of UAV systems introduce new threats from which cyber attacks may benefit. Adaptive security solutions for UAVs are required to counter the growing threat surface. The security of UAV systems has therefore become one of the fastest growing research topics. Machine learning based security mechanisms have a potential to provide effective countermeasures that complement traditional security mechanisms. The main motivation of this survey is to the lack of a comprehensive literature review about reinforcement learning based security solutions for UAV systems. In this paper, we present a comprehensive review on the security of UAV systems focusing on deep-reinforcement learning-based security solutions. We present a general architecture of an UAV system that includes communication systems to show potential sources of vulnerabilities. Then, the threat surface of UAV systems is explored. We explain attacks on UAV systems according to the threats in a systematic way. In addition, we present countermeasures in the literature for each attack on UAVs. Furthermore, traditional defense mechanisms are explained to highlight requirements for reinforcement based security solutions on UAVs. Next, we present the main reinforcement algorithms. We examine security solutions with reinforcement learning algorithms and their limitations in a holistic approach. We also identify research challenges about reinforcement based security solutions on UAVs. Briefly, this survey provides key guidelines on UAV systems, threats, attacks, reinforcement learning algorithms, the security of UAV systems, and research challenges.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142096624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FIDWATCH: Federated incremental distillation for continuous monitoring of IoT security threats FIDWATCH：用于持续监控物联网安全威胁的联合增量提炼技术

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2024-08-27 DOI: 10.1016/j.adhoc.2024.103637

{"title":"FIDWATCH: Federated incremental distillation for continuous monitoring of IoT security threats","authors":"","doi":"10.1016/j.adhoc.2024.103637","DOIUrl":"10.1016/j.adhoc.2024.103637","url":null,"abstract":"<div><p>The fast evolutions of Internet of Things (IoT) technologies have been accelerating their applicability in different sectors of life and becoming a pillar for sustainable development. However, this revolutionary expansion led to a substantial increase in attack surface, raising many concerns about security threats and their possible consequences. Machine learning has significantly contributed to designing intrusion detection systems (IDS) but suffers from critical limitations such as data privacy and sovereignty, data imbalance, concept drift, and catastrophic forgetting. This collectively makes existing IDSs an improper choice for securing IoT environments. This paper presents a federated learning approach called FIDWATCH to continuously monitor and detect a broad range of IoT security threats. The local side of FIDWATCH introduces contrastive focal loss to enhance the ability of the local model (teacher) to discriminate between diverse types of IoT security threats while putting an increased emphasis on hard-to-classify samples. A fine-grained Knowledge Distillation (KD) is introduced to allow the client to distill the required teacher's knowledge into a lighter, more compact model termed the pupil model. This greatly assists the competence and flexibility of the model in resource-constrained scenarios. Furthermore, an adaptive incremental updating method is introduced in FIDWATCH to allow the global model to exploit the distilled knowledge and refine the shared dataset. This helps generate global anchors for improving the robustness of the mode against the distributional shift, thereby improving model alignment and compliance with the dynamics of IoT security threats. Proof-of-concept simulations are performed on data from two public datasets (BoT-IoT and ToN-IoT), demonstrating the superiority of FIDWATCH over cutting-edge performance with an average f1-score of 97.07% and 95.63%, respectively.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142129049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Shared secret key extraction from atmospheric optical wireless channels with multi-scale information reconciliation 利用多尺度信息调和从大气光学无线信道中提取共享密钥

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2024-08-26 DOI: 10.1016/j.adhoc.2024.103638

