Secure Identification Research Articles

Cloud edge cooperative attack recognition based on CNN

In recent years, the concept of cloud edge collaboration has been proposed, which uses some operations of edge and cloud to complete all kinds of collaboration, and has produced various applications in various fields. CNN is one of the hot spots of scientific research, and has excellent performance in the field of image voice. In view of these advantages, combined with the cooperation of CNN and cloud edge, this paper proposes cloud edge collaborative attack recognition based on CNN. The attack recognition model is trained by using CNN and open source data set, and cloud edge collaboration is realized by data and model transmission between edge and cloud. This method realizes the security collaboration between the cloud and the edge, and reduces the resource pressure of the cloud. At the same time, the cooperation of multiple edge ends increases the security identification ability of the cloud and improves the security coordination between the cloud and the edge.

Clandestine nanoelectromechanical tags for identification and authentication

The realization of truly unclonable identification and authentication tags is the key factor in protecting the global economy from an ever-increasing number of counterfeit attacks. Here, we report on the demonstration of nanoscale tags that exploit the electromechanical spectral signature as a fingerprint that is characterized by inherent randomness in fabrication processing. Benefiting from their ultraminiaturized size and transparent constituents, these clandestine nanoelectromechanical tags provide substantial immunity to physical tampering and cloning. Adaptive algorithms are developed for digital translation of the spectral signature into binary fingerprints. A large set of tags fabricated in the same batch is used to estimate the entropy of the corresponding fingerprints with high accuracy. The tags are also examined under repetitive measurements and temperature variations to verify the consistency of the fingerprints. These experiments highlight the potential of clandestine nanoelectromechanical tags for the realization of secure identification and authentication methodologies applicable to a wide range of products and consumer goods.

Customers’ awareness and knowledge level of fraudulent acts in electronic banking in Ghana: evidence from a universal bank

PurposeThis study aims to assess customers’ awareness and level of knowledge on electronic banking fraud.Design/methodology/approachA well-structured interviewer-assisted questionnaire was used to collect data from 400 clients of a case study bank. Data were analysed using descriptive statistics. Kendall’s coefficient of concordance (W) statistic was also estimated to track and rank the fraudulent activities identified by the respondents with respect to electronic banking.FindingsThis study found that respondents were aware of most of the specific forms of electronic banking fraud. Firstly, automated teller machinfraud is the most common scam for which customers are aware of. Secondly, institutional factors such as lack of monitoring and education of clients are major factors which expose the bank and clients to fraudulent electronic banking acts. Thirdly, the most effective action that can be taken to prevent fraud in the bank is increased security and personal identification number (PIN) protection education.Research limitations/implicationsThis study focusses on a universal bank and uses data from customers of only one branch of the bank to achieve the research objectives.Originality/valueOne uniqueness of this paper is in the adoption of Kendall’s coefficient of concordance (W) statistic to track and rank fraudulent banking activities. The findings will allow financial institutions to know the forms of current and innovative electronic banking fraudulent activities that customers are aware of. It will also enable the banks to find ways to inform their clients about emerging electronic banking fraudulent activities to prevent them from falling victims.

Laminar Flow-Based Fiber Fabrication and Encoding via Two-Photon Lithography.

In recent years, flow photolithography (FL) has emerged as a powerful synthetic tool for the creation of barcoded microparticles with complex morphologies and chemical compositions which have been shown to be useful in a range of multiplexed bioassay applications. More specifically, FL has been highly successful in producing micron-sized, encoded particles of bespoke shape, size, and color. That said, to date, FL has been restricted to generating barcoded microparticles and has lacked the ability to produce hybrid fibers which are structurally and spectrally encoded. To this end, we herein present a method that combines a continuous flow microfluidic system with two-photon polymerization (2PP) to fabricate microscale-encoded fibers and Janus strips in a high-throughput manner. Specifically, two co-flow liquid streams containing a monomer and initiator are introduced through a Y-shape channel to form a stable interface in the center of a microfluidic channel. The flow containing the (fluorescently labeled) monomer is then patterned by scanning the voxel of the 2PP laser across the interface to selectively polymerize different regions of the forming fiber/particle. Such a process allows for rapid spectral encoding at the single fiber level, with the resulting structurally coded fibers having obvious application in the fields of security identification and anticounterfeiting.

