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This paper aims to investigate the feasibility of using system power consumption as a factor to improve laptop heat dissipation. The problems due to the CPU overheating are addressed. Based on the Taguchi method, the laptop fan parameters can be optimized with firmware adjustments only. In the Taguchi analysis, the fan speed, system power, and debounce time are considered as control factors, while the Cinebench point is utilized to evaluate the CPU performance. Experimental results demonstrate that the proposed heat dissipation scheme effectively reduces the idle time of a laptop fan. The improvement in heat dissipation can reduce CPU performance degradation because of overheating. According to the best combination of control factors, there is approximately a 5% increase in CPU performance despite a 0.35% increment in power consumption. This paper highlights the effectiveness of optimizing laptop fan parameters through firmware adjustments to improve heat dissipation and mitigate CPU overheating issues. Moreover, the study highlights the delicate balance between power consumption and performance gains. While there may be a slight increase in power consumption associated with the optimized heat dissipation scheme, the observed improvements in CPU performance outweigh this incremental power usage. [ABSTRACT FROM AUTHOR]

This paper presents ReproRun, a flexible and extensible run-time framework for the reconfiguration of functions in field programmable gate array (FPGA) devices used in popular software-defined radio (SDR) platforms. The FPGA devices embed a hardwired or soft processing system (PS) which communicates with the programmable logic (PL) using a standard embedded bus interface. In order to apply a seamless run-time partial reconfiguration, we made use of all the related building blocks, design guidelines, and tools offered by AMD-Xilinx. In ReproRun, each partial bitstream targeting a reconfigurable region (RR) of the PL area comes with its respective firmware (i.e., software functions) that runs on the PS side. Our work guarantees run-time updates of the firmware without interrupting the functionality of other software processes running in the PS or PL, by employing a specialized controller, denoted as Run-timE firmWare reconfIguration contRollEr (REWIRE). The latter leverages the open asymmetric multiprocessing framework (OpenAMP). The partial bitstreams and respective firmware are fetched from a remote location using the trivial file transfer protocol (TFTP). ReproRun can be applied in different FPGA accelerators residing in disaggregated open radio access network (RAN) equipment, adaptive radio access technologies, and Edge servers hosting virtualized functions. [ABSTRACT FROM AUTHOR]

Third-party libraries (TPLs) are extensively utilized by developers to expedite the software development process and incorporate external functionalities. Nevertheless, insecure TPL reuse can lead to significant security risks. Existing methods, which involve extracting strings or conducting function matching, are employed to determine the presence of TPL code in the target binary. However, these methods often yield unsatisfactory results due to the recurrence of strings and the presence of numerous similar non-homologous functions. Furthermore, the variation in C/C++ binaries across different optimization options and architectures exacerbates the problem. Additionally, existing approaches struggle to identify specific pieces of reused code in the target binary, complicating the detection of complex reuse relationships and impeding downstream tasks. And, we call this issue the poor interpretability of TPL detection results. In this article, we observe that TPL reuse typically involves not just isolated functions but also areas encompassing several adjacent functions on the Function Call Graph (FCG). We introduce LibAM, a novel Area Matching framework that connects isolated functions into function areas on FCG and detects TPLs by comparing the similarity of these function areas, significantly mitigating the impact of different optimization options and architectures. Furthermore, LibAM is the first approach capable of detecting the exact reuse areas on FCG and offering substantial benefits for downstream tasks. To validate our approach, we compile the first TPL detection dataset for C/C++ binaries across various optimization options and architectures. Experimental results demonstrate that LibAM outperforms all existing TPL detection methods and provides interpretable evidence for TPL detection results by identifying exact reuse areas. We also evaluate LibAM's scalability on large-scale, real-world binaries in IoT firmware and generate a list of potential vulnerabilities for these devices. Our experiments indicate that the Area Matching framework performs exceptionally well in the TPL detection task and holds promise for other binary similarity analysis tasks. Last but not least, by analyzing the detection results of IoT firmware, we make several interesting findings, for instance, different target binaries always tend to reuse the same code area of TPL. The datasets and source code used in this article are available at https://github.com/Siyuan-Li201/LibAM. [ABSTRACT FROM AUTHOR]

