Biblio

As edge computing has been widely used in IoT (Internet of Things) systems, the security has become one of important issues for IoT. Because of a large amount of private information stored in edge computing devices, it makes edge computing devices attractive to various kinds attacks. To deal with this challenge, this paper proposes a security awareness scheme for edge computing devices in IoT system. Test results show that the proposed approach can improve services-oriented security situation of IoT systems based on edge computing.

Supply chain management systems (SCM) are the most intensive and statistical RFID application for object tracking. A lot of research has been carried out to overcome security issues in the field of online/offline object tracking as well as authentication protocols involving RFID technology. Due to advancements with the Internet of Things (IoT) and embedded systems in object tracking schemes the latest research manages to deliver information about the object’s location as well as provide particulars about the state of an object. Recent research presented a proposal for an authentication and online object tracking protocol focusing on solutions for privacy issues for device identification, end-to-end authentication, and secure online object tracking. However, recent schemes have been found to be vulnerable to traceability attacks. This paper presents an enhanced end-to-end authentication scheme where the identity of the user is kept anonymous so that its actions can not be tracked, eliminating attacks related to traceability. The security of the proposed protocol is formally analyzed using the attack model of the automated security testing tool, ProVerif. The proposed scheme outperforms competing schemes based on security.

As the rapid development of information technology and networks, there have been several new challenges to data security. For security needs in the process of data transmission and storage, the data security protection mechanism based on SM algorithm is studied. In addition, data cryptographic security protection system model composed of cryptographic infrastructure, cryptographic service nodes and cryptographic modules is proposed. As the core of the mechanism, SM algorithm not only brings about efficient data encryption and decryption, but ensures the security, integrity and non-repudiation of data transmission and storage. Secure and controllable key management is implemented by this model, which provides easy-to-expandable cryptographic services, and brings efficient cryptographic capabilities applicable for multiple scenarios.

This study focuses on the behavior of magnetic properties and electromagnetic absorption of MgFe2O4 prepared by powder metallurgy. Magnesium ferrite was synthesized using oxide precursors (MgO and Fe2 O3). The samples were calcined at 700 °C for 3 hours and sintered at 1100 °C for 24 hours with varying compaction pressure (80 kg/cm2, 90 kg/cm2, 100 kg/cm2). Magnesium ferrites were characterized using an X-Ray Diffraction (XRD) for their crystal structure analysis, a Scanning Electron Microscope equipped with an Energy Dispersive Spectroscopy (SEM-EDS) for their microstructure and elemental composition studies, a Permagraph for their magnetic properties, and a Vector Network Analysis (VNA) for their microwave absorption characteristics. XRD patterns shows primary phase of MgFe2O4 and secondary phase of Fe2 O3 present in all three samples. The SEM characterization reveal the microstructure of magnesium ferrite and the EDS spectra confirm the presence of Fe, Mg, and O. The hysteresis curves show that the values of remanence magnetic induction (Br) are 17.5 emu/g, 16.5 emu/g, and 14.5 emu/g, respective to the increasing compaction pressure. Saturation magnetization values are increasing whereas the coercivity values are found to have inconsistent change with increasing compaction pressure. According to VNA results, the values of reflection loss are -16.15 dB, -22.45 dB, and -27.55 dB, respectively.

The circulating current in the D-winding may cause primary current waveform distortion, and the reliability of the restraint criterion based on the typical magnetizing inrush current characteristics will be affected. The magnetizing inrush current with typical characteristics is the sum of primary current and circulating current. Using the circulating current to compensate the primary current can improve the reliability of the differential protection. When the phase is not saturated, the magnetizing inrush current is about zero. Therefore, the primary current of unsaturated phase can be replaced by the opposite of the circulating current. Based on this, an engineering practical calculation method for circulating current is proposed. In the method, the segmented primary currents are used to replace the circulating current. Phasor analysis is used to demonstrate the application effect of this method when remanence coefficients are different. The method is simple and practical, and has strong applicability and high reliability. Simulation and recorded waveforms have verified the effectiveness of the method.

