Swedish Defence Research Agency

About: Swedish Defence Research Agency is a government organization based out in Stockholm, Sweden. It is known for research contribution in the topics: Radar & Synthetic aperture radar. The organization has 1413 authors who have published 2731 publications receiving 56083 citations. The organization is also known as: Totalförsvarets forskningsinstitut.

C-SAM: Multi-Robot SLAM using square root information smoothing

Abstract: This paper presents collaborative smoothing and mapping (C-SAM) as a viable approach to the multi-robot map- alignment problem. This method enables a team of robots to build joint maps with or without initial knowledge of their relative poses. To accomplish the simultaneous localization and mapping this method uses square root information smoothing (SRIS). In contrast to traditional extended Kalman filter (EKF) methods the smoothing does not exclude any information and is therefore also better equipped to deal with non-linear process and measurement models. The method proposed does not require the collaborative robots to have initial correspondence. The key contribution of this work is an optimal smoothing algorithm for merging maps that are created by different robots independently or in groups. The method not only joins maps from different robots, it also recovers the complete robot trajectory for each robot involved in the map joining. It is also shown how data association between duplicate features is done and how this reduces uncertainty in the complete map. Two simulated scenarios are presented where the C-SAM algorithm is applied on two individually created maps. One basically joins two maps resulting in a large map while the other shows a scenario where sensor extension is carried out.

Oscar — File Type Identification of Binary Data in Disk Clusters and RAM Pages

Abstract: This paper proposes a method, called Oscar, for determining the probable file type of binary data fragments. The Oscar method is based on building models, called centroids, of the mean and standard deviation of the byte frequency distribution of different file types. A weighted quadratic distance metric is then used to measure the distance between the centroid and sample data fragments. If the distance falls below a threshold, the sample is categorized as probably belonging to the modelled file type. Oscar is tested using JPEG pictures and is shown to give a high categorization accuracy, i.e. high detection rate and low false positives rate. By using a practical example we demonstrate how to use the Oscar method to prove the existence of known pictures based on fragments of them found in RAM and the swap partition of a computer.

Single-Chip 220-GHz Active Heterodyne Receiver and Transmitter MMICs With On-Chip Integrated Antenna

Abstract: This paper presents the design and characterization of single-chip 220-GHz heterodyne receiver (RX) and transmitter (TX) monolithic microwave integrated circuits (MMICs) with integrated antennas fabricated in 0.1- μm GaAs metamorphic high electron-mobility transistor technology. The MMIC receiver consists of a modified square-slot antenna, a three-stage low-noise amplifier, and a sub-harmonically pumped resistive mixer with on-chip local oscillator frequency multiplication chain. The transmitter chip is the dual of the receiver chip by inverting the direction of the RF amplifier. The chips are mounted on 5-mm silicon lenses in order to interface the antenna to the free space and are packaged into two separate modules.

Empirical Analysis of System-Level Vulnerability Metrics through Actual Attacks

Abstract: The Common Vulnerability Scoring System (CVSS) is a widely used and well-established standard for classifying the severity of security vulnerabilities. For instance, all vulnerabilities in the US National Vulnerability Database (NVD) are scored according to this method. As computer systems typically have multiple vulnerabilities, it is often desirable to aggregate the score of individual vulnerabilities to a system level. Several such metrics have been proposed, but their quality has not been studied. This paper presents a statistical analysis of how 18 security estimation metrics based on CVSS data correlate with the time-to-compromise of 34 successful attacks. The empirical data originates from an international cyber defense exercise involving over 100 participants and were collected by studying network traffic logs, attacker logs, observer logs, and network vulnerabilities. The results suggest that security modeling with CVSS data alone does not accurately portray the time-to-compromise of a system. However, results also show that metrics employing more CVSS data are more correlated with time-to-compromise. As a consequence, models that only use the weakest link (most severe vulnerability) to compose a metric are less promising than those that consider all vulnerabilities.