Search results for: biometric authentication

Authors: Nidal F. Shilbayeh, Sameh T. Khuffash, Mohammad H. Allymoun, Reem Al-Saidi

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There is a real threat on the VIPs personal pages on the Social Network Sites (SNS). The real threats to these pages is violation of privacy and theft of identity through creating fake pages that exploit their names and pictures to attract the victims and spread of lies. In this paper, we propose a new secure architecture that improves the trusting and finds an effective solution to reduce fake pages and possibility of recognizing VIP pages on SNS. The proposed architecture works as a third party that is added to Facebook to provide the trust service to personal pages for VIPs. Through this mechanism, it works to ensure the real identity of the applicant through the electronic authentication of personal information by storing this information within content of their website. As a result, the significance of the proposed architecture is that it secures and provides trust to the VIPs personal pages. Furthermore, it can help to discover fake page, protect the privacy, reduce crimes of personality-theft, and increase the sense of trust and satisfaction by friends and admirers in interacting with SNS.

Keywords: social network sites, online social network, privacy, trust, security and authentication

Procedia PDF Downloads 356

Authors: J. U. Santhosh Kumar, V. Krishna, Sebin Sebastian, G. S. Seethapathy, G. Ravikanth, R. Uma Shaanker

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Food is one of the basic needs of human beings. It requires the normal function of the body part and a healthy growth. Recently, food adulteration increases day by day to increase the quantity and make more benefit. Animal source foods can provide a variety of micronutrients that are difficult to obtain in adequate quantities from plant source foods alone. Particularly in the meat industry, products from animals are susceptible targets for fraudulent labeling due to the economic profit that results from selling cheaper meat as meat from more profitable and desirable species. This work presents an overview of the main PCR-based techniques applied to date to verify the authenticity of beef meat and meat products from beef species. We were analyzed 25 market beef samples in South India. We examined PCR methods based on the sequence of the cytochrome b gene for source species identification. We found all sample were sold as beef meat as Bos Taurus. However, interestingly Male meats are more valuable high price compare to female meat, due to this reason most of the markets samples are susceptible. We were used sex determination gene of cattle like TSPY(Y-encoded, testis-specific protein TSPY is a Y-specific gene). TSPY homologs exist in several mammalian species, including humans, horses, and cattle. This gene is Y coded testis protein genes, which only amplify the male. We used multiple PCR products form species-specific “fingerprints” on gel electrophoresis, which may be useful for meat authentication. Amplicons were obtained only by the Cattle -specific PCR. We found 13 market meat samples sold as female beef samples. These results suggest that the species-specific PCR methods established in this study would be useful for simple and easy detection of adulteration of meat products.

Keywords: authentication, meat products, species-specific, TSPY

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Authors: Mujahid Muhammad, Paul Kearney, Adel Aneiba

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The ability for vehicles to communicate with other vehicles (V2V), the physical (V2I) and network (V2N) infrastructures, pedestrians (V2P), etc. – collectively known as V2X (Vehicle to Everything) – will enable a broad and growing set of applications and services within the intelligent transport domain for improving road safety, alleviate traffic congestion and support autonomous driving. The telecommunication research and industry communities and standardization bodies (notably 3GPP) has finally approved in Release 14, cellular communications connectivity to support V2X communication (known as LTE – V2X). LTE – V2X system will combine simultaneous connectivity across existing LTE network infrastructures via LTE-Uu interface and direct device-to-device (D2D) communications. In order for V2X services to function effectively, a robust security mechanism is needed to ensure legal and safe interaction among authenticated V2X entities in the LTE-based V2X architecture. The characteristics of vehicular networks, and the nature of most V2X applications, which involve human safety makes it significant to protect V2X messages from attacks that can result in catastrophically wrong decisions/actions include ones affecting road safety. Attack vectors include impersonation attacks, modification, masquerading, replay, MiM attacks, and Sybil attacks. In this paper, we focus our attention on LTE-based V2X security and access control mechanisms. The current LTE-A security framework provides its own access authentication scheme, the AKA protocol for mutual authentication and other essential cryptographic operations between UEs and the network. V2N systems can leverage this protocol to achieve mutual authentication between vehicles and the mobile core network. However, this protocol experiences technical challenges, such as high signaling overhead, lack of synchronization, handover delay and potential control plane signaling overloads, as well as privacy preservation issues, which cannot satisfy the adequate security requirements for majority of LTE-based V2X services. This paper examines these challenges and points to possible ways by which they can be addressed. One possible solution, is the implementation of the distributed peer-to-peer LTE security mechanism based on the Bitcoin/Namecoin framework, to allow for security operations with minimal overhead cost, which is desirable for V2X services. The proposed architecture can ensure fast, secure and robust V2X services under LTE network while meeting V2X security requirements.

