Biblio

Robots are networks of a variety of computing devices, such as powerful computing platforms but also tiny microcontrollers. The Robot Operating System (ROS) is the dominant framework for powerful computing devices. While ROS version 2 adds important features like quality of service and security, it cannot be directly applied to microcontrollers because of its large memory footprint. The micro-ROS project has ported the ROS 2 API to microcontrollers. However, the standard ROS 2 concepts are not enough for real-time performance: In the ROS 2 release “Foxy”, the standard ROS 2 Executor, which is the central component responsible for handling timers and incoming message data, is neither real-time capable nor deterministic. Domain-specific requirements of mobile robots, like sense-plan-act control loops, cannot be addressed with the standard ROS 2 Executor. In this paper, we present an advanced Executor for the ROS 2 C API which provides deterministic scheduling and supports domain-specific requirements. A proof-of-concept is demonstrated on a 32-bit microcontroller.

The popularity and demand of home automation has increased exponentially in recent years because of the ease it provides. Recently, development has been done in this domain and few systems have been proposed that either use voice assistants or application for controlling the electrical appliances. However; less emphasis is laid on power efficiency and this system cannot be integrated with the existing appliances and hence, the entire system needs to be upgraded adding to a lot of additional cost in purchasing new appliances. In this research, the objective is to design such a system that emphasises on power efficiency as well as can be integrated with the already existing appliances. NodeMCU, along with Raspberry Pi, Firebase realtime database, is used to create a system that accomplishes such endeavours and can control relays, which can control these appliances without the need of replacing them. The experiments in this paper demonstrate triggering of electrical appliances using voice assistant, fire alarm on the basis of flame sensor and temperature sensor. Moreover; use of android application was presented for operating electrical appliances from a remote location. Lastly, the system can be modified by adding security cameras, smart blinds, robot vacuums etc.

Mobile and IoT operating systems–and their ensuing software updates–are usually distributed as binary files. Given that these binary files are commonly closed source, users or businesses who want to assess the security of the software need to rely on reverse engineering. Further, verifying the correct application of the latest software patches in a given binary is an open problem. The regular application of software patches is a central pillar for improving mobile and IoT device security. This requires developers, integrators, and vendors to propagate patches to all affected devices in a timely and coordinated fashion. In practice, vendors follow different and sometimes improper security update agendas for both mobile and IoT products. Moreover, previous studies revealed the existence of a hidden patch gap: several vendors falsely reported that they patched vulnerabilities. Therefore, techniques to verify whether vulnerabilities have been patched or not in a given binary are essential. Deep learning approaches have shown to be promising for static binary analyses with respect to inferring binary similarity as well as vulnerability detection. However, these approaches fail to capture the dynamic behavior of these systems, and, as a result, they may inundate the analysis with false positives when performing vulnerability discovery in the wild. In particular, they cannot capture the fine-grained characteristics necessary to distinguish whether a vulnerability has been patched or not. In this paper, we present PATCHECKO, a vulnerability and patch presence detection framework for executable binaries. PATCHECKO relies on a hybrid, cross-platform binary code similarity analysis that combines deep learning-based static binary analysis with dynamic binary analysis. PATCHECKO does not require access to the source code of the target binary nor that of vulnerable functions. We evaluate PATCHECKO on the most recent Google Pixel 2 smartphone and the Android Things IoT firmware images, within which 25 known CVE vulnerabilities have been previously reported and patched. Our deep learning model shows a vulnerability detection accuracy of over 93%. We further prune the candidates found by the deep learning stage–which includes false positives–via dynamic binary analysis. Consequently, PATCHECKO successfully identifies the correct matches among the candidate functions in the top 3 ranked outcomes 100% of the time. Furthermore, PATCHECKO's differential engine distinguishes between functions that are still vulnerable and those that are patched with an accuracy of 96%.