Aiming at the fact that the existing feature quantities cannot well identify the magnetizing inrush current during remanence and bias and the huge number of feature quantities, a new identification method using empirical mode decomposition energy index and artificial intelligence algorithm is proposed in 'this paper. Decomposition and denoising are realized through empirical mode decomposition, and then the corresponding energy index is obtained for the waveform of each inherent modal component and simplified by the mean impact value method. Finally, the accuracy of prediction using artificial intelligence algorithm is close to 100%. This reflects the practicality of the method proposed in 'this article.

In recent years, there have been situations in which the zero-sequence protection of the transformer has been incorrectly operated due to the converter transformer energizing or fault recovery. For converter transformers, maloperation may also occur. However, there is almost no theoretical research on the zero-mode inrush currents of converter transformers. This paper studies the characteristics of the zero-mode inrush currents of the converter transformers, including the relationship between the amplitude and attenuation characteristics of the zero-mode inrush currents of converter transformers, and their relationship with the system resistance, remanence, and closing angle. First, based on the T-type equivalent circuit of the transformer, the equivalent circuit of the zero-mode inrush current of each transformer is obtained. On this basis, the amplitude relationship of the zero-mode inrush currents of different converter transformers is obtained: the zero-mode inrush current of the energizing pole YY transformer becomes larger than the YD transformer, the energized pole YD becomes greater than the YY transformer, and the YY transformer zero-mode inrush current rises from 0. It is also analyzed that the sympathetic interaction will make the attenuation of the converter transformer zero-mode inrush current slower. The system resistance mainly affects the initial attenuation speed, and the later attenuation speed is mainly determined by the converter transformer leakage reactance. Finally, PSCAD modeling and simulation are carried out to verify the accuracy of the theoretical analysis.

Magnetic shielding is an important part in atomic clock’s physical system. The demagnetization of the assembled magnetic shielding system plays an important role in improving atomic clock’s performance. In terms of the drawbacks in traditional attenuated alternating-current demagnetizing method, this paper proposes a novel method — automatically attenuated alternating-current demagnetizing method. Which is implemented by controlling the demagnetization current waveform thorough the signal source’s modulation, so that these parameters such as demagnetizing current frequency, amplitude, transformation mode and demagnetizing period are precisely adjustable. At the same time, this demagnetization proceeds automatically, operates easily, and works steadily. We have the pulsed optically pumped (POP) rubidium atomic clock’s magnetic shielding system for the demagnetization experiment, the magnetic field value reached 1nT/7cm. Experiments show that novel method can effectively realize the demagnetization of the magnetic shielding system, and well meets the atomic clock’s working requirements.

This work investigates the impact of mechanical strain on wake-up behavior of planar HfO2 ferroelectric capacitor-based memory. External in-plane strain was applied using a four-point bending tool and strain impact on remanent polarization and coercive voltage of the ferroelectric was monitored. It was established that compressive strain is beneficial for 2Pr improvement, while tensile strain leads to its degradation, with a sensitivity of -8.4 ± 0.5 % per 0.1 % of strain. Strain-induced polarization rotation is considered to be the most likely mechanism affecting 2Pr At the same time, no strain impact on Vcwas observed in the investigated strain range. The results seen here can be utilized to undertake stress engineering of ferroelectric memory in order to improve its performance.

This work examines volatile memory modules as ephemeral key storage for security applications in the context of low temperatures. In particular, we note that such memories exhibit a rising level of data remanence as the temperature decreases, especially for temperatures below 280 Kelvin. Therefore, these memories cannot be used to protect the superconducting modules found in high-speed Magnetic Levitation (MagLev) trains, as such modules most often require extremely low temperatures in order to provide superconducting applications. Thus, a novel secure storage solution is required in this case, especially within the oncoming framework concept of the internet of railway things, which is partially based on the increasing utilisation of commercial off-the-shelf components and potential economies of scale, in order to achieve cost efficiency and, thus, widespread adoption. Nevertheless, we do note that volatile memory modules can be utilised as intrinsic temperature sensors, especially at low temperatures, as the data remanence they exhibit at low temperatures is highly dependent on the ambient temperature, and can, therefore, be used to distinguish between different temperature levels.