This article discusses the process of establishing an experimental lab alongside computational research. It provides ten simple rules for researchers who are interested in moving into experimental studies, including the importance of collaborating with experimentalists, staying up to date with experimental techniques, finding lab space, keeping computational research ongoing, securing funding, organizing the lab, writing ethics applications, expecting a three-year timeline, documenting experiments, and publishing in experimental journals. The article emphasizes the benefits of combining computational and experimental research and offers practical advice for researchers considering this transition. [Extracted from the article]

In recent years, the Internet of Things (IoT) paradigm has been widely applied across a variety of industrial and consumer areas to facilitate greater automation and increase productivity. Higher dependability on connected devices led to a growing range of cyber security threats targeting IoT-enabled platforms, specifically device firmware vulnerabilities, often overlooked during development and deployment. A comprehensive security strategy aiming to mitigate IoT firmware vulnerabilities would entail auditing the IoT device firmware environment, from software components, storage, and configuration, to delivery, maintenance, and updating, as well as understanding the efficacy of tools and techniques available for this purpose. To this effect, this paper reviews the state-of-the-art technology in IoT firmware vulnerability assessment from a holistic perspective. To help with the process, the IoT ecosystem is divided into eight categories: system properties, access controls, hardware and software re-use, network interfacing, image management, user awareness, regulatory compliance, and adversarial vectors. Following the review of individual areas, the paper further investigates the efficiency and scalability of auditing techniques for detecting firmware vulnerabilities. Beyond the technical aspects, state-of-the-art IoT firmware architectures and respective evaluation platforms are also reviewed according to their technical, regulatory, and standardization challenges. The discussion is accompanied also by a review of the existing auditing tools, the vulnerabilities addressed, the analysis method used, and their abilities to scale and detect unknown attacks. The review also proposes a taxonomy of vulnerabilities and maps them with their exploitation vectors and with the auditing tools that could help in identifying them. Given the current interest in analysis automation, the paper explores the feasibility and impact of evolving machine learning and blockchain applications in securing IoT firmware. The paper concludes with a summary of ongoing and future research challenges in IoT firmware to facilitate and support secure IoT development. [ABSTRACT FROM AUTHOR]

The integration of technology into healthcare has moved from being a luxury to being a need at a time when there is an ever-increasing focus on individual health and wellbeing. The real-time monitoring of one's health metrics and prompt alerts in the event of anomalies or irregularities hold enormous promise for proactive health management. This study's objective and value are revealed in this setting. This project combines cutting-edge hardware and software technologies that have been specially designed to meet the fitness and health requirements of the modern person. The ESP8266 microcontroller, a flexible and potent platform, which functions as the system's brain, easily integrates with a pulse sensor to deliver precise and uninterrupted heart rate monitoring. Real-time analysis of the recorded physiological data enables the early diagnosis of anomalies, abnormal heart rate patterns, or perhaps serious health events. The system uses a Buzzer to trigger a notice when such abnormalities are discovered, assuring prompt user attention. This cutting-edge health-monitoring system was designed with user security, privacy, and accessibility at its core, in addition to usefulness. A favorable user experience is guaranteed by the rigorous calibration of the alerting mechanisms, which deliver useful information without raising unnecessary concern. This initiative, which takes a user-centric approach, seeks to serve a wide range of users, from elders and people with chronic health conditions to athletes and fitness aficionados. This system's implementation process has gone through a number of stages, including hardware integration, firmware development, algorithm design, and user interface refining. The equipment's health-monitoring capabilities have undergone evaluation and calibration to guarantee their dependability and accuracy. Moreover, this project's evolution has been significantly shaped by user input and continuous improvements. This essentially epitomizes the nexus of contemporary technology and healthcare, providing a practical answer for those who are concerned about their health and advancing the development of health-monitoring systems. It equips users with the tools required to play a proactive role in promoting the early identification of health issues, ensuring users' wellbeing and offering peace of mind in a society that is becoming more and more health-conscious. [ABSTRACT FROM AUTHOR]

