The widespread adoption of blockchain technology has led to the exploration of its numerous applications in various fields.Cryptographic algorithms and smart contracts are critical components of blockchain security.De...The widespread adoption of blockchain technology has led to the exploration of its numerous applications in various fields.Cryptographic algorithms and smart contracts are critical components of blockchain security.Despite the benefits of virtual currency,vulnerabilities in smart contracts have resulted in substantial losses to users.While researchers have identified these vulnerabilities and developed tools for detecting them,the accuracy of these tools is still far from satisfactory,with high false positive and false negative rates.In this paper,we propose a new method for detecting vulnerabilities in smart contracts using the BERT pre-training model,which can quickly and effectively process and detect smart contracts.More specifically,we preprocess and make symbol substitution in the contract,which can make the pre-training model better obtain contract features.We evaluate our method on four datasets and compare its performance with other deep learning models and vulnerability detection tools,demonstrating its superior accuracy.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
Dear Editor,This letter presents a novel and efficient adversarial robustness verification method for tree-based smart grid dynamic security assessment(DSA).Based on tree algorithms technique,the data-driven smart gri...Dear Editor,This letter presents a novel and efficient adversarial robustness verification method for tree-based smart grid dynamic security assessment(DSA).Based on tree algorithms technique,the data-driven smart grid DSA has received significant research interests in recent years.展开更多
A novel multispectral smart window has been proposed,which features dynamic modulation of light transmittance and effective shielding against electromagnetic microwave radiation.This design integrates liquid crystal d...A novel multispectral smart window has been proposed,which features dynamic modulation of light transmittance and effective shielding against electromagnetic microwave radiation.This design integrates liquid crystal dynamic scattering and dye doping techniques,enabling the dual regulation of transmittance and scattering within a singlelayer smart window.Additionally,the precise control of conductive film thickness ensures the attainment of robust microwave signal shielding.We present a theoretical model for ion movement in the presence of an alternating electric field,along with a novel approach to manipulate negative dielectric constant.The proposed model successfully enables a rapid transition between light transparent,absorbing and haze states,with an optimum drive frequency adjustable to approximately 300 Hz.Furthermore,the resistive design of the conductive layer effectively mitigates microwave radiation within the 2−18 GHz range.These findings offer an innovative perspective for future advancements in environmental construction.展开更多
基金supported by the National Key Research and Development Plan in China(Grant No.2020YFB1005500)。
文摘The widespread adoption of blockchain technology has led to the exploration of its numerous applications in various fields.Cryptographic algorithms and smart contracts are critical components of blockchain security.Despite the benefits of virtual currency,vulnerabilities in smart contracts have resulted in substantial losses to users.While researchers have identified these vulnerabilities and developed tools for detecting them,the accuracy of these tools is still far from satisfactory,with high false positive and false negative rates.In this paper,we propose a new method for detecting vulnerabilities in smart contracts using the BERT pre-training model,which can quickly and effectively process and detect smart contracts.More specifically,we preprocess and make symbol substitution in the contract,which can make the pre-training model better obtain contract features.We evaluate our method on four datasets and compare its performance with other deep learning models and vulnerability detection tools,demonstrating its superior accuracy.
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.
基金supported in part by the Internal Talent Award with Wallenberg-NTU Presidential Postdoctoral Fellowship 2022the National Research Foundation,Singapore and DSO National Laboratories under the AI Singapore Program(AISG2-RP-2020-019)+1 种基金the Joint SDU-NTU Centre for AI Research(C-FAIR),the RIE 2020 Advanced Manufacturing and Engineering(AME)Programmatic Fund,Singapore(A20G8b0102)NOE Tier 1 Projects(RG59/22&RT9/22)。
文摘Dear Editor,This letter presents a novel and efficient adversarial robustness verification method for tree-based smart grid dynamic security assessment(DSA).Based on tree algorithms technique,the data-driven smart grid DSA has received significant research interests in recent years.
基金the financial supports from the National Key Research and Development Program of China(Grant No.2023YFB3811600)the National Science Fund for Distinguished Young Scholars(Grant No.51625201)+6 种基金State Key Program of National Natural Science of China(Grant No.52032004)National Youth Science Funds of China(Grant No.52102039)Key Research and Development Program of Heilongjiang Province(Grant No.GA21D001,2022ZX06C05)the Fundamental Research Funds for the Central Universities(Grant No.HIT.OCEF.2022011)the Major Program of Harbin Institute of Technology(Grant NO.2023FRFK01002)the Fundamental Research Funds for the Central Universities(2022FRFK060026)the National Youth Science Funds of China(Grant No.52302172).
文摘A novel multispectral smart window has been proposed,which features dynamic modulation of light transmittance and effective shielding against electromagnetic microwave radiation.This design integrates liquid crystal dynamic scattering and dye doping techniques,enabling the dual regulation of transmittance and scattering within a singlelayer smart window.Additionally,the precise control of conductive film thickness ensures the attainment of robust microwave signal shielding.We present a theoretical model for ion movement in the presence of an alternating electric field,along with a novel approach to manipulate negative dielectric constant.The proposed model successfully enables a rapid transition between light transparent,absorbing and haze states,with an optimum drive frequency adjustable to approximately 300 Hz.Furthermore,the resistive design of the conductive layer effectively mitigates microwave radiation within the 2−18 GHz range.These findings offer an innovative perspective for future advancements in environmental construction.