The behavior of the Current Transformer (CTs) is of utmost importance for protection engineers to ensure reliable operation of power system. CT magnetic saturation is a well-known phenomenon when analyzing its performance characteristics. Nevertheless, transient conditions in the system might be different every time. A good understanding of the magnetic saturation of different CT designs and the effect of saturation on the protection schemes is imperative for developing a robust and dependable protection system. In this paper, various factors that affect CT saturation like X/R ratio, large current magnitudes, DC offset, burden and magnetization remanence are discussed. Analysis of CT saturation based on changes to burden and remanence is performed. In addition to that, the effect of saturation due to these factors on distance protection are presented with test results and analysis. Saturation conditions are analyzed on mho distance elements during phase to ground and three phase faults. Finally, a practical approach to efficiently test the performance of protection schemes under CT saturation conditions is proposed using COMTRADE play back. COMTRADE play back files for various scenarios of CT saturation conditions are generated and used for testing the performance of the protection scheme.

In Magnetic Josephson Junctions (MJJs) based on Superconductor-Insulator-Superconductor-Ferromagnet-Superconductor (SIS’FS), we provide evidence of an unconventional magnetic field behavior of the critical current characterized by an inverted magnetic hysteresis, i.e., an inverted shift of the whole magnetic field pattern when sweeping the external field. By thermoremanence measurements of S/F/S trilayers, we have ruled out that this uncommon behavior could be related to the F-stray fields. In principle, this finding could have a crucial role in the design and proper functioning of scalable cryogenic memories.

Magnetic soft robots are increasingly popular as they provide many advantages such as miniaturization and tetherless control that are ideal for applications inside the human body or in previously inaccessible locations.While non-magnetic elastomers have been extensively characterized and modelled for optimizing the fabrication of soft robots, a systematic material characterization of their magnetic counterparts is still missing. In this paper, commonly employed magnetic materials made out of Ecoflex™ 00-30 and Dragon Skin™ 10 with different concentrations of NdFeB microparticles were mechanically and magnetically characterized. The magnetic materials were evaluated under uniaxial tensile testing and their behavior analyzed through linear and hyperelastic model comparison. To determine the corresponding magnetic properties, we present a method to determine the magnetization vector, and magnetic remanence, by means of a force and torque load cell and large reference permanent magnet; demonstrating a high level of accuracy. Furthermore, we study the influence of varied magnitude impulse magnetizing fields on the resultant magnetizations. In combination, by applying improved, material-specific mechanical and magnetic properties to a 2-segment discrete magnetic robot, we show the potential to reduce simulation errors from 8.5% to 5.4%.

Smart products, such as toy robots, must comply with multiple legal requirements of the countries they are sold and used in. Currently, compliance with the legal environment requires manually customizing products for different markets. In this paper, we explore a design approach for smart products that enforces compliance with aspects of the European Union’s data protection principles within a product’s firmware through a toy robot case study. To this end, we present an exchange between computer scientists and legal scholars that identified the relevant data flows, their processing needs, and the implementation decisions that could allow a device to operate while complying with the EU data protection law. By designing a data-minimizing toy robot, we show that the variety, amount, and quality of data that is exposed, processed, and stored outside a user’s premises can be considerably reduced while preserving the device’s functionality. In comparison with a robot designed using a traditional approach, in which 90% of the collected types of information are stored by the data controller or a remote service, our proposed design leads to the mandatory exposure of only 7 out of 15 collected types of information, all of which are legally required by the data controller to demonstrate consent. Moreover, our design is aligned with the Data Privacy Vocabulary, which enables the toy robot to cross geographic borders and seamlessly adjust its data processing activities to the local regulations.