Biometric key generation based on generated intervals and two-layer error correcting technique

As for a biometric key, key management and biometric data security are both important. Existing bio-key generation methods are usually based on the biometric templates or features directly, it may expose user’s biometric data and will further make the biometric data permanently unusable for his secure identification recognitions. In this paper, a fingerprint bio-key generation approach using the feature distance is proposed. We utilize the relative distances among user’s fingerprint minutiae to generate a unique bio-key. Such bio-key is determinable and recoverable via the generation interval scheme. In addition, we use a two-layer error correcting technique to guarantee a better reliability during the data transmission. The experimental results positively show that our approach can ensure higher security of the bio-key and guarantee a good key regeneration rate. Besides, the storage of the original bio-key or any fingerprint template is unnecessary.

An Intelligent, Secure, and Smart Home Automation System

The idea of a smart home is getting attention for the last few years. The key challenges in a smart home are intelligent decision making, secure identification, and authentication of the IoT devices, continuous connectivity, data security, and privacy issues. The existing systems are targeting one or two of these issues whereas a smart home automation system that is not only secure but also has intelligent decision making and analytical abilities is the need of time. In this paper, we present a novel idea of a smart home that uses a machine learning algorithm (Support Vector Machine) for intelligent decision making and also uses blockchain technology to ensure identification and authentication of the IoT devices. Emerging blockchain technology plays a vital role by providing a reliable, secure, and decentralized mechanism for identification and authentication of the IoT devices used in the proposed home automation system. Moreover, the SVM classifier is applied to classify the status of devices used in the proposed smart home automation system into one of the two categories, i.e., “ON” and “OFF.” This system is based on Raspberry Pi, 5 V relay circuit, and some sensors. A mobile application is developed using the Android platform. Raspberry Pi acting as the server maintains the database of each appliance. The HTTP web interface and apache server are used for communication among the Android app and Raspberry Pi. The proposed idea is tested in the lab and real life to validate its effectiveness and usefulness. It is also ensured that the hardware and technology used in the proposed idea are cheap, easily available, and replicable. The experimental results highlight its significance and validate the proof of the concept.

Cruel traces: Bone surface modifications and their relevance to forensic science

AbstractThe reconstruction of perimortem and postmortem events is of critical importance to criminal investigations. In many cases, the information required for these reconstructions can be accessed through the analysis of skeletal remains. One particular class of skeletal data—trauma to the surfaces of bones, or bone surface modifications (BSMs)—can reveal much about the perimortem and postmortem intervals. While the study of BSMs originated within the fields of paleontology and archeology and was only later integrated into forensic science, a fruitful interdisciplinary exchange of data and methods is now commonplace. BSMs from thermal alteration, sharp‐force trauma, terrestrial and aquatic scavengers and predators, bacteria and fungi, insects, weathering, and sediment abrasion can supply investigators with valuable information about the agents and events of a corpse's deposition, including weapon type, local environmental conditions, the postmortem interval, and the presence, temperature(s), and/or length(s) of thermal exposure. Based on a review of this rich body of literature, we argue that (a) all associations between a BSM and its alleged source must rest on observational cause‐and‐effect studies; (b) secure identifications of BSMs should rely both on the intrinsic features of the modifications themselves and relevant contextual data; (c) the scientific validity of BSM research depends, ultimately, on rigorous blind‐testing and the establishment of error rates; and (d) researchers need to make a concerted effort to enhance interanalyst correspondence through objective definitions, measurements, and/or codes of BSM features. The most promising path forward lies in the combination of digital image analysis and multivariate predictive modeling.This article is categorized under: Forensic Anthropology > Trauma Analysis Forensic Anthropology > Taphonomic Changes and the Environment Forensic Anthropology > Time Since Death Estimation

INVASIVE YET INEVITABLE? PRIVACY NORMALIZATION TRENDS IN EMERGING TECHNOLOGY

In the last few years, smart security and physical identification technologies have grown exponentially; people are increasingly installing smart video devices to monitor their homes and buying DNA kits to collect and analyze their genetics. As the number of users and profits of these businesses increase, so too does the potential for privacy violations and exploitation. To explore these dynamics of privacy in emerging technology, we conducted a U.S. nationally representative survey (N=1,587) and asked respondents for their perceptions of a number of emerging technologies such as facial recognition, DNA collection and biometrics monitoring. We also measured individual-level traits that have been found to influence technology acceptance. The results show that the actor wielding the technology matters for people’s acceptance. Respondents were overall more comfortable with public officials and airlines using more invasive technologies to guarantee people’s safety, as compared to private companies or non-profits using data for research. When keeping the actor constant across privacy technologies, there was an overwhelming preference for less invasive means of privacy data sharing. These findings indicate how the concept of normalization, social context and agents of control play a critical role in the way people accept emerging technology into their lives.

