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Multithreaded programs are subject to data races. Data race detectors find such defects by static or dynamic inspection of the program. Current race detectors suffer from high numbers of false positives, slowdown, and false negatives. Because of these disadvantages, recent approaches reduce the false positive rate and the runtime overhead by applying race detection only on a subset of the whole program...
Given noisy samples of a signal, the problem of testing whether the signal belongs to a given parametric class of signals is considered. We examine the nonparametric situation as for a well-defined null hypothesis signal model we admit broad alternative signal classes that cannot be parametrized. For such a setup, we introduce testing procedures relying on nonparametric kernel-type sampling reconstruction...
High false alarm rates and execution times are among the key issues in host-based anomaly detection systems. In this paper, we investigate the use of trace abstraction techniques for reducing the execution time of anomaly detectors while keeping the same accuracy. The key idea is to represent system call traces as traces of kernel module interactions and use the resulting abstract traces as input...
Software Fault Injection (SFI) is an established technique for assessing the robustness of a software under test by exposing it to faults in its operational environment. Depending on the complexity of this operational environment, the complexity of the software under test, and the number and type of faults, a thorough SFI assessment can entail (a) numerous experiments and (b) long experiment run times,...
Confronting the changing demand of users, the current Internet is revealing its limitations. Information Centric Network (ICN) are Future Internet proposals which are based on named data objects. In order to actually replace its predecessor, ICN must be able to resist existent threats in the current Internet, especially the Denial of Service (DoS) attack. In this paper, we focus on Interest flooding...
In this paper a new method is presented to automatically generate a Design-for-Testability infrastructure which increases the observability of defects in integrated circuits. An algorithm is proposed to detect circuit locations to which small detection blocks can be added. Those are coupled to an oscillator and the triggering of this oscillator in case of detected defects leaves traces in the power...
The purpose of this paper is to present the results of the optimization of some features of a Neural Network applied to the binary detection problem. We present how to design the structure and the training sets, and how to modify the BackPropagation algorithm to improve the results of the network for the binary detection task. The Neural Network, so designed, presents an optimal range of pulse integration...
We present a scene adaptation algorithm for object detection. Our method discovers scene-dependent features discriminative to classifying foreground objects into different categories. Unlike previous works suffering from insufficient training data collected online, our approach incorporated with a similarity grouping procedure can automatically gather more consistent training examples from a neighbour...
Most ports in the United States now inspect a large number of goods for radioactive cargo to address the potential smuggling of illicit nuclear material for terrorism. The U.S. Department of Homeland Security (DHS) has sponsored research to develop systems for detection of illicit nuclear materials at the ports. We present a systematic approach for testing the efficacy of different algorithms used...
The problem of voltage imbalance detection in a three-phase power system using phasor measurement unit (PMU) data is considered within a hypothesis testing framework. A general model for the symmetrical sequences from a PMU measurement at off-nominal frequencies is presented. The new formulation takes into account the fact that minor degree of imbalance in the system is acceptable and does not indicate...
The FLD ensemble classifier is a widely used machine learning tool for steganalysis of digital media due to its efficiency when working with high dimensional feature sets. This paper explains how this classifier can be formulated within the framework of optimal detection by using an accurate statistical model of base learners' projections and the hypothesis testing theory. A substantial advantage...
This paper deals with the blind spectrum sensing problem for arbitrary noise. The majority of current methods consider the Gaussian noise. However, this assumption cannot model the impulsive noise due to the artificial source. In this paper, we remove the requirement on Gaussianity and propose a detection method based on the bootstrap technique. By using multiple receiving antennas, the proposed detector...
Current drift detection techniques detect a change in distribution within a stream. However, there are no current techniques that analyze the change in the rate of these detected changes. We coin the term stream volatility, to describe the rate of changes in a stream. A stream has a high volatility if changes are detected frequently and has a low volatility if changes are detected infrequently. We...
In this paper, we propose a new detector for multiantenna spectrum sensing in cognitive radios (CR) by exploiting the Separating Function Estimation Test (SFET) framework. Specifically, we consider a blind scenario for multiantenna spectrum sensing in which both the channel gains and noise variance are assumed to be unknown. For such a scenario, we find an appropriate Separating Function (SF) whose...
Input Injections are considered as the most common and effective vulnerabilities to exploit in many software systems (esp. web apps). In this paper, we propose a way to detect such vulnerabilities, such as SQL injection, command injection, and cross-site scripting. Input injection is caused by executing user inputs which have not been validated or sanitized, so that the purpose of execution is changed...
Session management vulnerabilities can be categorized as a group of vulnerability that is still often discovered. Session management vulnerabilities consist of session fixation, CSRF, and insufficient cookies attributes. Based on OWASP Top 10 2013, issues on session management are ranked on 2nd place, while CSRF on 8th. To detect session management vulnerabilities, we developed a vulnerability scanning...
Microstructured semiconductor neutron detectors (MSNDs) have long been investigated as a replacement for inefficient thin-film-coated semiconductor neutron detectors. Thin-film-coated semiconductor thermal neutron detection efficiency is restricted to 4–5%. MSNDs improved upon these devices with etched perforations into the diode backfilled with neutron conversion material. Neutron absorption and...
Distributed networks of robust, low-cost, radiation detectors offer the ability to track and locate materials across a number of applications. Individual sensors must be positioned to collectively optimise both the sensing and communication roles of the network and ruggedized to achieve consistent detection performance under a range of environmental conditions. Here we consider the interplay between...
The paper presents the specific testability features included in the design of a single photon counting hybrid pixel detector readout circuit built in the 40nm CMOS. The readout integrated circuit consists of a 18×24 pixel matrix with a pitch of 100 µm. Each pixel comprises of a charge sensitive amplifier, two shapers, two discriminators, eight comparators, tens of inter-pixel connections and a digital...
The problem of reducing electromagnetic interferences (EMI) in industrial and commercial systems is today an issue of international interest. Since nowadays the field of electrical and electronics engineering has rapidly advanced, various apparatus, such as radio and television broadcast stations communication transmitters and mobile phone, intentionally radiate electromagnetic energy during their...
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