Drone based applications have progressed significantly in recent years across many industries, including agriculture. This paper proposes a sporadically connected cyber-physical system for assisting winemakers and minimizing the travel time to remote and poorly connected infrastructures. A set of representative diseases and conditions, which will be monitored by land-bound sensors in combination with multispectral images, is identified. To collect accurate data, a trustworthy and secured communication of the drone with the sensors and the base station should be established. We propose to use an Internet of Things framework for establishing a chain of trust by securely onboarding drones, sensors and base station, and providing self-adaptation support for the use case. Furthermore, we perform a security analysis of the use case for identifying potential threats and security controls that should be in place for mitigating them.

An important demand of a wearable health observance system is to soundly exchange the Employees' health data and preventing improper use of black devices. In this project we tend to measure planning wearable sensors device sight abnormal and/or unforeseen things by observance physiological parameters alongside different symptoms. Therefore, necessary facilitate is provided in times of urgent would like. To minimize the health hazards and improving the well-being of employees is to be a major critical role in an organization. As per the report by the Indian Labour Organization, the organization spends an average of 3.94% for GDP on employee treatment. The same study revealed that almost 2.78% million deaths occurs every year and 3.74% million occur non-fatal injuries every year at work. So, the organizations are making towards mitigating the facilities to decimating various IoT technologies and the IoT technology are embedded with modern smart systems, it is easy to monitor every employee in an organization, and also it collects and gather the data and send any critical information by the employees.

In this paper, we propose a functional model for the implementation of devices that use the Internet of Things (IoT). In recent years, the number of devices connected to the internet per person has increased from 0.08 in 2003 to a total of 6.58 in 2020, suggesting an increase of 8,225% in 7 years. The proposal includes a functional IoT model of a cybersecurity architecture by including components to ensure compliance with the proposed controls within a cybersecurity framework to detect cyber threats in IoT-based wearable devices. The proposal focuses on reducing the number of vulnerabilities present in IoT devices since, on average, 57% of these devices are vulnerable to attacks. The model has a 3-layer structure: business, applications, and technology, where components such as policies, services and nodes are described accordingly. The validation was done through a simulated environment of a system for the control and monitoring of pregnant women using wearable devices. The results show reductions of the probability index and the impact of risks by 14.95% and 6.81% respectively.

Recently, the frequent security incidents of the Internet of things make the wearable IOT health monitoring systems (WIHMS) face serious security threats. Aiming at the security requirements of WIHMS identity authentication, Q. Jiang proposed a lightweight device mutual identity authentication solution in 2019. The scheme has good security performance. However, we find that in Jiang’s scheme, in the authentication phase, the server CS needs at least 3 queries and 1 update of the database operation, which affects the overall performance of the system. For this reason, we propose a new device mutual authentication and key agreement protocol. In our protocol, the authentication server only needs to query the server database twice.

Poultry farming has contributed immensely to global food security and the economy. Its produces are favourites and hugely subscribed, due to the uniqueness of their nutrients to all categories of people and the alternatives they provide to other high-cholesterol proteins. The increase in the world's population will continuously stretch for an increase in demands for poultry products. A smart way to ensure continuous production and increased yields in various farms is to adopt automated and remote management of poultries. This paper modelled and developed a collaborative system using the synergistic wireless sensor network technology and the internet of things. The system integrated resourcefully selected wireless sensors, mobile phone, other autonomous devices and the internet to remotely monitor and control environmental parameters and activities within the farm. Parameters such as temperature, humidity, water level, food valve level, ammonia gas, illumination are sensed, benchmarked against selected thresholds, and communicated wirelessly to the sink node and the internet cloud. The required control actions can also be initiated remotely by the administrator through messages or command signal. Also, the various parameters and actions can be read or documented in real-time over the web. The system was tested and evaluated to give an average of about 93.7% accuracy in parameters detection and 2s delay in real-time response. Therefore, a modelled system has been developed to provide robust and more intuitive solutions in poultry farming.

