Security-sensitive Areas Research Articles

Detection and Identification of Non-cooperative UAV Using a COTS mmWave Radar

Small Unmanned Aerial Vehicles (UAVs) are becoming potential threats to security-sensitive areas and personal privacy. A UAV can shoot photos at height, but how to detect such an uninvited intruder is an open problem. This article presents mmHawkeye, a passive approach for non-cooperative UAV detection and identification with a commercial off-the-shelf millimeter wave (mmWave) radar. mmHawkeye does not require prior knowledge of the type, motions, and flight trajectory of the UAV, while exploiting the signal feature induced by the UAV’s periodic micro-motion (PMM) for long-range accurate detection. The design is therefore effective in dealing with low signal-to-noise ratio and uncertain reflected signals from the UAV. After analyzing the theoretical model of the PMM feature, mmHawkeye can further track the UAV’s position containing range, azimuth and altitude angle with dynamic programming and particle filtering and then identify it with a Long Short-Term Memory–based detector. We implement mmHawkeye on a commercial mmWave radar and evaluate its performance under varied settings. The experimental results show that mmHawkeye has a detection accuracy of 95.8% and can realize detection at a range up to 80 m.

Intermediate-Layer Transferable Adversarial Attack With DNN Attention

The widespread deployment of deep learning models in practice necessitates an assessment of their vulnerability, particularly in security-sensitive areas. As a result, transfer-based adversarial attacks have elicited increasing interest in assessing the security of deep learning models. However, adversarial samples usually exhibit poor transferability over different models because of overfitting of the particular architecture and feature representation of a source model. To address this problem, the Intermediate Layer Attack with Attention guidance (IAA) is proposed to alleviate overfitting and enhance the black-box transferability. The IAA works on an intermediate layer <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> of the source model. Guided by the model’s attention to the features of layer <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> , the attack algorithm seeks and undermines the key features that are likely to be adopted by diverse architectures. Significantly, IAA focuses on improving existing white-box attacks without introducing significant visual perceptual quality degradation. Namely, IAA maintains the white-box attack performance of the original algorithm while significantly enhancing its black-box transferability. Extensive experiments on ImageNet classifiers confirmed the effectiveness of our method. The proposed IAA outperformed all state-of-the-art benchmarks in various white-box and black-box settings.

The Female ‘Boot on the Ground’: Indian Ambivalence Over Gender Mainstreaming in UN Peacekeeping Operations

ABSTRACT The Indian government has presented itself as a champion of gender mainstreaming in UN peacekeeping. At the same time, the domestic security sector in India continues to create a gender-segregated environment and experiences of uniformed women in the field show remaining barriers for gender equity. Given this contradiction, the article examines the ambivalence inherent to Indian gender mainstreaming of peacekeeping units. We argue that transnational norms, such as gender mainstreaming, are embedded in larger norm bundles, and we combine the literature of norm localization and norm contestation in our conceptual framework to illustrate how India localizes parts of the gender mainstreaming norm bundle whilst contesting others. We find that India’s localization of the gender mainstreaming norm has meant to pursue an asymmetric gender-parity approach between different branches of the Indian security forces and that it has fomented a division of labour within the police corps. Moreover, we illustrate how India contests the idea of placing women in security-sensitive areas, in combat roles, and gender-integrated police units.

Passive Gamma-Ray and Neutron Imaging Systems for National Security and Nuclear Non-Proliferation in Controlled and Uncontrolled Detection Areas: Review of Past and Current Status.

Global concern for the illicit transportation and trafficking of nuclear materials and other radioactive sources is on the rise, with efficient and rapid security and non-proliferation technologies in more demand than ever. Many factors contribute to this issue, including the increasing number of terrorist cells, gaps in security networks, politically unstable states across the globe and the black-market trading of radioactive sources to unknown parties. The use of passive gamma-ray and neutron detection and imaging technologies in security-sensitive areas and ports has had more impact than most other techniques in detecting and deterring illicit transportation and trafficking of illegal radioactive materials. This work reviews and critically evaluates these techniques as currently utilised within national security and non-proliferation applications and proposes likely avenues of development.