Smart home environments, which consist of various Internet of Things (IoT) devices to support and improve our daily lives, are expected to be widely adopted in the near future. Owing to a lack of awareness regarding the risks associated with IoT devices and challenges in replacing or the updating their firmware, adequate security measures have not been implemented. Instead, IoT device identification methods based on traffic analysis have been proposed. Since conventional methods process and analyze traffic data simultaneously, bias in the occurrence rate of traffic patterns has a negative impact on the analysis results. Therefore, this paper proposes an IoT traffic analysis and device identification method based on two-stage clustering in smart home environments. In the first step, traffic patterns are extracted by clustering IoT traffic at a local gateway located in each smart home and subsequently sent to a cloud server. In the second step, the cloud server extracts common traffic units to represent IoT traffic by clustering the patterns obtained in the first step. Two-stage clustering can reduce the impact of data bias, because each cluster extracted in the first clustering is summarized as one value and used as a single data point in the second clustering, regardless of the occurrence rate of traffic patterns. Through the proposed two-stage clustering method, IoT traffic is transformed into time series vector data that consist of common unit patterns and can be identified based on time series representations. Experiments using public IoT traffic datasets indicated that the proposed method could identify 21 IoTs devices with an accuracy of 86.9%. Therefore, we can conclude that traffic analysis using two-stage clustering is effective for improving the clustering quality, device identification, and implementation in distributed environments. [ABSTRACT FROM AUTHOR]

This research paper deals with the enhancement of Internet of Things (IoT) security through federated ensemble learning (FEI) and adversarial machine learning (AMLI) algorithms. The proposed approach strives to enhance the security of IoT devices and networks against numerous cyber threats. To address the increasing threat of IoT, the study will utilize advanced machine learning techniques in order to build more resilient defenses for IoT networks. Using the IoT-23_Combined dataset, the study scrutinized an array of IoT attack types, revealing the distribution and frequency of different attack categories. The FEI and AMLI models were trained and tested to detect and mitigate these IoT attacks, with the evaluation metrics being accuracy, precision, recall, and F1 score. The FEI model surpassed the AMLI model, registering superior performance in all metrics, with an accuracy of 87.94% and an F1 score of 88.44%. Concurrently, the study recommends the adoption of system hardening strategies and real-time response measures, including robust authentication methods, secure firmware updates, and security awareness training programs. The assessment of these measures was based on their implementation complexity, potential impact on system performance, and adaptability to changing threats. Conclusively, the research findings illustrate the potential of machine learning to bolster IoT security, suggesting a path towards more proactive defense mechanisms and the creation of a resilient IoT ecosystem. This study holds relevance for entities seeking to fortify their IoT security systems against an evolving threat landscape. [ABSTRACT FROM AUTHOR]

The Internet of Things has a bootloader and applications responsible for initializing the device's hardware and loading the operating system or firmware. Ensuring the security of the bootloader is crucial to protect against malicious firmware or software being loaded onto the device. One way to increase the security of the bootloader is to use digital signature verification to ensure that only authorized firmware can be loaded onto the device. Additionally, implementing secure boot processes, such as a chain of trust, can prevent unauthorized access to the device's firmware and protect against tampering during the boot process. This research is based on the firmware bootloader and application dataflow taint analysis and security assessment of IoT devices as the most critical step in ensuring the security and integrity of these devices. This process helps identify vulnerabilities and potential attack vectors that attackers could exploit and provides a foundation for developing effective remediation strategies. [ABSTRACT FROM AUTHOR]

Embedded devices are pervasive nowadays with the rapid development of the Internet of Things (IoT). This brings significant security issues that make the security analysis of embedded devices important. This paper presents a survey on the security analysis research of embedded devices. First, we analyze the embedded device types and their operating systems. Then, we describe a major dynamic security analysis method for an embedded device, i.e., simulating the firmware of the embedded device and performing fuzzing on the web interface provided by the firmware. Third, we discuss some other issues in embedded security analysis, such as analyzing the attack surface, applying static analysis, and performing large-scale analysis. Based on these analyses, we finally conclude three challenges in the current research and present our insights for future research directions. [ABSTRACT FROM AUTHOR]