Complex CPS such as UAS got rapid development these years, but also became vulnerable to GPS spoofing, packets injection, buffer-overflow and other malicious attacks. Ensuring the behaviors of UAS always keeping secure no matter how the environment changes, would be a prospective direction for UAS security. This paper aims at presenting a reactive synthesis-based approach to implement the automatic generation of secure UAS controller. First, we study the operating mechanism of UAS and construct a high-Ievel model consisting of actuator and monitor. Besides, we analyze the security threats of UAS from the perspective of hardware, software and data transmission, and then extract the corresponding specifications of security properties with LTL formulas. Based on the UAS model and security specifications, the controller can be constructed by GR(1) synthesis algorithm, which is a two-player game process between UAV and Environment. Finally, we expand the function of LTLMoP platform to construct the automatons for controller in multi-robots system, which provides secure behavior strategies under several typical UAS attack scenarios.

RISC-V is free and open standard instruction set architecture following reduced instruction set computer principle. Because of its openness and scalability, RISC-V has been adapted not only for embedded CPUs such as mobile and IoT market, but also for heavy-workload CPUs such as the data center or super computing field. On top of it, Robotics is also a good application of RISC-V because security and reliability become crucial issues of robotics system. These problems could be solved by enthusiastic open source community members as they have shown on open source operating system. However, running RISC-V on local FPGA becomes harder than before because now RISC-V foundation are focusing on cloud-based FPGA environment. We have experienced that recently released OS and toolchains for RISC-V are not working well on the previous CPU image for local FPGA. In this paper we design the local FPGA platform for RISC-V processor and run the robotics application on mainstream Robot Operating System on top of the RISC-V processor. This platform allow us to explore the architecture space of RISC-V CPU for robotics application, and get the insight of the RISC-V CPU architecture for optimal performance and the secure system.

By analogy to nature, sight is the main integral component of robotic complexes, including unmanned vehicles. In this connection, one of the urgent tasks in the modern development of unmanned vehicles is the solution to the problem of providing security for new advanced systems, algorithms, methods, and principles of space navigation of robots. In the paper, we present an approach to the protection of machine vision systems based on technologies of deep learning. At the heart of the approach lies the “Feature Squeezing” method that works on the phase of model operation. It allows us to detect “adversarial” examples. Considering the urgency and importance of the target process, the features of unmanned vehicle hardware platforms and also the necessity of execution of tasks on detecting of the objects in real-time mode, it was offered to carry out an additional simple computational procedure of localization and classification of required objects in case of crossing a defined in advance threshold of “adversarial” object testing.

The paper presents a comprehensive model of cybersecurity threats for a system of autonomous and remotely controlled vehicles (AV) in the environment of a smart city. The main focus in the security context is given to the “integrity” property. That property is of higher importance for industrial control systems in comparison with other security properties (availability and confidentiality). The security graph, which is part of the model, is dynamic, and, in real cases, its analysis may require significant computing resources for AV systems with a large number of assets and connections. The simplified example of the security graph for the AV system is presented.

In light of the problem for garbage cleaning in small water area, an intelligent miniature water surface garbage cleaning robot with unmanned driving and convenient operation is designed. Based on STC12C5A60S2 as the main controller in the design, power module, transmission module and cleaning module are controlled together to realize the function of cleaning and transporting garbage, intelligent remote control of miniature water surface garbage cleaning robot is realized by the WiFi module. Then the prototype is developed and tested, which will verify the rationality of the design. Compared with the traditional manual driving water surface cleaning devices, the designed robot realizes the intelligent control of unmanned driving, and achieves the purpose of saving human resources and reducing labor intensity, and the system operates security and stability, which has certain practical value.

Robot Operating System (ROS) is becoming more and more important and is used widely by developers and researchers in various domains. One of the most important fields where it is being used is the self-driving cars industry. However, this framework is far from being totally secure, and the existing security breaches do not have robust solutions. In this paper we focus on the camera vulnerabilities, as it is often the most important source for the environment discovery and the decision-making process. We propose an unsupervised anomaly detection tool for detecting suspicious frames incoming from camera flows. Our solution is based on spatio-temporal autoencoders used to truthfully reconstruct the camera frames and detect abnormal ones by measuring the difference with the input. We test our approach on a real-word dataset, i.e. flows coming from embedded cameras of self-driving cars. Our solution outperforms the existing works on different scenarios.