Secrecy Capacity and Secure Distance for Diffusion-Based Molecular Communication Systems

The biocompatibility and nanoscale features of Molecular Communication (MC) make this paradigm, based on molecules and chemical reactions, an enabler for communication theory applications in the healthcare at its biological level ( e.g. , bimolecular disease detection/monitoring and intelligent drug delivery). However, the adoption of MC-based innovative solutions into privacy and security-sensitive areas is opening new challenges for this research field. Despite fundamentals of information theory applied to MC have been established in the last decade, research work on security in MC systems is still limited. In contrast to previous literature focused on challenges, and potential roadmaps to secure MC, this paper presents the preliminary elements of a systematic approach to quantifying information security as it propagates through an MC link. In particular, a closed-form mathematical expression for the secrecy capacity of an MC system based on free molecule diffusion is provided. Numerical results highlight the dependence of the secrecy capacity on the average thermodynamic transmit power, the eavesdropper’s distance, the transmitted signal bandwidth, and the receiver radius. In addition, the concept of secure distance in an MC system is introduced and investigated for two different techniques of signal detection, i.e. , based on energy and amplitude. The secrecy capacity can be used to determine how much secure information (bit/sec/Hz) can be exchanged and within which operative range, while the secure distance can be used to set the transmit power to obtain a secure channel at a given distance. We envision these metrics will be of utmost importance for a future design framework tailored to MC systems and their practical applications.

Blockchain-based Object Name Service with Tokenized Authority

Today, the Internet of Things (IoT) technology is applied everywhere, providing tremendous amounts of IoT service. The GS1, a non-profit international standards organization, has established standards for IoT technology. Especially, the GS1 standardized an Object Name Service (ONS) leveraging DNS's distributed and federated infrastructure, enables users to manage and discover IoT services such as the retail, food, healthcare, smart city, and so on. However, the ONS is vulnerable to the data tampering, privilege escalation, and service fault caused by DNS attacks including the man in the middle, cache poisoning, replay, hijacking, and denial of service attacks. Nowadays, IoT services are used in security-sensitive areas, such as finance and healthcare. Therefore, the security of ONS should be strengthened before causing severe problems such as data breach, economic loss, and social loss. In this paper, we propose a blockchain-based ONS with a tokenized authority called the BlockONS. The BlockONS provides strength in the data tampering and privilege escalation allowing a fault tolerance. The BlockONS consists of a content off-chain scaling, a data tampering validation method, a fault-tolerance method, and a Blockchain Token-Based Access Control (BTBAC) method. We designed the BlockONS into two parts: A BlockONS Node part manages the validation method and BTBAC model. A BlockONS Agent part manages the off-chain scaling and fault tolerance. Finally, we implemented the BlockONS leveraging a Hyperledger Sawtooth blockchain. We proved the proposed validation method, fault tolerance method, and BTBAC method through use cases and security analyses on attack situations. We deployed the BlockONS in the Daejeon city and evaluated the performance to show the feasibility of the BlockONS.

Hidden Markov model based drone sound recognition using MFCC technique in practical noisy environments

The development of drones has captured the attention of hobbyists and investors alike; drones now have greater commercial and military applications owing to their relatively small size and ability to fly without an on-board pilot. However, certain drone applications may pose serious threats to public safety. The most important problem to be addressed is the recognition of drones in security-sensitive areas. This paper presents an approach to recognize drones through sounds emitted by their propellers using Mel frequency cepstral coefficients (MFCCs) technique for feature extraction and the hidden Markov model (HMM) approach for classification. In the feature extraction stage, two schemes for feature vectors (one using twenty-four MFCCs and the other using the proposed thirty-six MFCCs) are applied, where additional dynamic information of the features is added in the latter. The classifier based on HMMs is then trained using the extracted features according to different training datasets in order to validate the effect of the number of sound types in each cluster on the recognition rate performance. We perform experiments for drone sound recognition utilizing various training datasets for the purpose of classifier optimization, as well as for the two MFCC schemes that are applied in each trial, using the same training datasets for a fair comparison. The experimental results finally validate the feasibility and effectiveness of our proposed methods with relatively high recognition rates, even in noisy environments.