The article discusses the development of advanced fly scans using the Mamba software project at the High Energy Photon Source (HEPS) in Beijing, China. The Mamba software aims to provide a reliable and flexible framework for beamline experiments, with a focus on high framerates and data throughputs. The article explores the architectural essentials of fly scans and discusses issues related to motion control, triggering sequences, detectors, and other fields of interest in fly scans. The document discusses the challenges and potential solutions for conducting fly scans with framerates of 10 kHz or higher at HEPS, including limited motor encoder ports, performance limitations of detectors and readout software, and the unsuitability of stepping motors for high-frequency scans. It proposes solutions such as using DeltaTau PowerPMAC for encoder processing and implementing scan fragmentation to address clock drift. The document also discusses the potential for signal distortion in high-frequency data captures and the need for improved hardware/software system architecture for data processing. The source code for the Bubo software is available as part of the open-source edition of Mamba. [Extracted from the article]

This paper studies how to implement Flash data programming for AMOLED display module products through eDP interface. eDP interface is an internal digital interface based on DisplayPort architecture and protocol, which has the advantages of high transmission rate and low power consumption, but is not suitable for transmitting non‐image or video data. Therefore, AMOLED display modules usually need additional interfaces to write key data (such as Demura, Gamma and TCON firmware) into Flash chips, which brings some problems of data transmission interference, unreliability and inefficiency. To solve these problems, this paper proposes a new operation method, which repackages the data to be written, converts them into images, sends them to TCON through eDP interface, and then TCON analyzes the images, extracts the valid data, and starts programming for Flash. This paper divides the whole process into three steps, and verifies the feasibility and effectiveness of the method through experiments. This method effectively solves the problem of data programming, simplifies the production process, and improves the speed and reliability of programming. [ABSTRACT FROM AUTHOR]

This article provides information on the development of alternative firmware for Quansheng UV-5K radios, which allows for additional features such as sending DSB and CW signals, as well as SSTV capabilities. The radios are available for purchase online at a low cost and are considered a good option for basic 2m/70cm handheld use. The article also mentions the passing of Martyn G3UKV, a well-known figure in the amateur radio community. It includes reports of VHF tropo activity, experiences of different operators on various bands, and updates on amateur radio activities such as making contacts with different stations, participating in contests, and working on equipment repairs. The text also mentions DX contacts, meteor showers, satellite operations, and a surprise received by a radio enthusiast from NASA astronaut Kjell Lindgren. [Extracted from the article]

NovAtel has recently leveraged its expertise in both receiver design and anti-jam technology to develop solutions for space- and weight-constrained applications in challenged GNSS environments. Robust Dual-Antenna Receiver (RoDAR), is based on a commercial dual-antenna receiver, originally designed for attitude determination, and employs special firmware to mitigate jammers and spoofers without an increase in size or power consumption. With RoDAR, the multi-frequency, multi-constellation dual-antenna receiver is capable of null-steering at two different frequency bands (e.g., L1 and L5). In September 2022, the Norwegian Public Roads Administration hosted JammerTest, a live, over-the-air broadcast jamming and spoofing test. This paper presents the jamming and spoofing detection and mitigation performance of RoDAR during this live broadcast test. The interference detection provides spectrum monitoring and jamming characterization on all GNSS bands. The mitigation is carried out by steering a null formed on-board the receiver towards a jamming/spoofing source at GPS L1 and L5 bands. The null steering performance is characterized as a function of signal and position availability compared to a non-protected NovAtel receiver. The effectiveness of the anti-jam and anti-spoofing technology is demonstrated using representative complex spoofing and jamming test cases during this event. [ABSTRACT FROM AUTHOR]

The European Spallation Source (ESS) is a neutron source powered by a 5 MW, 2 GeV superconducting proton linac which is currently being constructed in Lund. Due to high beam current, just a few microseconds of operation with a misaligned beam can melt the accelerating cavity wall. Therefore, a Beam Loss Monitor (BLM) system is necessary to protect hardware and personnel from the consequences of beam loss. The BLM's main function is to inhibit beam production when excessively high beam losses are detected. Besides protection functionality, the system is anticipated to provide the means to monitor the beam losses during all modes of operation with the objective of preventing excessive machine activation. This paper concentrates on implementation for ionization chamber Beam Loss Monitor (ICBLM) and Neutron Sensitive Beam Loss Monitor (nBLM) systems. The required microsecond reaction time has been achieved due to the application of an FPGA. A single detector module was installed and successfully tested at LINAC4 at CERN, in the section where conditions are similar to the ones expected in the ESS linac. The summary of these tests is also included. [ABSTRACT FROM AUTHOR]