In Robotics Operating System Process correspondence is the instrument given by the working framework that enables procedures to speak with one another Message passing model enables different procedures to peruse and compose information to the message line without being associated with one another, messages going between Robots. ROS is intended to be an inexactly coupled framework where a procedure is known as a hub and each hub ought to be answerable for one assignment. In the military application robots will go to go about as an officer and going ensure nation. In the referenced idea robot solider will give the message passing idea then the officers will go caution and start assaulting on the foes.

Industrial robots are playing an important role in now a day industrial productions. However, due to the increasing in robot hardware modules and the rapid expansion of software modules, the reliability of operating systems for industrial robots is facing severe challenges, especially for the light-weight edge computing platforms. Based on current technologies on resource security isolation protection and access control, a novel resource management model for real-time edge system of multiple robot arms is proposed on light-weight edge devices. This novel resource management model can achieve the following functions: mission-critical resource classification, resource security access control, and multi-level security data isolation transmission. We also propose a fault location and isolation model on each lightweight edge device, which ensures the reliability of the entire system. Experimental results show that the robot operating system can meet the requirements of hierarchical management and resource access control. Compared with the existing methods, the fault location and isolation model can effectively locate and deal with the faults generated by the system.

With the wide application of modern robots, more concerns have been raised on security and privacy of robotic systems and applications. Although the Robot Operating System (ROS) is commonly used on different robots, there have been few work considering the security aspects of ROS. As ROS does not employ even the basic permission control mechanism, applications can access any resources without limitation, which could result in equipment damage, harm to human, as well as privacy leakage. In this paper we propose an access control mechanism for ROS based on an extended policy-based access control (PBAC) model. Specifically, we extend ROS to add an additional node dedicated for access control so that it can provide user identity and permission management services. The proposed mechanism also allows the administrator to revoke a permission dynamically. We implemented the proposed method in ROS and demonstrated its applicability and performance through several case studies.

In this paper, we formulate a combinatorial optimization problem that aims to maximize the accuracy of a lower bound estimate of the probability of security of a multi-robot system (MRS), while minimizing the computational complexity involved in its calculation. Security of an MRS is defined using the well-known control theoretic notion of left invertiblility, and the probability of security of an MRS can be calculated using binary decision diagrams (BDDs). The complexity of a BDD depends on the number of disjoint path sets considered during its construction. Taking into account all possible disjoint paths results in an exact probability of security, however, selecting an optimal subset of disjoint paths leads to a good estimate of the probability while significantly reducing computation. To deal with the dynamic nature of MRSs, we introduce two methods: (1) multi-point optimization, a technique that requires some a priori knowledge of the topology of the MRS over time, and (2) online optimization, a technique that does not require a priori knowledge, but must construct BDDs while the MRS is operating. Finally, our approach is validated on an MRS performing a rendezvous objective while exchanging information according to a noisy state agreement process.

To bring a uniform development platform which seamlessly combines hardware components and software architecture of various developers across the globe and reduce the complexity in producing robots which help people in their daily ergonomics. ROS has come out to be a game changer. It is disappointing to see the lack of penetration of technology in different verticals which involve protection, defense and security. By leveraging the power of ROS in the field of robotic automation and computer vision, this research will pave path for identification of suspicious activity with autonomously moving bots which run on ROS. The research paper proposes and validates a flow where ROS and computer vision algorithms like YOLO can fall in sync with each other to provide smarter and accurate methods for indoor and limited outdoor patrolling. Identification of age,`gender, weapons and other elements which can disturb public harmony will be an integral part of the research and development process. The simulation and testing reflects the efficiency and speed of the designed software architecture.