Assessment of nerve stimulation during thyroidectomy for identification of the external branch of superior laryngeal nerve

Background The external branch of the superior laryngeal nerve (EBSLN) injury is an important and not uncommon, though frequently overlooked, complication of thyroid surgery. The rate of EBSLN injury has been reported to vary from 0 to 58%, depending on different postoperative assessment methods. Injury to the EBSLN during thyroid operation can paralyze ipsilateral cricothyroid muscle, and the clinical symptoms mainly include vocal fatigue and diminished vocal frequency range, especially with respect to raising pitch, which may result in decreased quality of life, particularly for voice professionals. Patients and methods This prospective study included 22 patients with goiter. They were divided into two groups: group 1 (G1) included all cases in whom nerve stimulator was used and group 2 (G2) included all cases in whom trial of visual identification of the EBSLN was done. Results It was found that patients with short obese neck, large gland size, large gland weight, and retrosternal extension showed difficulty in EBSLN identification and had high risk of nerve injury (P Conclusion It was concluded that routine use of nerve stimulator in surgical interventions on the thyroid gland will be beneficial for more secure identification and prevention of EBSLN injury and preservation of voice quality postoperatively.

Zero-Chain: A Blockchain-Based Identity for Digital City Operating System

The challenges of population management as urban density increase globally have compelled researchers and developers to consider more efficient means of managing resources in cities. Consequently, the smart city concept has emerged as a response to addressing the challenge of optimal resource utilization in urban centers. However, with digital technologies proliferating as key components of the solution, it is necessary to develop a digital identity solution for all components of the smart city environment. For completeness, the solution must encompass all entities, including physical and intangible assets, processes, and most importantly, its residents. Consequently, a unified, distributed data integration and efficient analysis platform is required: the digital city operating system. In this article, we focus on a key component of digital city management in the form of secure identification of individual residents. We collect user attributes and securely transmit them to other system components for verification. Upon successful completion of the verification process, a digital identity is created for the applying resident and the set of transactions leading to the ID creation are stored in the blockchain. Our system is secure and can serve as the basis for the development of a digital infrastructure for smart city management.

Intelligent complex security management system FEC for the Industry 5.0

Taking into account the digital transformation, the prospects for the development of intelligent complex security management system FEC are revealed. For the first time a definition of intelligent complex security management system FEC is given, also, its generalized structure is developed, considering the development of the Russian human-machine concept, as a complex information-energy system, on the basis of intellectualization of theoretical principles of human physiology and psychology. Its main elements are defined: a core, subsystems and components and mathematical dependencies implementing management functions are given. The core, subsystems and components are represented by the protected system at the level of security threat management in the form of a block-functional system scheme with elements of artificial intelligence that differ in the detail level. The mutual influence mechanism of separate subsystems and components is defined through simple, hybrid and complex threats. Besides, system threats of FEC were classified and their definitions were given. As an example, we consider the complex threat related to security of critical information FEC infrastructure. What is more, the basic intelligent management principles of complex FEC security are formulated, based on the block-functional system scheme with artificial intelligence elements and operator state security Identification in real time. We obtained general equations of the output state variables vector, which is equivalent to the security model of the operator, vectors of output state variables in case of hybrid, complex, and system FEC threats.

Exploiting Channel Distortion for Transmitter Identification for In-Vehicle Network Security

Exploiting Channel Distortion for Transmitter Identification for In-Vehicle Network Security

Flexible, switchable and wearable image storage device based on light responsive textiles

Materials with reversible optical properties under light irradiation have great potential application in various optoelectronic fields. Particularly, photochromic materials have received extensive attention in many fields. Herein, a novel composite photochromic fabric was fabricated via Layer-by-Layer self-assembling of phosphomolybdic acid (PMoA) and polyacrylamide (PAM). Based on the established electron transfer photochromic system, the dynamic manipulation of photochromic behavior of the cotton fabric was achieved with outstanding fine high-resolution image under the visible light irradiation. The prepared fabric can change from colorless to blue rapidly (within 5 min) under UV light and maintain excellent reusability photochromic performance after more than 20 reversible color changing cycles, implying its great potential applications in the field of intelligent devices and UV detection in sunlight. Moreover, we constructed fabric weaving and developed a Quick Response (QR) code security identification to prove the practical application of the prepared photochromic fabric in the fields of wearable, optical information storage and information security encryption.