The aim of the study is the development of a VTOL (Vertical Takeoff and Landing) bicopter, utilizing Autodesk Inventor and Ultimaker Cura software. Design models were inspired by the V22- Osprey and Samson SA-2 from the Avatar movie. Composite materials (carbon fiber and PLA for 3D printing) were chosen due to their high-performance capabilities, as aerospace technology is in an ongoing development and evolution. The construction of the bicopter employed the FAAT method, and for control, the MATEK F411-WSE was utilized to process data from sensors, with specific firmware and the BetaFLIGHT interface for optimizing drone performance. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to present the design and implementation of an embedded controlling system for the Tunable Magnetograph (TuMag) instrument camera sensor and test-bench software application for camera laboratory characterization. The TuMag camera is based on a new scientific sensor GPIXEL SENSE400 device family equipped with an FPGA. The camera sensor has an active area of 2048 × 2048 pixels and reaches a frame rate of up to 48 frames per second. The embedded controlling system was implemented on an Artix 7 FPGA, which oversees controlling the image sensor through a configuration interface. It controls the read-out of the sensor data and the communication of commands with the host device. The camera has a standard CoaXPress communication interface of up to 3125 Gbps. The FPGA embedded control system allows bit, word, and serial channel calibration and the modification of several parameters, such as the region of interest (RoI) size, exposition time, hardware or software trigger, single or continuous acquisition modes, sensor gain, and adjustment of the black level offset and exposition time. In addition, the firmware has a temperature controller, voltage level monitoring, and an enable–disable power sensor. In addition, the test-bench software application is a library developed in Python 3.7. It is a wrapper for the standard GeniCan commercial frame grabber interpreter. This wrapper permits the improvement of the interaction and interface between the user and the hardware in the camera calibration. The test-bench software application permits the reduction of costs and the transport risk of the TuMag camera between different laboratories. All TuMag embedded control systems and test-bench software application functionalities were successfully tested according to scientific requirements. [ABSTRACT FROM AUTHOR]

Hardware/software co-simulation is a technique that can help design and validate digital circuits controlled by embedded processors. Co-simulation has largely been applied to system-level models, and tools for SystemC or SystemVerilog are readily available, but they are either not compatible or very cumbersome to use with VHDL, the most commonly used language for FPGA design. This paper presents a direct, simple-to-use solution to co-simulate a VHDL design together with the firmware (FW) that controls it. It aims to bring the power of co-simulation to every digital designer, so it uses open-source tools, and the developed code is also open. A small patch applied to the QEMU emulator allows it to communicate with a custom-written VHDL module that exposes a CPU bus to the digital design, controlled by the FW emulated in QEMU. No changes to FW code or VHDL device code are required: with our approach, it is possible to co-simulate the very same code base that would then be implemented into an FPGA, enabling debugging, verification, and tracing capabilities that would not be possible even with the real hardware. [ABSTRACT FROM AUTHOR]

LoRa technology has gained popularity as one of the most widely used standards for device interconnection due to its ability to cover long distances and energy efficiency, making it a suitable choice for various Internet of Things (IoT) monitoring and control applications. In this sense, this work presents the development of a visual support tool for creating IoT devices with LoRa and LoRaWAN connectivity. This work significantly advances the state of the art in LoRa technology by introducing a novel visual support tool tailored for creating IoT devices with LoRa and LoRaWAN connectivity. By simplifying the development process and offering compatibility with multiple hardware solutions, this research not only facilitates the integration of LoRaWAN technology within educational settings but also paves the way for rapid prototyping of IoT nodes. The incorporation of block programming for LoRa and LoRaWAN using the Arduinoblocks framework as a graphical environment enhances the capabilities of the tool, positioning it as a comprehensive solution for efficient firmware generation. In addition to the visual tool for firmware generation, multiple compatible hardware solutions enable easy, economical, and stable development, offering a comprehensive hardware and software solution. The hardware proposal is based on an ESP32 microcontroller, known for its power and low cost, in conjunction with an RFM9x module that is based on SX127x LoRa transceivers. Finally, three successfully tested use cases and a discussion are presented. [ABSTRACT FROM AUTHOR]