With the growing use of the Robot Operating System (ROS), it can be argued that it has become a de-facto framework for developing robotic solutions. ROS is used to build robotic applications for industrial automation, home automation, medical and even automatic robotic surveillance. However, whenever ROS is utilized, security is one of the main concerns that needs to be addressed in order to ensure a secure network communication of robots. Cyber-attacks may hinder evolution and adaptation of most ROS-enabled robotic systems for real-world use over the Internet. Thus, it is important to address and prevent security threats associated with the use of ROS-enabled applications. In this paper, we propose a novel approach for securing ROS-enabled robotic system by integrating ROS with the Message Queuing Telemetry Transport (MQTT) protocol. We manage to secure robots' network communications by providing authentication and data encryption, therefore preventing man-in-the-middle and hijacking attacks. We also perform real-world experiments to assess how the performance of a ROS-enabled robotic surveillance system is affected by the proposed approach.

The Robot Operating System (ROS) are being deployed for multiple life critical activities such as self-driving cars, drones, and industries. However, the security has been persistently neglected, especially the image flows incoming from camera robots. In this paper, we perform a structured security assessment of robot cameras using ROS. We points out a relevant number of security flaws that can be used to take over the flows incoming from the robot cameras. Furthermore, we propose an intrusion detection system to detect abnormal flows. Our defense approach is based on images comparisons and unsupervised anomaly detection method. We experiment our approach on robot cameras embedded on a self-driving car.

Robotic Operating System(ROS) security research is currently in a preliminary state, with limited research in tools or models. Considering the trend of digitization of robotic systems, this lack of foundational knowledge increases the potential threat posed by security vulnerabilities in ROS. In this article, we present a new tool to assist further security research in ROS, ROSploit. ROSploit is a modular two-pronged offensive tool covering both reconnaissance and exploitation of ROS systems, designed to assist researchers in testing exploits for ROS.

The purpose of this work is to analyze the security model of a robotized system, to analyze the approaches to assessing the security of this system, and to develop our own framework. The solution to this problem involves the use of developed frameworks. The analysis will be conducted on a robotic system of robots. The prefix structures assume that the robotic system is divided into levels, and after that it is necessary to directly protect each level. Each level has its own characteristics and drawbacks that must be considered when developing a security system for a robotic system.

The usage of robot is rapidly growth in our society. The communication link and applications connect the robots to their clients or users. This communication link and applications are normally connected through some kind of network connections. This network system is amenable of being attached and vulnerable to the security threats. It is a critical part for ensuring security and privacy for robotic platforms. The paper, also discusses about several cyber-physical security threats that are only for robotic platforms. The peer to peer applications use in the robotic platforms for threats target integrity, availability and confidential security purposes. A Remote Administration Tool (RAT) was introduced for specific security attacks. An impact oriented process was performed for analyzing the assessment outcomes of the attacks. Tests and experiments of attacks were performed in simulation environment which was based on Gazbo Turtlebot simulator and physically on the robot. A software tool was used for simulating, debugging and experimenting on ROS platform. Integrity attacks performed for modifying commands and manipulated the robot behavior. Availability attacks were affected for Denial-of-Service (DoS) and the robot was not listened to Turtlebot commands. Integrity and availability attacks resulted sensitive information on the robot.

The Robot Operating System (ROS) is a widely adopted standard robotic middleware. However, its preliminary design is devoid of any network security features. Military grade unmanned systems must be guarded against network threats. ROS 2 is built upon the Data Distribution Service (DDS) standard and is designed to provide solutions to identified ROS 1 security vulnerabilities by incorporating authentication, encryption, and process profile features, which rely on public key infrastructure. The Department of Defense is looking to use ROS 2 for its military-centric robotics platform. This paper seeks to demonstrate that ROS 2 and its DDS security architecture can serve as a functional platform for use in military grade unmanned systems, particularly in unmanned Naval aerial swarms. In this paper, we focus on the viability of ROS 2 to safeguard communications between swarms and a ground control station (GCS). We test ROS 2's ability to mitigate and withstand certain cyber threats, specifically that of rogue nodes injecting unauthorized data and accessing services that will disable parts of the UAV swarm. We use the Gazebo robotics simulator to target individual UAVs to ascertain the effectiveness of our attack vectors under specific conditions. We demonstrate the effectiveness of ROS 2 in mitigating the chosen attack vectors but observed a measurable operational delay within our simulations.