Amateur Drone Monitoring: State-of-the-Art Architectures, Key Enabling Technologies, and Future Research Directions

The UAV or mini-drones equipped with sensors are becoming increasingly popular for various commercial, industrial, and public-safety applications. However, drones with uncontrolled deployment pose challenges for highly security-sensitive areas such as a President's house, nuclear plants, and commercial areas because they can be used unlawfully. In this article, to cope with security-sensitive challenges, we propose point-to-point and FANET architectures to assist the efficient deployment of MDrs. To capture an ADr, an MDr must have the capability to efficiently and quickly detect, track, jam, and hunt the ADr. We discuss the capabilities of the existing detection, tracking, localization, and routing schemes, and also present the limitations of these schemes as further research challenges. Moreover, the future challenges related to co-channel interference, channel model design, and cooperative schemes are discussed. Our findings indicate that MDr deployment is necessary for the care of ADrs, and intensive research and development is required to fill the gaps in the existing technologies.

A Three Electrode Mixed Potential Sensor for Gas Detection and Discrimination

Mixed potential solid state electrochemical sensors potentially serve as devices for detection of pollutants from industrial and automotive exhaust and can screen dangerous explosive chemicals in security sensitive areas. In these sensors the difference in catalytic activity between two electrode materials produces a voltage from the difference in the mixed potential that is established at steady state. By integrating multiple electrodes on a single substrate, each pair tuned to be sensitive to different gases, a device can be produced which is selectively sensitive to a variety of gases. The three-electrode sensors were fabricated by ESL ElectroScience with a high temperature co-firing technique on an insulator-YSZ-insulator substrate and Pt, La0.8Sr0.2CrO3 (LSCO), and Au0.5Pd0.5 electrodes were applied by screen printing. A porous YSZ layer over the electrodes serves as the electrolyte, and a length of Pt is printed on the back to serve as an integrated heater. The heating is applied by a control board which imposes a constant resistance, maintaining the temperature during the testing at various flow rates. The sensors were tested at 450-500oC in a 10% O2 atmosphere to different test gases which include NOx, CO, C3H8, (Figure 1) and mixtures of these gases. The Au/Pd+Pt pair is found to be most sensitive to NOx and CO, the LSCO+Pt pair is most sensitive to NOx and C3H8, and the Au/Pd+Pt pair is sensitive only to CO. Against 50-200 ppm backgrounds of NOx and C3H8, the introduction of 100 ppm CO to the gas stream yields a 30 mV response on the Au/Pd+Pt and Au/Pd+LSCO pairs, but produces less than 10 mV shift on the LSCO+Pt pair. Once sets of data consisting of voltage responses to blends of gases were collected, we successfully trained artificial neural networks to associate voltage responses with both binary gas mixture ratios and absolute concentrations of gases, as well as identify which mixtures of gases were present. Figure 1. Response of the three-electrode sensor at 450oC to different gases, where a preferential selectivity towards CO is seen in Au/Pd+Pt or Au/Pd+LSCO pairs and a selectivity towards C3H8 is seen in LSCO+Pt. Figure 1

Frequency of Flame Sensor Activation in Public Places after Administration of Radioactive Iodine to Treat Graves Disease: A Recent Survey

Ultraviolet (UV)-perception-type flame sensors detect gamma rays emitted from iodine 131 ((131)I). Explaining the possibility of flame sensor activation to patients when they receive (131)I to treat Graves disease or other ablative purposes is important. We investigate the current situation of flame sensor activation after radioactive iodine (RAI) therapy. A total of 318 patients (65 males and 253 females) with Graves disease who received RAI therapy at our clinic between November 2007 and June 2014 participated in this study. Patients were given both written and oral explanations regarding the possibility of flame sensor activation. Participants were surveyed with a questionnaire. The following question was asked: "Did the fire alarm (flame sensor) go off when you used a restroom in places like shopping centers within a few days after your isotope therapy?" To those who answered "yes," we asked where the fire alarm had gone off. Of the 318 patients, 19 (6.0%) answered "yes," 2 of whom were male while 17 were female. Of the 299 (94.0%) patients who answered "no," 63 were male and 236 were female. As to the place of restroom sensor activation, shopping centers were reported by 9 patients; supermarkets by 5; airports by 2; and a bookstore, the Kyushu Shinkansen (bullet train), and a hospital by 1 each. Explaining to patients the possibility of flame sensor activation after RAI therapy is important to avoid some complications, especially in security-sensitive areas. (131)I = iodine 131 RAI = radioactive iodine UV = ultra-violet.

