Miracle-dz/UniFAR-FTUs huggingface dataset:
LLWM & IR-Mark: Integrating Software Watermarks into an LLVM-based Framework

While software protection mechanisms, such as DRM and online services, hinder the unrestrained duplication of games and applications, these mechanisms fail at protecting individual software components from reuse by intellectual property thieves. While conceptually watermarking can discourage software misuse and allows proof of ownership, embedding watermarks requires expert knowledge. This is why software watermarks are barely used. This paper presents LLWM, an LLVM-based watermarking framework that automates the embedding of watermarks and thus enables the widespread use of watermarking. LLWM incorporates several (adapted) implementations of existing watermarking techniques and provides the foundation for IR-Mark, a new watermarking technique based on a modified register allocation. With LLWM, built upon LLVM and its compiler Clang, developers can use a watermark simply by compiling their codes, without the obstacle of having to understand and run existing methods and standalone tools. With the methods included in LLWM, we offer a variety of choices for embedding techniques and evaluate and discuss their characteristics and resilience against common attacks.
You Make Me Tremble: A First Look at Attacks Against Structural Control Systems

This paper takes a first look at the potential consequences of cyberattacks against structural control systems. We design algorithms and implement them in a testbed and on well-known benchmark models for buildings and bridges. Our results show that attacks to structures equipped with semi-active and active vibration control systems can let the attacker oscillate the building or bridge at the resonance frequency, effectively generating threats to the structure and the people using it. We also implement and test the effectiveness of attack-detection systems.
Regression Greybox Fuzzing

What you change is what you fuzz! In an empirical study of all fuzzer-generated bug reports in OSSFuzz, we found that four in every five bugs have been introduced by recent code changes. That is, 77% of 23k bugs are regressions. For a newly added project, there is usually an initial burst of new reports at 2-3 bugs per day. However, after that initial burst, and after weeding out most of the existing bugs, we still get a constant rate of 3-4 bug reports per week. The constant rate can only be explained by an increasing regression rate. Indeed, the probability that a reported bug is a regression (i.e., we could identify the bug-introducing commit) increases from 20% for the first bug to 92% after a few hundred bug reports. In this paper, we introduce regression greybox fuzzing (RGF) a fuzzing approach that focuses on code that has changed more recently or more often. However, for any active software project, it is impractical to fuzz sufficiently each code commit individually. Instead, we propose to fuzz all commits simultaneously, but code present in more (recent) commits with higher priority. We observe that most code is never changed and relatively old. So, we identify means to strengthen the signal from executed code-of-interest. We also extend the concept of power schedules to the bytes of a seed and introduce Ant Colony Optimization to assign more energy to those bytes which promise to generate more interesting inputs. Our large-scale fuzzing experiment demonstrates the validity of our main hypothesis and the efficiency of regression greybox fuzzing. We conducted our experiments in a reproducible manner within Fuzzbench, an extensible fuzzer evaluation platform. Our experiments involved 3+ CPU-years worth of fuzzing campaigns and 20 bugs in 15 open-source C programs available on OSSFuzz.
RealSWATT: Remote Software-based Attestation for Embedded Devices under Realtime Constraints

Smart factories, critical infrastructures, and medical devices largely rely on embedded systems that need to satisfy realtime constraints to complete crucial tasks. Recent studies and reports have revealed that many of these devices suffer from crucial vulnerabilities that can be exploited with fatal consequences. Despite the security and safety-critical role of these devices, they often do not feature state-of-the-art security mechanisms. Moreover, since realtime systems have strict timing requirements, integrating new security mechanisms is not a viable option as they often influence the device's runtime behavior. One solution is to offload security enhancements to a remote instance, the so-called remote attestation. We present RealSWATT, the first software-based remote attestation system for realtime embedded devices. Remote attestation is a powerful security service that allows a party to verify the correct functionality of an untrusted remote device. In contrast to previous remote attestation approaches for realtime systems, RealSWATT does neither require custom hardware extensions nor trusted computing components. It is designed to work within real-world IoT networks, connected through Wi-Fi. RealSWATT leverages a dedicated processor core for remote attestation and provides the required timing guarantees without hardware extensions. We implement RealSWATT on the popular ESP32 microcontroller, and we evaluate it on a real-world medical device with realtime constraints. To demonstrate its applicability, we furthermore integrate RealSWATT into a framework for off-the-shelf IoT devices and apply it to a smart plug, a smoke detector, and a smart light bulb.
CatchAll: A Robust Multivariate Intrusion Detection System for Cyber-Physical Systems using Low Rank Matrix