Autonomous technologies have been rapidly replacing the traditional manual intervention nearly in every aspect of our life. These technologies essentially require robots to carry out their automated processes. Nowadays, with the emergence of industry 4.0, robots are increasingly being remote-controlled via client-server connection, which creates uncommon vulnerabilities that allow attackers to target those robots. The development of an open source operational environment for robots, known as Robot Operating System (ROS) has come as a response to these demands. Security and privacy are crucial for the use of ROS as the chance of a compromise may lead to devastating ramifications. In this paper, an overview of ROS and the attacks targeting it are detailed and discussed. Followed by a review of the ROS security and digital investigation studies.

Robots operating alongside humans in field environments have the potential to greatly increase the situational awareness of their human teammates. A significant challenge, however, is the efficient conveyance of what the robot perceives to the human in order to achieve improved situational awareness. We believe augmented reality (AR), which allows a human to simultaneously perceive the real world and digital information situated virtually in the real world, has the potential to address this issue. Motivated by the emerging prevalence of practical human-wearable AR devices, we present a system that enables a robot to perform cooperative search with a human teammate, where the robot can both share search results and assist the human teammate in navigation to the search target. We demonstrate this ability in a search task in an uninstrumented environment where the robot identifies and localizes targets and provides navigation direction via AR to bring the human to the correct target.

This paper explores an innovative approach to the telerobotics reasoning architecture and networking, which offer a reliable and adaptable operational process for complex tasks. There are many operational challenges in the remote control for manufacturing that can be introduced by the network communications and Iatency. A new protocol, named compact Reliable UDP (compact-RUDP), has been developed to combine both data channelling and media streaming for robot teleoperation. The original approach ensures connection reliability by implementing a TCP-like sliding window with UDP packets. The protocol provides multiple features including data security, link status monitoring, bandwidth control, asynchronous file transfer and prioritizing transfer of data packets. Experiments were conducted on a 5DOF robotic arm where a cutting tool was mounted at its distal end. A light sensor was used to guide the robot movements, and a camera device to provide a video stream of the operation. The data communication reliability is evaluated using Round-Trip Time (RTT), and advanced robot path planning for distributed decision making between endpoints. The results show 88% correlation between the remotely and locally operated robots. The file transfers and video streaming were performed with no data loss or corruption on the control commands and data feedback packets.

Cyber-physical systems contribute to building new infrastructure in the modern world. These systems help realize missions reducing costs and risks. The seas being a harsh and dangerous environment are a perfect application of them. Unmanned Surface vehicles (USV) allow realizing normal and new tasks reducing risk and cost i.e. surveillance, water cleaning, environmental monitoring or search and rescue operations. Also, as they are unmanned vehicles they can extend missions to unpleasing and risky weather conditions. The novelty of these systems makes that new command and control platforms need to be developed. In this paper, we describe an implemented architecture with 5 separated levels. This structure increases security by defining roles and by limiting information exchanges.

This paper revealed the development and implementation of the wearable sensors based on transient responses of textile chemical sensors for odorant detection system as wearable sensor of humanoid robot. The textile chemical sensors consist of nine polymer/CNTs nano-composite gas sensors which can be divided into three different prototypes of the wearable humanoid robot; (i) human axillary odor monitoring, (ii) human foot odor tracking, and (iii) wearable personal gas leakage detection. These prototypes can be integrated into high-performance wearable wellness platform such as smart clothes, smart shoes and wearable pocket toxic-gas detector. While operating mode has been designed to use ZigBee wireless communication technology for data acquisition and monitoring system. Wearable humanoid robot offers several platforms that can be applied to investigate the role of individual scent produced by different parts of the human body such as axillary odor and foot odor, which have potential health effects from abnormal or offensive body odor. Moreover, wearable personal safety and security component in robot is also effective for detecting NH3 leakage in environment. Preliminary results with nine textile chemical sensors for odor biomarker and NH3 detection demonstrates the feasibility of using the wearable humanoid robot to distinguish unpleasant odor released when you're physically active. It also showed an excellent performance to detect a hazardous gas like ammonia (NH3) with sensitivity as low as 5 ppm.