{"title":"Shared secret key extraction from atmospheric optical wireless channels with multi-scale information reconciliation","authors":"","doi":"10.1016/j.adhoc.2024.103638","DOIUrl":"10.1016/j.adhoc.2024.103638","url":null,"abstract":"<div><p>Due to the impact of turbulence, atmospheric optical wireless channel exhibits characteristics such as time-varying, space-varying and natural randomness, which can be used as a common natural random source for shared secret key extraction. Wireless laser communication technology boasts advantages like high bandwidth and fast transmission, which is conducive to improving key generation rate. Additionally, the strong anti-interference of laser signal helps to reduce key disagreement rate. Moreover, the laser beam’s good directionality effectively decreases the risk of eavesdropping on key information. Given its advantages and a scarcity of research in this regard, this paper proposes a scheme of shared secret key extraction from atmospheric optical wireless channels with multi-scale information reconciliation. In the scheme, to increase the cross-correlation coefficient of signal samples at the two legitimate parties, a preprocessing algorithm is designed based on a denoising algorithm and a threshold-based outliers elimination algorithm, and the denoising algorithm is inspired by the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDan); moreover, a multi-level quantization algorithm based on Equilibrium-Optimizer(EO) is developed to balance and optimize distribution of sample points in the sample space; furthermore, to simplify the process of and decrease the computational complexity of information reconciliation, a concept of a multi-scale information reconciliation is formed, on the basis of which three algorithms, B-MSIR, I-MSIR and C-MSIR, are formulated. Finally, its performance is verified by numerical simulations and experiments, and the results show it has better performance in terms of the key disagreement rate, the key generation rate and the key randomness compared with several state-of-the-art algorithms.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142088660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mobility-aware parallel offloading and resource allocation scheme for vehicular edge computing 面向车载边缘计算的移动感知并行卸载和资源分配方案

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2024-08-26 DOI: 10.1016/j.adhoc.2024.103639

{"title":"Mobility-aware parallel offloading and resource allocation scheme for vehicular edge computing","authors":"","doi":"10.1016/j.adhoc.2024.103639","DOIUrl":"10.1016/j.adhoc.2024.103639","url":null,"abstract":"<div><p>Vehicle edge computing (VEC) enhances the distributed task processing capability within intelligent vehicle-infrastructure cooperative systems (i-VICS) by deploying servers at the network edge. However, the proliferation of onboard sensors and the continual emergence of new applications have exacerbated the inadequacy of wireless spectrum resources and edge server resources, while the high mobility of vehicles reduces reliability in task processing, resulting in increased communication and task processing delays. To address these challenges, we propose a mobile-aware Many-to-Many Parallel (MTMP) offloading scheme that integrates: a) millimeter-wave (mmWave) and cellular vehicle-to-everything (C-V2X) to mitigate excessive communication delays; and b) leveraging the underutilized resources of surrounding vehicles and parallel offloading to mitigate excessive task processing delays. To minimize the average completion delay of all tasks, this paper formulates the objective as a min-max optimization problem and solves it using the maximum entropy method (MEM), the Lagrange multiplier method, and an iterative algorithm. Extensive experimental results demonstrate the superior performance of the proposed scheme in comparison with other baseline algorithms. Specifically, our proposal achieves a 47 % reduction in task completion delay under optimal conditions, a 31.3 % increase in task completion rate, and a 30 % decrease in program runtime compared to the worst-performing algorithm.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142096630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mixed fragmentation technique for securing structured data using multi-cloud environment (MFT-SSD) 利用多云环境确保结构化数据安全的混合分片技术（MFT-SSD）

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2024-08-22 DOI: 10.1016/j.adhoc.2024.103625

引用次数: 0

An edge computing and distributed ledger technology architecture for secure and efficient transportation 用于安全高效运输的边缘计算和分布式账本技术架构

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2024-08-22 DOI: 10.1016/j.adhoc.2024.103633