Protection relays that incorporate advanced microprocessors are vital to electrical grids, providing fast and reliable responses to faulty conditions using efficient communication protocols. Instant detection and response to various faults are essential to minimise the risk of damage. Numerical relays can identify faulty conditions and trigger circuit breakers to open, thus preventing further damage to the system. Due to the lack of autonomous decision-making capabilities, existing numerical relays require manual reconfiguration in situations such as a change in network configuration and protection settings. These relays also do not have the ability to coordinate fault clearance when multiple sources supply power to the grid. A comprehensive overview of the research aimed at developing a multiagent system (MAS)- based adaptive protection relay will be provided by dividing it into separate articles such as firmware and hardware. This first part delves into the firmware aspects of this innovative relay, highlighting its adaptive capabilities and key considerations in its development. The second part will provide detailed design descriptions for the hardware features of the relay. An STM32MPU multicore advanced microprocessor is utilised to design and develop the adaptive numerical relay firmware. It incorporates several protection relay ANSI codes, communication protocols, and MAS-based adaptive protection schemes as part of the firmware. [ABSTRACT FROM AUTHOR]

With the rapid growth of IoT devices, ensuring the security of embedded firmware has become a critical concern. Despite advances in existing vulnerability discovery methods, previous research has been limited to vulnerabilities occurring in binary programs. Although an increasing number of vendors are utilizing Lua scripting language in firmware development, no automated method is currently available to discover vulnerabilities in Lua-based programs. To fill this gap, in this paper, we propose FLuaScan, a novel progressive static analysis approach specifically designed to detect taint-style vulnerabilities in Lua applications in IoT firmware. FLuaScan first heuristically locates the code that handles user input, then divides the code into different segments to conduct a progressive taint analysis. Finally, a graph-based search method is applied to identify vulnerable code that satisfies the conditions of taint propagation. To comprehensively compare FLuaScan with state-of-the-art tool Tscancode, we conducted various experiments on a dataset consisting of 13 real-world firmware samples from different vendors. The results demonstrate the superior performance of FLuaScan in terms of accuracy (increased TP rate from 0% to 42.50%), effectiveness (discovered 21 vulnerabilities, of which 7 are unknown), and practicality (acceptable time overhead and visual output to assist in manual analysis). [ABSTRACT FROM AUTHOR]

WEB technology is utilized for the configuration, interaction, and management of network equipment, which has become ubiquitous in the intelligent industry and consumer electronics field. Unauthorized access on WEB allows unauthorized users to access authorized information, causing security vulnerabilities such as information leakage and command execution. However, commonly used vulnerability detection techniques for WEB unauthorized access face increasing challenges and more efficiently identify potentially sensitive pages. We propose WEBUAD, a WEB Unauthorized Access Detection framework, for the vulnerability detection of WEB service IoT network devices. WEBUAD utilizes the depth-first search algorithm to fully mine available information on device firmware and generate a potential-visit page set as well as a similarity–matching algorithm of machine learning to calculate the similarity of the responses of a web request. Finally, we evaluate WEBUAD on 9 real physical devices from four vendors and 190 device firmware from seven vendors. The result shows that compared with the state-of-the-art tool such as IoTScope, WEBUAD discovered 5007 potentially available pages, of which 658 were accessible and 9 sensitive pages existed, taking 50 s. Furthermore, WEBUAD exposed 13 security-critical vulnerabilities. Our approach can be used to automate the discovery of the WEB unauthorized access vulnerabilities of IoT devices. [ABSTRACT FROM AUTHOR]

In view of the security problem of embedded device firmware update, this study proposes a multi-check firmware security update scheme based on hash, symmetric and asymmetric encryption algorithms. In this study, the master key pairs, temporary key pairs, shared key and hash chain are designed to protect firmware update from identity authentication, data encryption, integrity check and other aspects, which can effectively prevent illegal users, firmware tampering, firmware data leakage, replay attack, firmware rollback and other attacks. In this study, the concrete implementation of the security update scheme is carried out. The experiment results show that compared with the ISP(In System Programming) and IAP(In Application Pragramming) technologies without any security protection, the scheme achieves the security protection of the whole process of firmware update at the time cost of about 7% and 11%, it provides a safe and reliable update method for embedded device firmware update. [ABSTRACT FROM AUTHOR]