Both the sophistication and scale of cyberattacks are increasing, revealing the extent of risks at which critical infrastructure and other information and communication systems are exposed. Furthermore, the introduction of IoT devices in a number of different applications, ranging from home automation to the monitoring of critical infrastructure, has created an even more complicated cybersecurity landscape. A large amount of research has been done on detecting these attacks in real time, however mitigation is left to security experts, which is time consuming and may have economic consequences. In addition, there is no public data available for action selection that could enable the use of the latest techniques in machine learning or deep learning for this area. Currently, most systems deploy a rule-based response selection methodology for mitigating detected attacks. In this paper, we introduce a situation calculus-based approach to automated response for IoT cyberattacks. The approach offers explicit semantic-rich cognitive modeling of attacks, effects and actions and supports situation inference for timely and accurate responses. We demonstrate the effectiveness of our approach for modelling and responding to cyberattacks by implementing a use case in a real-world IoT scenario.

Assuring Cybersecurity for the Internet of things (IoT) remains a significant challenge. Most IoT devices have minimal computational power and should be secured with lightweight security techniques (optimized computation and energy tradeoff). Furthermore, IoT devices are mainly designed to have long lifetimes (e.g., 10–15 years), forcing the designers to open the system for possible future updates. Here, we developed a lightweight and reconfigurable security architecture for IoT devices. Our research goal is to create a simple authentication protocol based on physical unclonable function (PUF) for FPGA-based IoT devices. The main challenge toward realization of this protocol is to make it make it resilient against machine learning attacks and it shall not use cryptography primitives.

The Internet of Things (IoT) provides significant benefits for industry due to connect the devices together through the internet. Attribute-Based Encryption (ABE) is a technique can enforce an access control over data to guarantee the data security. In this paper, we propose an ABE scheme for data in industrial IoT. The scheme achieves both security and high performance. When there is a shared subpolicy among the access policies of a sensor, the scheme optimizes the encryption of the messages. Through analysis and simulation, we show that our solution is security and efficient.

This paper presents LIRA-V, a lightweight system for performing remote attestation between constrained devices using the RISC-V architecture. We propose using read-only memory and the RISC-V Physical Memory Protection (PMP) primitive to build a trust anchor for remote attestation and secure channel creation. Moreover, we show how LIRA-V can be used for trusted communication between two devices using mutual attestation. We present the design, implementation and evaluation of LIRA-V using an off-the-shelf RISC-V microcontroller and present performance results to demonstrate its suitability. To our knowledge, we present the first remote attestation mechanism suitable for constrained RISC-V devices, with applications to cyber-physical systems and Internet of Things (IoT) devices.

With the development of the Internet of Things, embedded devices have become increasingly frequent in people's daily use. However, with the influx of a huge amount of heterogeneous embedded devices, its security has become an important issue. To face with such problems, remote attestation is undoubtedly a suitable security technology. Nevertheless, traditional remote attestation is limited to verifying the performance of devices as large and heterogeneous devices enter daily life. Therefore, this paper proposes a many-to-one swarm attestation and recovery scheme. Besides, the reputation mechanism and Merkel tree measurement method are introduced to reduce the attestation and recovery time of the scheme, and greatly reducing the energy consumption.

Controller Area Network is the bus standard that works as a central system inside the vehicles for communicating in-vehicle messages. Despite having many advantages, attackers may hack into a car system through CAN bus, take control of it and cause serious damage. For, CAN bus lacks security services like authentication, encryption etc. Therefore, an anomaly detection system must be integrated with CAN bus in vehicles. In this paper, we proposed an Artificial Neural Network based anomaly detection method to identify illicit messages in CAN bus. We trained our model with two types of attacks so that it can efficiently identify the attacks. When tested, the proposed algorithm showed high performance in detecting Denial of Service attacks (with accuracy 100%) and Fuzzy attacks (with accuracy 99.98%).