MALDI-TOF MS: optimization for future uses in entomological surveillance and identification of mosquitoes from New Caledonia

BackgroundMosquito vectors cause a significant human public health burden through the transmission of pathogens. Due to the expansion of international travel and trade, the dispersal of these mosquito vectors and the pathogens they carry is on the rise. Entomological surveillance is therefore required which relies on accurate mosquito species identification. This study aimed to optimize the use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for mosquito identification.MethodsAedes aegypti of the Bora-Bora strain and 11 field-sampled mosquito species were used in this study. Analyses were performed to study the impact of the trapping duration on mosquito identification with MALDI-TOF MS. The best preservation methods to use for short, medium and long-term preservation before MALDI-TOF MS analysis were also assessed. In addition, the number of specimens per species required for MALDI-TOF MS database creation was determined. The first MALDI-TOF database of New Caledonian mosquitoes was assembled and the optimal threshold for mosquito species identification according to the sensitivity and specificity of this technique was determined.ResultsThis study showed that the identification scores decreased as the trapping duration increased. High identification scores were obtained for mosquitoes preserved on silica gel and cotton at room temperature and those frozen at − 20 °C, even after two months of preservation. In addition, the results showed that the scores increased according to the number of main spectrum patterns (MSPs) used until they reached a plateau at 5 MSPs for Ae. aegypti. Mosquitoes (n = 67) belonging to 11 species were used to create the MALDI-TOF reference database. During blind test analysis, 96% of mosquitoes tested (n = 224) were correctly identified. Finally, based on MALDI-TOF MS sensitivity and specificity, the threshold value of 1.8 was retained for a secure identification score.ConclusionsMALDI-TOF MS allows accurate species identification with high sensitivity and specificity and is a promising tool in public health for mosquito vector surveillance.

HEnRY: a DZIF LIMS tool for the collection and documentation of biomaterials in multicentre studies

BackgroundWell-characterized biomaterials of high quality have great potential for acceleration and quality improvement in translational biomedical research. To improve accessibility of local sample collections, efforts have been made to create central biomaterial banks and catalogues. Available technical solutions for creating professional local sample catalogues and connecting them to central systems are cost intensive and/or technically complex to implement. Therefore, the Translational Thematic Unit HIV of the German Center for Infection Research (DZIF) developed a Laboratory Information and Management System (LIMS) called HIV Engaged Research Technology (HEnRY) for implementation into the Translational Platform HIV (TP-HIV) at the DZIF and other research networks.ResultsHEnRY is developed at the University Hospital of Cologne. It is an advanced LIMS to manage processing and storage of samples and aliquots of different sample types. Features include:monitoring of stored samples and associated informationdata selection via query tools or Structured Query Language (SQL)preparation of summary documents, including scannable search listscentralized management of the practical laboratory part of multicentre studies (e.g. import of drawing schemes and sample processing steps),preparation of aliquot shipments, including associated documents to be added to shipmentsunique and secure identification of aliquots through use of customizable Quick Response (QR) code labels directly from HEnRYsupport of aliquot data transmission to central registries.In summary, HEnRY offers all features necessary for a LIMS software. In addition, the structure of HEnRY provides sufficient flexibility to allow the implementation in other research areas.ConclusionHEnRY is a free biobanking tool published under the MIT license. While it was developed to support HIV research in Germany, the feature set and language options, allow much broader applications and make this a powerful free research tool.

House style recognition using deep convolutional neural network

The recent development in deep learning has opened up a new era of possibilities, once difficult to achieve with conventional methods, to revolutionize image recognition, speech recognition, and natural language processing. Specifically, image recognition has been widely applied in various areas such as face recognition, object identification for security, and other purposes. Although it is rarely applied to discover new methods for use in architecture, image recognition has great potential in architectural design. For example, it can be used to identify the preference of the client and to design a building that satisfies a client's aesthetic preference.One of the major hurdles of utilizing image recognition in architecture is the architectural styles based on culture, location, and time. For that reason, it is difficult to identify an architectural style by non-trained clients and sometimes certain buildings are composed of different styles that are difficult to identify by experts as one style.This paper explores the possibility of using state-of-the-art image recognition algorithms in house style recognition to find out its limitations and possibilities. Moreover, the paper adopted a convolutional neural network model for classifying house styles in the US. Although the final accuracy is not high due to the lack of image datasets, the trained model performed reasonable predictions with a limited test set. The results show the importance of properly defining style for image recognition to improve its accuracy.