Critical infrastructures often depend upon cyber-physical systems (CPS), as seen in the smart grid, autonomous vehicle monitoring, industrial monitoring systems, etc. With the IT/OT convergence, cyber-physical systems became connected to the Internet through firewalls and De-militarized Zones (DMZs). Therefore, cyber-attacks disrupting critical infrastructure services are not uncommon. Advanced attackers often use techniques to subvert standard defenses such as network intrusion detection, firewall, etc., by using packet fragmentation, overlapping fragments, checksum manipulation, sequence number manipulation, etc. Therefore, attacks often go through perimeter defenses and start affecting the physical dynamics of the CPS. This paper proposes a robust intrusion detection system dubbed CatchAll for detecting attacks by finding anomalies in the dynamics of the cyber-physical systems. The proposed Intrusion Detection System(IDS) uses unsupervised learning, as the availability of labeled data is often a problem. We further assume that some fraction of the training data might get corrupted, possibly by network noise or data poisoning attacks. Such assumptions make our method applicable to real-world scenarios, where clean and trusted training data may not be available. The proposed IDS works in $O(d)$ space and time complexity at the deployment and outperforms existing anomaly detection techniques in several real-world data sets and attack scenarios.
CPscan: Detecting Bugs Caused by Code Pruning in IoT Kernels

To reduce the development costs, IoT vendors tend to construct IoT kernels by customizing the Linux kernel. Code pruning is common in this customization process. However, due to the intrinsic complexity of the Linux kernel and the lack of long-term effective maintenance, IoT vendors may mistakenly delete necessary security operations in the pruning process, which leads to various bugs such as memory leakage and NULL pointer dereference. Yet detecting bugs caused by code pruning in IoT kernels is difficult. Specifically, (1) a significant structural change makes precisely locating the deleted security operations (DSO ) difficult, and (2) inferring the security impact of a DSO is not trivial since it requires complex semantic understanding, including the developing logic and the context of the corresponding IoT kernel. In this paper, we present CPscan, a system for automatically detecting bugs caused by code pruning in IoT kernels. First, using a new graph-based approach that iteratively conducts a structure-aware basic block matching, CPscan can precisely and efficiently identify theDSOs in IoT kernels. Then, CPscan infers the security impact of a DSO by comparing the bounded use chains (where and how a variable is used within potentially influenced code segments) of the security-critical variable associated with it. Specifically, CPscan reports the deletion of a security operation as vulnerable if the bounded use chain of the associated security-critical variable remains the same before and after the deletion. This is because the unchanged uses of a security-critical variable likely need the security operation, and removing it may have security impacts. The experimental results on 28 IoT kernels from 10 popular IoT vendors show that CPscan is able to identify 3,193DSO s and detect 114 new bugs with a reasonably low false-positive rate. Many such bugs tend to have a long latent period (up to 9 years and 5 months). We believe CPscan paves a way for eliminating the bugs introduced by code pruning in IoT kernels. We will open-source CPscan to facilitate further research.
Towards Transparent and Stealthy Android OS Sandboxing via Customizable Container-Based Virtualization

A fast-growing demand from smartphone users is mobile virtualization.This technique supports running separate instances of virtual phone environments on the same device. In this way, users can run multiple copies of the same app simultaneously,and they can also run an untrusted app in an isolated virtual phone without causing damages to other apps. Traditional hypervisor-based virtualization is impractical to resource-constrained mobile devices.Recent app-level virtualization efforts suffer from the weak isolation mechanism. In contrast, container-based virtualization offers an isolated virtual environment with superior performance.However, existing Android containers do not meet the anti-evasion requirement for security applications: their designs are inherently incapable of providing transparency or stealthiness. In this paper, we present VPBox, a novel Android OS-level sandbox framework via container-based virtualization. We integrate the principle of anti-virtual-machine detection into VPBox's design from two aspects.First, we improve the state-of-the-art Android container work significantly for transparency.We are the first to offer complete device virtualization on mainstream Android versions.To minimize the fingerprints of VPBox's presence, we enable all virtualization components (i.e., kernel-level device and user level device virtualization) to be executed outside of virtual phones (VPs). Second, we offer new functionality that security analysts can customize device artifacts (e.g., phone model, kernel version, and hardware profiles) without user-level hooking. This capability prevents the tested apps from detecting the particular mobile device (e.g., Google Pixel phone) that runs an Android container.Our performance evaluation on five VPs shows that VPBox runs different benchmark apps at native speed.Compared with other Android sandboxes, VPBox is the only one that can bypass a set of virtual environment detection heuristics. At last, we demonstrate VPBox's flexibility in testing environment-sensitive malware that tries to evade sandboxes.
A PKI-based Framework for Establishing Efficient MPC Channels