{"title":"An edge computing and distributed ledger technology architecture for secure and efficient transportation","authors":"","doi":"10.1016/j.adhoc.2024.103633","DOIUrl":"10.1016/j.adhoc.2024.103633","url":null,"abstract":"<div><p>Intelligent Transportation Systems (ITS) faces significant challenges in achieving its goal of sustainable and efficient transportation. These challenges include real-time data processing bottlenecks caused by high communication latency and security vulnerabilities related to centralized data storage. We propose a novel architecture that leverages Edge Computing and Distributed Ledger Technology (DLT) to address these concerns. Edge computing pushes cloud services, such as vehicles and roadside units, closer to the data source. This strategy reduces latency and network congestion. DLT provides a secure, decentralized platform for storing and sharing ITS data. Its tamper-proof nature ensures data integrity and prevents unauthorized access. Our architecture utilizes these technologies to create a decentralized platform for ITS data management. This platform facilitates secure processing, storage, and data exchange from various sources in the transportation network. This paper delves deeper into the architecture, explaining its essential components and functionalities. Additionally, we explore its potential applications and benefits for ITS. We describe a case study focusing on a data marketplace system for connected vehicles to assess the architecture’s effectiveness. The simulation results show an average latency reduction of 83.35% for publishing and 87.57% for purchasing datasets compared to the cloud architecture. Additionally, transaction processing speed improved by 18.73% and network usage decreased by 96.67%. The proposed architecture also achieves up to 99.61% reduction in mining centralization.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142088657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel differentiated coverage-based lifetime metric for wireless sensor networks 基于覆盖范围的新型无线传感器网络寿命指标

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2024-08-22 DOI: 10.1016/j.adhoc.2024.103636

{"title":"A novel differentiated coverage-based lifetime metric for wireless sensor networks","authors":"","doi":"10.1016/j.adhoc.2024.103636","DOIUrl":"10.1016/j.adhoc.2024.103636","url":null,"abstract":"<div><p>This paper delves into optimizing network lifetime (NL) subject to connected-coverage requirement, a pivotal issue for realistic wireless sensor network (WSN) design. A key challenge in designing WSNs consisting of energy-limited sensors is maximizing NL, the time a network remains functional by providing the desired service quality. To this end, we introduce a novel NL metric addressing target-specific coverage requirements that remedies the shortcomings imposed by conventional definitions like <em>first node die</em> (FND) and <em>last node die</em> (LND). In this context, while we want targets to be sensed by multiple sensors for a portion of the network lifetime, we let the periods, during which cells are monitored by at least one sensor, vary. We also allow the ratios of multiple and single tracking times to differ depending on the target and incorporate target-based prioritization in coverage. Moreover, we address role assignment to sensors and propose a selective target-sensor assignment strategy. As such, we aim to reduce redundant data transmissions and hence overall energy consumption in WSNs. We first propose a unique 0-1 mixed integer programming (MIP) model, to analyze the impact of our proposal on optimal WSN performance, precisely. Next, we present comprehensive comparative studies of WSN performance for alternative NL metrics regarding different coverage requirements and priorities across a wide range of parameters. Our test results reveal that by utilizing our novel NL metric total coverage time can be improved significantly, while facilitating more reliable sensing of the target region.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142084098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy minimization for IRS-and-UAV-assisted mobile edge computing 最小化 IRS 和无人机辅助移动边缘计算的能耗

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2024-08-20 DOI: 10.1016/j.adhoc.2024.103635

{"title":"Energy minimization for IRS-and-UAV-assisted mobile edge computing","authors":"","doi":"10.1016/j.adhoc.2024.103635","DOIUrl":"10.1016/j.adhoc.2024.103635","url":null,"abstract":"<div><p>Intelligent reconfigurable surface (IRS) is an emerging technology for the enhancement of spectrum and energy efficiency. We propose a novel IRS-and-unmanned aerial vehicle (UAV)-Assisted mobile edge computing (MEC) framework, where a MEC server installing on an UAV to facilitate task calculations by mobile users (MUs), and an IRS modulates channels between MUs and the UAV. Non-orthogonal multiple access (NOMA) is employed for further improving system-wide spectral efficiency. There are needs for joint optimization of multiple parameters, e.g., the task partition parameters and the transmit power of all MUs, the reflection coefficient matrix of the IRS and the movement trajectory of the UAV, and such needs raises the challenge of minimizing the long-term total energy consumption of all MUs while satisfying required transmission rate and task completion delay. We divide optimization tasks into two sub-problems and propose specific solutions respectively, i.e., relevant decisions about the UAV and MUs to be solved by deep reinforcement learning (DRL); and the reflection coefficient matrix of the IRS to be solved by block coordinate descent (BCD). A series of experiments have verified the effectiveness of the proposed communication techniques and optimization algorithms. Simulation results demonstrate that (1) NOMA-IRS technique achieves better energy efficacy compared to the cases where random IRS or no IRS is deployed and the conventional orthogonal multiple access (OMA) technique with IRS. (2) our proposed deep deterministic policy gradient (DDPG)-BCD algorithm outperforms other four benchmark algorithms in solving the complex and dynamic optimization problem.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Systematic survey on artificial intelligence based mobile crowd sensing and sourcing solutions: Applications and security challenges 基于人工智能的移动人群感知和来源解决方案的系统调查：应用和安全挑战