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In this research article, a concept for a secondary RAdio Direction And Ranging (RADAR) angle of arrival based system with cooperative targets transmitting at 2.4 GHz and using Multiple Signal Classification (MuSiC) to determine the angles of incidence is investigated. In addition to introducing common algorithms and presenting thorough derivations, the system is first examined through simulations. To prove the concept, hardware, firmware, and software are developed. For MuSiC, we propose three novel methods to obtain the correct incident angle from the spectrum, especially in strong multipath environments. These methods work either for a single spectrum or for a combination recorded at multiple times. Together with the estimated angles of incidence, our methods determine measures on the respective likelihoods. Based on this, we additionally propose two algorithms for computing the final position. Our system is characterized in both a simple 20 m × 15 m outdoor and a 17 m × 13 m multipath indoor environment, where we achieve a mean angular error of 3◦ and a mean positioning error of 0.67 m for the former using only four base stations with four antennas each. Our novel approach shows position accuracy improvements of 15% outdoors and 25% indoors compared to classical MuSiC estimation. [ABSTRACT FROM AUTHOR]

Recently, the process control network (PCN) of oil and gas installation has been subjected to amorphous cyber-attacks. Examples include the denial-of-service (DoS), distributed denial-of-service (DDoS), and man-in-the-middle (MitM) attacks, and this may have largely been caused by the integration of open network to operation technology (OT) as a result of low-cost network expansion. The connection of OT to the internet for firmware updates, third-party support, or the intervention of vendors has exposed the industry to attacks. The inability to detect these unpredictable cyber-attacks exposes the PCN, and a successful attack can lead to devastating effects. This paper reviews the different forms of cyber-attacks in PCN of oil and gas installations while proposing the use of machine learning algorithms to monitor data exchanges between the sensors, controllers, processes, and the final control elements on the network to detect anomalies in such data exchanges. Python 3.0 Libraries, Deep-Learning Toolkit, MATLAB, and Allen Bradley RSLogic 5000 PLC Emulator software were used in simulating the process control. The outcomes of the experiments show the reliability and functionality of the different machine learning algorithms in detecting these anomalies with significant precise attack detections identified using tree algorithms (bagged or coarse) for man-in-the-middle (MitM) attacks while taking note of accuracy-computation complexity trade-offs. [ABSTRACT FROM AUTHOR]

Although the vigorous development of smart homes brings great convenience to people's lives, smart homes usually suffer from various security threats due to firmware vulnerabilities. Firmware update is a possible solution, but existing methods cannot address the security issues during the update process well. To enable secure firmware updates, a Forward Secure Firmware Update (FSFU) system was realized based on the proposed Puncturable-Ciphertext Policy-Attribute-Based Encryption (P-CP-ABE) scheme. In FSFU, when the service provider delivers the latest firmware, it specifies an access policy and some tags to encrypt the data and appends its signature to achieve both fine-grained access control and authentication. Authorized customers can obtain the latest firmware by decrypting the encrypted data through their private key. In particular, after a successful update, each authorized customer can realize forward security by updating his/her puncturable key, which is an important private key component. In addition, FSFU is further enhanced by outsourcing a part of the parameters and computational tasks. Finally, FSFU was proven to be secure under the Decisional Bilinear Diffie–Hellman (DBDH) assumption. Our proposed FSFU is efficient from both the theoretical analysis and the experimental results. [ABSTRACT FROM AUTHOR]

The pervasiveness of IoT and embedded devices allows the deployment of services that were unthinkable only few years ago. Such devices are typically small, run unattended, possibly on batteries and need to have a low cost of production. As all software systems, this type of devices need to be updated for different reasons, e.g., introducing new features, improving/correcting existing functionalities or fixing security flaws. At the same time, because of their low-complexity, standard software distribution platforms and techniques cannot be used to update the software. In this paper we review the current limitations posed to software distribution systems for embedded/IoT devices, consider challenges that the researchers in this area have been identifying and propose the corresponding solutions. [ABSTRACT FROM AUTHOR]