The Transport Layer Security (TLS) protocol is a fundamental building block for ensuring security on Internet. It provides an easy to use framework for the purposes of establishing an authenticated and secure channel between two parties that have never physically met. Nevertheless, TLS only provides a simple cryptographic functionality compared to more advanced protocols such as protocols for secure multiparty computation (MPC). In this work, we provide a framework for efficiently establishing channels for MPC over the Internet. We focus on MPC protocols in the oblivious transfer (OT) hybrid model such that it is sufficient to establish OT correlations for such a channel. We revisit and combine different notions of UC security proposed in both the MPC and authenticated key exchange settings. Through this work, we show how an OT protocol can be composed with a secure authenticator to ensure the authenticity of messages sent during the OT. In addition, we adapt and analyse non-interactive OTs based on dense key encapsulation mechanisms (KEMs) in the random oracle model, where the first message, i.e. public key, can be reused. These KEMs can be instantiated based on CDH, RSA and LWE and after a performance and security evaluation, it turns out that the resulting OT protocols are very competitive with the state of the art and are able to leverage existing PKIs.
The role of the ventrolateral anterior temporal lobes in social cognition

A key challenge for neurobiological models of social cognition is to elucidate whether brain regions are specialised for that domain. In recent years, discussion surrounding the role of anterior temporal regions epitomises such debates; some argue the anterior temporal lobe (ATL) is part of a domain-specific network for social processing, while others claim it comprises a domain-general hub for semantic representation. In the present study, we used ATL-optimised fMRI to map the contribution of different ATL structures to a variety of paradigms frequently used to probe a crucial social ability, namely ‘theory of mind’ (ToM). Using multiple tasks enables a clearer attribution of activation to ToM as opposed to idiosyncratic features of stimuli. Further, we directly explored whether these same structures are also activated by a non-social task probing semantic representations. We revealed that common to all of the tasks was activation of a key ventrolateral ATL region that is often invisible to standard fMRI. This constitutes novel evidence in support of the view that the ventrolateral ATL contributes to social cognition via a domain-general role in semantic processing, and against claims of a specialised social function.
Observations of ocean ambient noise (10 Hz to 10 kHz) at the site of a former navy listening station to the west of Point Sur, California, from January to July of 2007

Abstract : Ocean acoustic recordings were obtained from January through June of 2007 at the site of a former Unites States Navy listening station to the west of Point Sur, California. These data were analyzed to determine the characteristics of the ambient acoustic noise. Direct comparisons to previous studies conducted at the same location revealed a near identical match of the pressure spectrum level in the 50 to 120 Hz frequency band to a 1994-2001 study. Comparison to a 1963-1965 study revealed a 3 to 5 dB increase in ambient noise over the 60 to 300 Hz frequency band. As expected, relating ambient noise to wind speed revealed a significant (correlation coefficient greater than 0.5) correlation between 400 Hz and 10 kHz with a maximum correlation coefficient of 0.78 near 2 kHz. Comparing shipping data from San Francisco and Los Angeles-Long Beach ports to ambient noise in the 10 to 1000 Hz band revealed obvious patterns in the relationship of the number of ships arriving or departing each day and noise level. Due to its proximity, the San Francisco shipping data had a greater effect on the ambient noise level at Point Sur. The largest value of the correlation coefficient between ambient noise and shipping traffic was 0.55 and occurred at 700 Hz.
On-line Identification of a Municipal Solid Waste Incinerator by Fully Tuned RBF Neural Networks

Abstract The paper describes an on-line identification algorithm to estimate the steam production of a municipal solid waste incinerator. The algorithm has to learn on-line the system dynamics due to the heavy disturbances acting on the incineration process. The learning algorithm is based on radial basis function networks and combines the growth criterion of the resource allocating network technique with an adaptive extended Kalman filter to update all the parameters of the networks.
Internal meandered loop antenna for GSM/DCS/PCS multiband operation in a mobile phone with the user's hand

A novel internal meandered loop antenna for application in a mobile phone for Global System for Mobile Communication/Digital Communication System/Personal Communication System (GSM/DCS/PCS) multiband operation is presented. Along the symmetric metal‐strip loop structure of the antenna, there are meandered sections for adjusting the antenna's resonant frequencies and widened sections for improving the impedance matching. The antenna's first and second resonant modes (half‐ and one‐wavelength modes) excited at about 900 and 1800 MHz for GSM/DCS operation. With the meandered sections in the loop structure, the antenna's third resonant mode (1.5‐wavelength mode) can be adjusted to be close to the second resonant mode at 1800 MHz to achieve a wider upper band for DCS/PCS operation. In addition, the central region of the proposed loop antenna is unoccupied, which can be used to accommodate possible nearby electronic components, such as the lens of a digital camera. Furthermore, effects of the user's hand holding the mobile phone with the proposed loop antenna are analyzed in this study. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 759–765, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22271
Frequency-response identification of XV-15 tilt-rotor aircraft dynamics

