城市地下管廊内布设了大量的管线,如燃气管道、网络通讯线路、电力线路等,由于地下环境复杂多变,存在着气体泄漏、爆炸、火灾等安全风险。针对这些问题,提出一种基于窄带物联网技术(Narrow Band Internet of Things,NB-IoT)的地下管廊...城市地下管廊内布设了大量的管线,如燃气管道、网络通讯线路、电力线路等,由于地下环境复杂多变,存在着气体泄漏、爆炸、火灾等安全风险。针对这些问题,提出一种基于窄带物联网技术(Narrow Band Internet of Things,NB-IoT)的地下管廊环境监测系统。该系统采用先进的传感器技术、NB-IoT技术、软件技术,系统主要分为数据采集模块、物联网云平台、远程监测系统三部分。数据采集模块以STM32作为主控单元连接各个传感器,采集温度、湿度、水位、可燃气体等数据,经过处理后利用NB-IoT网络上传到物联网云平台,远程监测系统调用物联网云平台的数据接口进行远程显示与预警。实验结果表明,系统在降低系统总体功耗的同时,能够实时、稳定地进行地下管廊环境监测,提前预防可能存在的风险。展开更多
随着物联网技术的飞速发展,窄带物联网(Narrow Band Internet of Things,NB-IoT)作为一种低功耗、广覆盖、大连接的无线通信技术,逐渐成为连接物理世界与数字世界的桥梁。然而,在实际应用中,NB-IoT信号面临着诸如信号衰减、干扰、覆盖...随着物联网技术的飞速发展,窄带物联网(Narrow Band Internet of Things,NB-IoT)作为一种低功耗、广覆盖、大连接的无线通信技术,逐渐成为连接物理世界与数字世界的桥梁。然而,在实际应用中,NB-IoT信号面临着诸如信号衰减、干扰、覆盖不均等挑战。这些挑战不仅影响用户体验,还限制了物联网应用的进一步发展。因此,研究面向物联网的NB-IoT信号优化方法具有重要意义。文章深入研究面向物联网的NB-IoT信号优化方法,提出多种有效的优化策略和技术手段。展开更多
The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the d...The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device itself.Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features.This paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in homes.We have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT devices.Our system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing devices.We have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache server.The feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time settings.It is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation systems.Additionally,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber threats.The trial results support the proposed system and demonstrate its potential for use in everyday life.展开更多
The rapid adoption of the Internet of Things(IoT)across industries has revolutionized daily life by providing essential services and leisure activities.However,the inadequate software protection in IoT devices exposes...The rapid adoption of the Internet of Things(IoT)across industries has revolutionized daily life by providing essential services and leisure activities.However,the inadequate software protection in IoT devices exposes them to cyberattacks with severe consequences.Intrusion Detection Systems(IDS)are vital in mitigating these risks by detecting abnormal network behavior and monitoring safe network traffic.The security research community has shown particular interest in leveraging Machine Learning(ML)approaches to develop practical IDS applications for general cyber networks and IoT environments.However,most available datasets related to Industrial IoT suffer from imbalanced class distributions.This study proposes a methodology that involves dataset preprocessing,including data cleaning,encoding,and normalization.The class imbalance is addressed by employing the Synthetic Minority Oversampling Technique(SMOTE)and performing feature reduction using correlation analysis.Multiple ML classifiers,including Logistic Regression,multi-layer perceptron,Decision Trees,Random Forest,and XGBoost,are employed to model IoT attacks.The effectiveness and robustness of the proposed method evaluate using the IoTID20 dataset,which represents current imbalanced IoT scenarios.The results highlight that the XGBoost model,integrated with SMOTE,achieves outstanding attack detection accuracy of 0.99 in binary classification,0.99 in multi-class classification,and 0.81 in multiple sub-classifications.These findings demonstrate our approach’s significant improvements to attack detection in imbalanced IoT datasets,establishing its superiority over existing IDS frameworks.展开更多