Optical Constants of Harmful and Highly Energetic Liquids for Application to THz Screening Systems

The far-infrared (IR) optical constants of a set of hazardous and flammable liquids have been obtained by means of spectroscopic ellipsometry in attenuated total reflection configuration over a broad spectral range. Such liquids recently became of considerable concern for transportation security measures worldwide. Their optical identification at check-in gates can only become possible if the characteristic spectra are already known. The refractive indices and the extinction coefficients reported here contribute to a spectroscopic data base in the far-IR and terahertz (THz) spectral regions and may support modeling the performance of THz screening systems on liquids for airports and other security sensitive areas. Examples of several container material/liquid systems are discussed. From the measured optical constants typical THz waveforms are calculated and discussed.

Advanced Moving Object Detection by Using K-means Algorithm

Moving Object Detection systems have long been in use to look at security sensitive areas. The manufacture of video investigating systems sensible desires fast, reliable and durable algorithms for moving object detection classification pursuit and activity analysis. Moving object detection is that the essential step for extra analysis of video. It handles segmentation of moving objects from stationary background objects. Object classification step categorizes detected objects into preened classes like human, vehicle, animal, clutter, etc. it's a necessity to inform apart objects from each other therefore on trace and analyse their actions reliably. In previous system we have got performed background subtraction by victimization clever Edge Detection. In clever Edge Detection technique we tend to tend to square measure taking 2 photos for comparison those square measure background image and foreground image. Previous strategies for object detection square measure methodology along side object detectors image segmentation and Background subtraction. Our methodology aims to section objects supported motion info and it contains a part of background modelling. In the previous strategies we tend to tend to square measure conducting background subtraction only for photos. For this we tend to tend to projected an image component wise background modelling and subtraction technique mistreatment multiple choices. Hence, throughout this color, gradient and Hear-Like choices square measure integrated to handle the variation element. Thus, motion segmentation and background subtraction square measure the foremost connected topics to the current paper.

A Motion Region Detection and Tracking Method

Nowadays, video surveillance is indispensable in security-sensitive areas. Hence, a significant amount of work has been done in this field. This paper proposes a hybrid framework for motion region detection and an appearance-based real-time motion tracking system. Initially, a foreground map is extracted through a process of subtraction from a background model, applying a temporal differencing method. Then, shadow elimination and morphological operations are used to remove noise. Finally, models are initiated for each detected motion region by extracting features such as center of mass and a color correlogram, which are then used for tracking purposes. As the similarity in distances within a certain radius is measured, the probability of confusing objects is reduced considerably, and therefore, performance is optimized significantly. The proposed framework also uses a robust technique to label people within a group. This framework has the capability to work in indoor, semi-outdoor, and even outdoor environments that generate a penumbra shadow, and it handles the groups formed due to occlusion effectively. The framework takes good care of false foreground pixels due to penumbra shadow. Hence, the proposed framework will play a pivotal role in providing security in highly confidential areas.

Design and optimization of distributed sensing coverage in wireless sensor networks

For many sensor network applications, such as military surveillance, it is necessary to provide full sensing coverage to a security-sensitive area while, at the same time, minimizing energy consumption and extending system lifetime by leveraging the redundant deployment of sensor nodes. In this paper, we propose a surveillance service for sensor networks based on a distributed energy-efficient sensing coverage protocol. In the protocol, each node is able to dynamically decide a schedule for itself to guarantee a certain degree-of-coverage (DOC) with average energy consumption inversely proportional to the node density. Several optimizations and extensions are proposed to enhance the basic design with a better load-balance feature and a longer network lifetime. We consider and address the impact of the target size and the unbalanced initial energy capacity of individual nodes to the network lifetime. Several practical issues such as the localization error, irregular sensing range, and unreliable communication links are addressed as well. Simulation shows that our protocol extends system lift-time significantly with low energy consumption. It outperforms other state-of-the-art schemes by as much as 50% reduction in energy consumption and as much as 130% increase in the half-life of the network.