Robots are increasingly involved in our daily lives. Fundamental to robots are the communication link (or stream) and the applications that connect the robots to their clients or users. Such communication link and applications are usually supported through client/server network connection. This networking system is amenable of being attacked and vulnerable to the security threats. Ensuring security and privacy for robotic platforms is thus critical, as failures and attacks could have devastating consequences. In this paper, we examine several cyber-physical security threats that are unique to the robotic platforms; specifically the communication link and the applications. Threats target integrity, availability and confidential security requirements of the robotic platforms, which use MobileEyes/arnlServer client/server applications. A robot attack tool (RAT) was developed to perform specific security attacks. An impact-oriented approach was adopted to analyze the assessment results of the attacks. Tests and experiments of attacks were conducted in simulation environment and physically on the robot. The simulation environment was based on MobileSim; a software tool for simulating, debugging and experimenting on MobileRobots/ActivMedia platforms and their environments. The robot platform PeopleBot^TM was used for physical experiments. The analysis and testing results show that certain attacks were successful at breaching the robot security. Integrity attacks modified commands and manipulated the robot behavior. Availability attacks were able to cause Denial-of-Service (DoS) and the robot was not responsive to MobileEyes commands. Integrity and availability attacks caused sensitive information on the robot to be hijacked. To mitigate security threats, we provide possible mitigation techniques and suggestions to raise awareness of threats on the robotic platforms, especially when the robots are involved in critical missions or applications.

Graphics processing units (GPUs) are now the dominant computing fabric within many supercomputers. As such many mission critical applications run on GPUs, which demand stringent reliability and computational correctness guarantees from GPUs. Prior approaches to GPU reliability have tackled solely either error detection, or error correction assuming error detection is already present. In this paper we present Warped Redundant Execution (Warped-RE), a unified framework that is capable of detecting and then correcting transient and nontransient errors in the GPU execution lanes. Our work exploits two critical properties of applications running on GPUs. First, we observe that neighboring execution lanes in GPUs may operate on the same values. Thus when neighboring lanes execute the same instruction using the same values then these lanes provide inherent DMR (dual modular redundancy) or even inherent TMR (triple modular redundancy) opportunities. The second property we exploit is that due to insufficient parallelism or due to branch divergence, applications do not fully utilize all the available execution lanes. In this case it is possible to force DMR or TMR on unused execution lanes, when inherent redundancy is insufficient. During error-free execution, Warped-RE uses a combination of inherent and forced DMR to guarantee that every thread computation within every warp instruction will be verified. When an error is detected in a warp instruction, the instruction is re-executed in TMR mode in order to correct the error and identify execution lanes with potential non-transient errors. Our evaluations show 8.4% and 29% average performance overhead during the DMR and TMR operation modes, respectively. Compared to traditional DMR and TMR, Warped-RE reduces the power overhead by 42% and 40%, respectively.

Nowadays, robots are widely ubiquitous and integral part in our daily lives, which can be seen almost everywhere in industry, hospitals, military, etc. To provide remote access and control, usually robots are connected to local network or to the Internet through WiFi or Ethernet. As such, it is of great importance and of a critical mission to maintain the safety and the security access of such robots. Security threats may result in completely preventing the access and control of the robot. The consequences of this may be catastrophic and may cause an immediate physical damage to the robot. This paper aims to present a security risk assessment of the well-known PeopleBot; a mobile robot platform from Adept MobileRobots Company. Initially, we thoroughly examined security threats related to remote accessing the PeopleBot robot. We conducted an impact-oriented analysis approach on the wireless communication medium; the main method considered to remotely access the PeopleBot robot. Numerous experiments using SSH and server-client applications were conducted, and they demonstrated that certain attacks result in denying remote access service to the PeopleBot robot. Consequently and dangerously the robot becomes unavailable. Finally, we suggested one possible mitigation and provided useful conclusions to raise awareness of possible security threats on the robotic systems; especially when the robots are involved in critical missions or applications.

Graphics processing units (GPUs) are rapidly becoming the parallel accelerators of choice to run general purpose applications. GPUs that run general purpose applications are termed as GPGPUs. Many mission-critical and long-running scientific application are being ported to run on GPGPUs. These applications demand strong computational integrity. GPGPUs, like many other digital components, face imminent reliability threats due to technology scaling. Of particular concern is the infield hard faults that are persistent and irreversible. GPGPUs comprise of dozens of streaming processors where each streaming processor employs tens of execution units, organized as single instruction multiple thread (SIMT) lanes to deliver massive parallel computational power. In this paper we exploit the massive replication of SIMT lanes to tolerate infield hard faults. First, we introduce thread shuffling to reroute threads, originally mapped to faulty SIMT lanes, to idle healthy lanes. Thread shuffling is insufficient when the number of healthy SIMT lanes is fewer than the number of active threads. To broaden the reach of thread shuffling, we propose dynamic warp deformation to split the warp into multiple sub-warps, each sub-warp uses fewer SIMT lanes thereby providing more opportunities to avoid using a faulty SIMT lane. Finally, we propose warp shuffling which exploits non-uniform degradation of different streaming processors by scheduling a warp to a streaming processor that requires fewer warp splits. Hence, warp shuffling helps to reduce the performance overhead associated with dynamic warp deformation. By deploying the proposed techniques, we can tolerate the worst case scenario of having up to three hard faults per four SIMT lane cluster with at most 36%performance degradation.

Building automation is one of the most popular trends in the 21st century, as it provides buildings with modern and luxurious touches. Furthermore, voice-controlled automation systems are very convenient for the current fast-paced life style as people need to quickly, efficiently, and safely control everything around them. The goal of this article is to provide a skeleton for implementing voice control to a building automation system. The article also presents and evaluates a use case of the proposed skeleton integrated with a KNX-based office automation system. Through the integrated system, lights and blinds are controlled and sensors are polled using voice commands from an authorized personal. This article serves as an educational reference for engineering students interested in applying authorized voice control capability to automation systems.