REAL TIME EYE TRACKING FOR PASSWORD AUTHENTICATION

The Generality of today’s authentication systems, including password , fingerprint scanners and Personal Identification Number(PIN) entry, are based on one time, static authentication methods which are prone to attacks. Real time eye tracking contributes significantly for Patients who are incapacitated, internet study , gaze based password entry as well as house hold security applications. The use of real time eye tracking and password authentication system has a wider possibility for reliability, but in this case the system must be secure and restrained for Eye Detection and Tracking. For the user’s security and validation (authentication) personal identification numbers are used abroad thereby reducing the chances of being attacked. In static authentication methods , since the password has to be entered physically using PIN’s there are possibilities for tracking the password using shoulder surfing, in order to avoid this spy game of tracking the password , hands off gaze- based PIN entry techniques are used. The smart camera is used to detect the eye position and for Gaze-based PIN Identification thereby doing the data processing. This project is focused on a real time hands off and gaze based PIN entry , detecting the eye position and tracking the eye movement using the smart camera.

Nucleus preservation in early Ediacaran Weng'an embryo-like fossils, experimental taphonomy of nuclei and implications for reading the eukaryote fossil record.

The challenge of identifying fossilized organelles has long hampered attempts to interpret the fossil record of early eukaryote evolution. We explore this challenge through experimental taphonomy of nuclei in a living eukaryote and microscale physical and chemical characterization of putative nuclei in embryo-like fossils from the early Ediacaran Weng'an Biota. The fossil nuclei exhibit diverse preservational modes that differ in shape, presence or absence of an inner body and the chemistry of the associated mineralization. The nuclei are not directly fossilized; rather, they manifest as external moulds. Experimental taphonomy of epidermal cells from the common onion (Allium cepa) demonstrates that nuclei are more decay resistant than their host cells, generally maintaining their physical dimensions for weeks to months post-mortem, though under some experimental conditions they exhibit shrinkage and/or become shrouded in microbial biofilms. The fossil and experimental evidence may be rationalized in a single taphonomic pathway of selective mineralization of the cell cytoplasm, preserving an external mould of the nucleus that is itself resistant to both decay and mineral replication. Combined, our results provide both a secure identification of the Weng'an nuclei as well as the potential of a fossil record of organelles that might help arbitrate in long-standing debates over the relative and absolute timing of the evolutionary assembly of eukaryote-grade cells.

Two Fourteenth-Century Islamic Philosophers

Abstract Two handbooks were central to the study of philosophy in the Islamic world in the period from the thirteenth to the nineteenth centuries: the introductory Hidāyat al-ḥikma by Athīr al-Dīn al-Abharī (d. 663/1265), and the more advanced Ḥikmat al-ʿayn by Abharī’s student Najm al-Dīn al-Kātibī al-Qazwīnī (d. 675/1276). Two fourteenth-century scholars play an important part in the early commentary tradition on these two works: Ibn Mubārakshāh al-Bukhārī who wrote what was to become the standard commentary on Kātibī’s Ḥikmat al-ʿayn, and Mullāzāde al-Kharziyānī, who wrote an influential commentary on Abharī’s Hidāyat al-ḥikma. Despite the impact of the two commentaries, biographical information on their authors is sparse, and what has been written often confuses them with other figures. The present article attempts to review the available evidence, and to offer more secure identifications of the two commentators.

Locked Deduplication of Encrypted Data to Counter Identification Attacks in Cloud Storage Platforms

Deduplication of encrypted data is a significant function for both the privacy of stored data and efficient storage management. Several deduplication techniques have been designed to provide improved security or efficiency. In this study, we focus on the client-side deduplication technique, which has more advantages than the server-side deduplication technique, particularly in communication overhead, owing to conditional data transmissions. From a security perspective, poison, dictionary, and identification attacks are considered as threats against client-side deduplication. Unfortunately, in contrast to other attacks, identification attacks and the corresponding countermeasures have not been studied in depth. In identification attacks, an adversary tries to identify the existence of a specific file. Identification attacks should be countered because adversaries can use the attacks to break the privacy of the data owner. Therefore, in the literature, some counter-based countermeasures have been proposed as temporary remedies for such attacks. In this paper, we present an analysis of the security features of deduplication techniques against identification attacks and show that the lack of security of the techniques can be eliminated by providing uncertainness to the conditional responses in the deduplication protocol, which are based on the existence of files. We also present a concrete countermeasure, called the time-locked deduplication technique, which can provide uncertainness to the conditional responses by withholding the operation of the deduplication functionality until a predefined time. An additional cost for locking is incurred only when the file to be stored does not already exist in the server’s storage. Therefore, our technique can improve the security of client-side deduplication against identification attacks at almost the same cost as existing techniques, except in the case of files uploaded for the first time.