Product assurance technology for custom LSI/VLSI electronics

The technology for obtaining custom integrated circuits from CMOS-bulk silicon foundries using a universal set of layout rules is presented. The technical efforts were guided by the requirement to develop a 3 micron CMOS test chip for the Combined Release and Radiation Effects Satellite (CRRES). This chip contains both analog and digital circuits. The development employed all the elements required to obtain custom circuits from silicon foundries, including circuit design, foundry interfacing, circuit test, and circuit qualification

An Integrated Analog Optical Motion Sensor

This paper describes the theory and implementation of an integrated system that reports the uniform motion of a visual scene. We have built a VLSI circuit that reports the motion of an image focused directly on it. The chip contains an integrated photosensor array to sense the image and has closely coupled custom circuits to perform computation and data extraction

TOPOLINANO & MAGCAD: A DESIGN AND SIMULATION FRAMEWORK FOR THE EXPLORATION OF EMERGING TECHNOLOGIES

We developed a design framework that enables the exploration and analysis of emerging beyond-CMOS technologies. It is composed of two powerful tools: ToPoliNano and MagCAD. Different technologies are supported, and new ones could be added thanks to their modular structure. ToPoliNano starts from a VHDL description of a circuit and performs the place&route following the technological constraints. The resulting circuit can be simulated both at logical or physical level. MagCAD is a layout editor where the user can design custom circuits, by plac-ing basic elements of the selected technology. The tool can extract a VHDL netlist based on compact models of placed elements derived from experiments or physical simulations. Circuits can be verified with standard VHDL simulators. The design workflow will be demonstrated at the U-booth to show how those tools could be a valuable help in the studying and development of emerging technologies and to obtain feedbacks from the scientific community

An economic analysis of a commercial approach to the design and fabrication of a space power system

A commercial approach to the design and fabrication of an economical space power system is presented. Cost reductions are projected through the conceptual design of a 2 kW space power system built with the capability for having serviceability. The approach to system costing that is used takes into account both the constraints of operation in space and commercial production engineering approaches. The cost of this power system reflects a variety of cost/benefit tradeoffs that would reduce system cost as a function of system reliability requirements, complexity, and the impact of rigid specifications. A breakdown of the system design, documentation, fabrication, and reliability and quality assurance cost estimates are detailed

Detecting ADS-B Spoofing Attacks using Deep Neural Networks

The Automatic Dependent Surveillance-Broadcast (ADS-B) system is a key component of the Next Generation Air Transportation System (NextGen) that manages the increasingly congested airspace. It provides accurate aircraft localization and efficient air traffic management and also improves the safety of billions of current and future passengers. While the benefits of ADS-B are well known, the lack of basic security measures like encryption and authentication introduces various exploitable security vulnerabilities. One practical threat is the ADS-B spoofing attack that targets the ADS-B ground station, in which the ground-based or aircraft-based attacker manipulates the International Civil Aviation Organization (ICAO) address (a unique identifier for each aircraft) in the ADS-B messages to fake the appearance of non-existent aircraft or masquerade as a trusted aircraft. As a result, this attack can confuse the pilots or the air traffic control personnel and cause dangerous maneuvers. In this paper, we introduce SODA - a two-stage Deep Neural Network (DNN)-based spoofing detector for ADS-B that consists of a message classifier and an aircraft classifier. It allows a ground station to examine each incoming message based on the PHY-layer features (e.g., IQ samples and phases) and flag suspicious messages. Our experimental results show that SODA detects ground-based spoofing attacks with a probability of 99.34%, while having a very small false alarm rate (i.e., 0.43%). It outperforms other machine learning techniques such as XGBoost, Logistic Regression, and Support Vector Machine. It further identifies individual aircraft with an average F-score of 96.68% and an accuracy of 96.66%, with a significant improvement over the state-of-the-art detector.Comment: Accepted to IEEE CNS 201

Spoiled Onions: Exposing Malicious Tor Exit Relays

Several hundred Tor exit relays together push more than 1 GiB/s of network traffic. However, it is easy for exit relays to snoop and tamper with anonymised network traffic and as all relays are run by independent volunteers, not all of them are innocuous. In this paper, we seek to expose malicious exit relays and document their actions. First, we monitored the Tor network after developing a fast and modular exit relay scanner. We implemented several scanning modules for detecting common attacks and used them to probe all exit relays over a period of four months. We discovered numerous malicious exit relays engaging in different attacks. To reduce the attack surface users are exposed to, we further discuss the design and implementation of a browser extension patch which fetches and compares suspicious X.509 certificates over independent Tor circuits. Our work makes it possible to continuously monitor Tor exit relays. We are able to detect and thwart many man-in-the-middle attacks which makes the network safer for its users. All our code is available under a free license