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2024-08-20 DOI: 10.1016/j.adhoc.2024.103634

{"title":"Systematic survey on artificial intelligence based mobile crowd sensing and sourcing solutions: Applications and security challenges","authors":"","doi":"10.1016/j.adhoc.2024.103634","DOIUrl":"10.1016/j.adhoc.2024.103634","url":null,"abstract":"<div><p>Mobile Crowd Sensing/Souring (MCS) is a novel sensing approach that leverages the collective participation of users and their mobile devices to collect sensing data. As large volumes of data get stored and processed by the MCS platform, Artificial Intelligence (AI) techniques are being deployed to make informed decisions that help optimize the system performance. Despite their effectiveness in solving many of the challenges, incorporating AI models in the system introduces many concerns, which could adversely affect its performance. This includes exploiting the vulnerabilities of the models by an adversary to manipulate the data and cause harm to the system. Adversarial Machine Learning (AML) is a field of research that studies attacks and defences against machine learning models. In this study, we conduct a systematic literature review to comprehensively analyze state-of-the-art works that address various aspects of AI-based MCS systems. The review focuses mainly on the applications of AI in different components of MCS, including task allocation and data aggregation, to improve its performance and enhance its security. This work also proposes a novel classification framework that can be adapted to compare works in this domain. This framework can help study AML in the context of MCS, as it facilitates identifying the attack surfaces that adversaries can exploit, and hence highlights the potential vulnerabilities of AI-based MCS systems to adversarial attacks, motivating future research to focus on designing resilient systems.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142049635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

APPS: Authentication-enabled privacy protection scheme for secure data transfer in Internet of Things APPS：面向物联网安全数据传输的认证式隐私保护方案

IF 4.4 3区计算机科学

Ad Hoc Networks Pub Date : 2024-08-14 DOI: 10.1016/j.adhoc.2024.103631

{"title":"APPS: Authentication-enabled privacy protection scheme for secure data transfer in Internet of Things","authors":"","doi":"10.1016/j.adhoc.2024.103631","DOIUrl":"10.1016/j.adhoc.2024.103631","url":null,"abstract":"<div><p>The Internet of Things (IoT) is an emerging field that encompasses several heterogeneous devices and smart objects that are integrated with the network. In open platforms, these objects are deployed to present advanced services in numerous applications. Innumerable security-sensitive data is generated by the IoT device and therefore, the security of these devices is an important task. This work formulates a secure data transfer technique in IoT, named Authentication enabled Privacy Protection (APPS) scheme for resource-constrained IoT devices. The proposed scheme demonstrates resilience against various attacks; such as resisting reply attacks, device anonymity, untracebility, session key establishment, quantum attacks and resisting MITM attacks. For the privacy protection scheme, the secured data transfer is initiated between the entities, like IoT devices, servers, and registration centers, by using various phases, namely registration phase, key generation phase, data encryption, authentication, verification, and data retrieval phase. Here, a mathematical model is designed for protecting data privacy using hashing, encryption, secret keys, etc. Finally, performance of proposed APPS model is analyzed; wherein the outcomes reveal that the proposed APPS model attained the maximum detection rate of 0.85, minimal memory usage of 0.497MB, and minimal computational time of 112. 79 sec and minimal turnaround time 131.91 sec.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142077504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0