Abstract : Timely design and development of the next generation of tilt-rotor aircraft depend heavily on in-depth understanding of existing XV-15 dynamics and the availability of fully validated simulation models. Previous studies have considered aircraft and simulation trim characteristics, but analyses of basic flight vehicle dynamics have been limited to qualitative pilot evaluations. This study has the following objectives: Documentation and evaluation of XV-15 bare- airframe dynamics; Comparison of aircraft and simulation responses; and Development of a validated transfer function description of the XV-15 needed for future studies. A nonparametric frequency-response approach is used which does not depend on assumed model order or structure. Transfer function representations are subsequently derived which fit the frequency responses in the bandwidth of greatest concern for piloted handling qualities and flight control system applications. This study involved the planning and execution of flight tests on the XV-15 aircraft and piloted-simulation for four flight conditions from hover to cruise. Improved test techniques and pilot-training procedures were devised. Analytical software tools were developed which allow identification of high-resolution spectral responses and the derivation and validation of multi-input/multi-output transfer function models. These techniques were applied in an extensive evaluation of the open-loop flight dynamics of the XV-15 aircraft and simulation mathematical models.
001-112 Tourism 2020 01ENG.indd

Th is paper empirically investigates a causal relationship between tourism and economic growth in Georgia for 1997-2018 period by employing ARDLBT approach to cointegration. Results reject economic-driven tourism growth hypothesis for Georgia and reveal that impact of tourism development over economic growth is negative in the long-run, in contrary positive in the short-run. Obtained results suggest that there is a possibility to have a tourism resource curse in the long-term in Georgia. Georgian government should build a tourism strategy to avoid crowding out of human capital from industrial production and decrease the share of imports for the needs of tourism sector.
Numerical Reasoning over Legal Contracts via Relational Database

Numerical reasoning over text requires deep integration between the semantic understanding of the natural language context and the mathematical calculation of the symbolic terms. However, existing approaches are limited in their ability to incorporate domain-specific knowledge and express mathematical formulas over data structures. Delegating logic reasoning to a relational database is a promising approach to enhance the reasoning complexity. We study the problem of distilling natural language text into a relational database with numerical data structure and querying this database to obtain desired answers. Specifically, given a legal contract and a set of date-related questions in natural language, we utilize pre-trained neural network models to create a relational database to retrieve and generate the target dates. We evaluate our method on the CUAD dataset and demonstrate that our approach has high correct answer coverage and reduces a significant amount of incorrect results even without any labels.
Learning of logical-mathematical contents through fairy tales in Early Childhood Education

The adaptation and use of stories provide a comprehensive scenario of the content, both from a cognitive and emotional point of view. The aim of this research is to show how reading stories can be used in the early learning of mathematics. In order to do so we describe and assess the effectiveness in the classroom, using learning opportunities that use tales scenes as a learning tool. The design is quasi-experimental with a quantitative approach focusing on a control group, containing a sample of students from Kindergarten. The target group worked in the classroom with resources taken from an adaptation of the story of the Ugly Duckling, while the control group worked on the same contents without any didactic modification. The results of the intervention, evaluated using an individual tool, TEMT (Test of Early Mathematics Assessment), initially show homogeneity of the two groups (target and control) and improvements after the intervention in the level of mathematical proficiency in the target group. No differences by age are observed, and very few differences by gender, only in some variables, showing a better performance of the girls.
Education in Efforts to Moderate Islam: A Phenomenological Study of Former Terrorists in East Java, Indonesia

Education is a learning process that is generally held in schools and there are regulations that apply and must be followed. Learners are in learning there are related parties such as teachers/educators in supervising the learning process at school. Some understanding of education or education according to. Langeveld [1], namely: Education is an adult human effort to guide immature humans to maturity. Education is an effort to help children/or adults to carry out their life tasks, so that they can be independent, from an early age, and have social responsibility.
Design of distributed sparse arrays for Lamb wave SHM based upon estimated scattering matrices

A common practice in guided wave structural health monitoring is collecting measurements from a transducer array using the pitch-catch method. Among different array configurations, the spatially distributed array provides a cost-effective solution for rapid interrogation of large, plate-like structures. Several guided wave imaging techniques have been proposed and successfully demonstrated for damage detection and localization. However, the performance of these imaging methods can be compromised by a mismatch between a particular transducer array geometry and the scattering characteristics of a defect of interest. This study proposes a method, which is based upon estimating scattering matrices, to quantify the ability of a specific array geometry to interrogate a scatterer. Several array geometries are evaluated using this method, and a Monte Carlo simulation is then performed to vary the transducer locations to find the array geometry that is best matched to a specific directional scatterer. The efficacy.