基于物联大数据赋能的业务流程能够更快更准地感知物理世界并及时做出响应的需求突现,提出一种物联网(Internet of Things,IoT)感知的业务微流程建模方法。首先,以单个IoT对象为中心建模,融合MAPE-K(monitor,analysis,plan,execution an...基于物联大数据赋能的业务流程能够更快更准地感知物理世界并及时做出响应的需求突现,提出一种物联网(Internet of Things,IoT)感知的业务微流程建模方法。首先,以单个IoT对象为中心建模,融合MAPE-K(monitor,analysis,plan,execution and knowledge base,MAPE-K)模型思想,将IoT对象实例生命周期的行为状态与微流程实例状态一一映射,实现对单个IoT对象的环形自动监控和调节;其次,基于从IoT传感设备获取的数据,定义基于SASE+语言的业务规则,提取对业务流程有意义的业务事件,避免了无关事件对宏流程的干扰;最后,通过设计一个微流程建模工具原型系统,结合真实案例分析,验证了提出建模方法的有效性,实现了业务流程与IoT实时流式感知数据的结合,并显著减少了宏流程需要处理的业务事件数量。展开更多
由于地址跳变是物联网主动防御的一种有效手段,但因跳变资源匮乏、可预见性以及数据包混淆度低已经成为制约物联网地址跳变的主要问题。为此,提出一种基于双模式端址跳变的主动防御方法。该方法设计了双模式端址选择算法,通过动态确定...由于地址跳变是物联网主动防御的一种有效手段,但因跳变资源匮乏、可预见性以及数据包混淆度低已经成为制约物联网地址跳变的主要问题。为此,提出一种基于双模式端址跳变的主动防御方法。该方法设计了双模式端址选择算法,通过动态确定虚拟端址生成策略,以通信时间为阈值,扩大端址跳变空间,从而解决地址池资源受限问题。同时,还构建了双虚拟端址跳变方法,通过动态分配和同步虚拟接收和发送地址,提升数据包混淆度,增强跳变的不可预见性。并且基于SDN(Software Defined Network)设计了流表双向同步机制,实现流表的动态下发和同步,以保证端址跳变的一致性。实验结果表明,该方法能有效提升地址跳变的多样性和不可预测性,显著增强抵御嗅探攻击的能力。展开更多
Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the...Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the effectiveness of migratory phototropic pest control. However, since the SIL is connected to the Internet, it is vulnerable to various security issues.These issues can lead to serious consequences, such as tampering with the parameters of SIL, illegally starting and stopping SIL,etc. In this paper, we describe the overall security requirements of SIL-IoT and present an extensive survey of security and privacy solutions for SIL-IoT. We investigate the background and logical architecture of SIL-IoT, discuss SIL-IoT security scenarios, and analyze potential attacks. Starting from the security requirements of SIL-IoT we divide them into six categories, namely privacy, authentication, confidentiality, access control, availability,and integrity. Next, we describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions. Based on the current survey, we finally discuss the challenges and future research directions of SIL-IoT.展开更多
文摘城市地下管廊内布设了大量的管线,如燃气管道、网络通讯线路、电力线路等,由于地下环境复杂多变,存在着气体泄漏、爆炸、火灾等安全风险。针对这些问题,提出一种基于窄带物联网技术(Narrow Band Internet of Things,NB-IoT)的地下管廊环境监测系统。该系统采用先进的传感器技术、NB-IoT技术、软件技术,系统主要分为数据采集模块、物联网云平台、远程监测系统三部分。数据采集模块以STM32作为主控单元连接各个传感器,采集温度、湿度、水位、可燃气体等数据,经过处理后利用NB-IoT网络上传到物联网云平台,远程监测系统调用物联网云平台的数据接口进行远程显示与预警。实验结果表明,系统在降低系统总体功耗的同时,能够实时、稳定地进行地下管廊环境监测,提前预防可能存在的风险。
文摘随着物联网技术的飞速发展,窄带物联网(Narrow Band Internet of Things,NB-IoT)作为一种低功耗、广覆盖、大连接的无线通信技术,逐渐成为连接物理世界与数字世界的桥梁。然而,在实际应用中,NB-IoT信号面临着诸如信号衰减、干扰、覆盖不均等挑战。这些挑战不仅影响用户体验,还限制了物联网应用的进一步发展。因此,研究面向物联网的NB-IoT信号优化方法具有重要意义。文章深入研究面向物联网的NB-IoT信号优化方法,提出多种有效的优化策略和技术手段。
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2024R333)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device itself.Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features.This paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in homes.We have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT devices.Our system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing devices.We have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache server.The feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time settings.It is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation systems.Additionally,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber threats.The trial results support the proposed system and demonstrate its potential for use in everyday life.
文摘The rapid adoption of the Internet of Things(IoT)across industries has revolutionized daily life by providing essential services and leisure activities.However,the inadequate software protection in IoT devices exposes them to cyberattacks with severe consequences.Intrusion Detection Systems(IDS)are vital in mitigating these risks by detecting abnormal network behavior and monitoring safe network traffic.The security research community has shown particular interest in leveraging Machine Learning(ML)approaches to develop practical IDS applications for general cyber networks and IoT environments.However,most available datasets related to Industrial IoT suffer from imbalanced class distributions.This study proposes a methodology that involves dataset preprocessing,including data cleaning,encoding,and normalization.The class imbalance is addressed by employing the Synthetic Minority Oversampling Technique(SMOTE)and performing feature reduction using correlation analysis.Multiple ML classifiers,including Logistic Regression,multi-layer perceptron,Decision Trees,Random Forest,and XGBoost,are employed to model IoT attacks.The effectiveness and robustness of the proposed method evaluate using the IoTID20 dataset,which represents current imbalanced IoT scenarios.The results highlight that the XGBoost model,integrated with SMOTE,achieves outstanding attack detection accuracy of 0.99 in binary classification,0.99 in multi-class classification,and 0.81 in multiple sub-classifications.These findings demonstrate our approach’s significant improvements to attack detection in imbalanced IoT datasets,establishing its superiority over existing IDS frameworks.
文摘基于物联大数据赋能的业务流程能够更快更准地感知物理世界并及时做出响应的需求突现,提出一种物联网(Internet of Things,IoT)感知的业务微流程建模方法。首先,以单个IoT对象为中心建模,融合MAPE-K(monitor,analysis,plan,execution and knowledge base,MAPE-K)模型思想,将IoT对象实例生命周期的行为状态与微流程实例状态一一映射,实现对单个IoT对象的环形自动监控和调节;其次,基于从IoT传感设备获取的数据,定义基于SASE+语言的业务规则,提取对业务流程有意义的业务事件,避免了无关事件对宏流程的干扰;最后,通过设计一个微流程建模工具原型系统,结合真实案例分析,验证了提出建模方法的有效性,实现了业务流程与IoT实时流式感知数据的结合,并显著减少了宏流程需要处理的业务事件数量。
文摘由于地址跳变是物联网主动防御的一种有效手段,但因跳变资源匮乏、可预见性以及数据包混淆度低已经成为制约物联网地址跳变的主要问题。为此,提出一种基于双模式端址跳变的主动防御方法。该方法设计了双模式端址选择算法,通过动态确定虚拟端址生成策略,以通信时间为阈值,扩大端址跳变空间,从而解决地址池资源受限问题。同时,还构建了双虚拟端址跳变方法,通过动态分配和同步虚拟接收和发送地址,提升数据包混淆度,增强跳变的不可预见性。并且基于SDN(Software Defined Network)设计了流表双向同步机制,实现流表的动态下发和同步,以保证端址跳变的一致性。实验结果表明,该方法能有效提升地址跳变的多样性和不可预测性,显著增强抵御嗅探攻击的能力。
基金supported in part by the National Natural Science Foundation of China (62072248, 62072247)the Jiangsu Agriculture Science and Technology Innovation Fund (CX(21)3060)。
文摘Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the effectiveness of migratory phototropic pest control. However, since the SIL is connected to the Internet, it is vulnerable to various security issues.These issues can lead to serious consequences, such as tampering with the parameters of SIL, illegally starting and stopping SIL,etc. In this paper, we describe the overall security requirements of SIL-IoT and present an extensive survey of security and privacy solutions for SIL-IoT. We investigate the background and logical architecture of SIL-IoT, discuss SIL-IoT security scenarios, and analyze potential attacks. Starting from the security requirements of SIL-IoT we divide them into six categories, namely privacy, authentication, confidentiality, access control, availability,and integrity. Next, we describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions. Based on the current survey, we finally discuss the challenges and future research directions of SIL-IoT.