Keywords: authentication, long term evolution, security, vehicle-to-everything

Procedia PDF Downloads 146

Authors: Mai Anh Tuan, Wenlong Liu, Meng Li

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Despite warnings and concerns about the use of fast food that has health effects, the fast-food industry is actually a source of profit for the global food industry. Obviously, in the face of such huge economic benefits, investors will not hesitate to continuously add recipes, processing methods, menu diversity, etc., to improve and apply information technology in enhancing the diners' experience; the ultimate goal is still to attract diners to find their brand and give them the fastest, most convenient and enjoyable service. In China, as the achievements of the industrial revolution 4.0, big data and artificial intelligence are reaching new heights day by day, now fast-food diners can instantly pay the bills only by identifying the biometric signature available on the self-ordering kiosk, using their own face without any additional form of confirmation. In this study, the author will evaluate the acceptance level of customers with this new form of payment through a survey of customers who have used and witnessed the use of smart kiosks and biometric payments within the city of Nanjing, China. A total of 200 valid volunteers were collected in order to test the customers' intentions and feelings when choosing and experiencing payment through AI services. 55% think that it bothers them because of the need for personal information, but more than 70% think that smart kiosk brings out many benefits and convenience. According to the data analysis findings, perceived innovativeness has a positive influence on satisfaction which in turn affects behavioral intentions, including reuse and word-of-mouth intentions.

Keywords: artificial intelligence, catering industry, smart kiosks, technology acceptance

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Authors: Mohd Sukri Hassan, Ahlam Inayatullah Badrul Munir, M. Husaini A. Rahman

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Halal authentication and verification in supplement capsules are highly required as the gelatine available in the market can be from halal or non-halal sources. It is an obligation for Muslim to consume and use the halal consumer goods. At present, real-time polymerase chain reaction (RT-PCR) is the most common technique being used for the detection of porcine and bovine DNA in gelatine due to high sensitivity of the technique and higher stability of DNA compared to protein. In this study, twenty samples of supplements capsules from different products with different Halal logos were analyzed for porcine and bovine DNA using RT-PCR. Standard bovine and porcine gelatine from eurofins at a range of concentration from 10^-1 to 10^-5 ng/µl were used to determine the linearity range, limit of detection and specificity on RT-PCR (SYBR Green method). RT-PCR detected porcine (two samples), bovine (four samples) and mixture of porcine and bovine (six samples). The samples were also tested using FT-IR technique where normalized peak of IR spectra were pre-processed using Savitsky Golay method before Principal Components Analysis (PCA) was performed on the database. Scores plot of PCA shows three clusters of samples; bovine, porcine and mixture (bovine and porcine). The RT-PCR and FT-IR with chemometrics technique were found to give same results for porcine gelatine samples which can be used for Halal authentication.

Keywords: halal, real-time PCR, gelatine, chemometrics

Procedia PDF Downloads 204

Authors: A. Smaï, H. Idouhar-Saadi, S. Zenia, F. Haddadj, A. Aboun, S.Doumandji

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The quail is the smallest member of the order fowl. His captive breeding has been practiced for centuries by the Japanese. Knowing that in the literature, it is mentioned that the end of lay is noted for the age of 6 months, our work has revealed a good egg production by females aged up to 35 weeks of age. In the same vein, our study focused on various parameters such as weight, diet and the number of eggs laid and this in order to better know the potential production and reproduction of domestic quail. Egg production has started from the 8th week of age of breeding, crop them and their counts are conducted daily basis until the age of 35 weeks. Indeed, biometric parameters are studied such as weight, length, and the largest diameter, the shape index, the index of shell, in order to analyze the physical condition of eggs by females of age. Until the age of 22 weeks, the eggs have maintained good biometric features. Japanese quail are best producing eggs. Hatchability is also considered. They are excellent poultry yields, since they begin laying eggs in two months and can provide abundant nesting with females over 8 months in our study. Other farms results reveal conclusions. Indeed, one aspect remains to be developed; it is the analysis of nutritional and therapeutic values of eggs over the age of females. The latter, given their wealth is a dietary supplement of animal origin with dietary value (it contains 0 cholesterol) that characterizes the quail eggs. Raising quail among other reproduction requires minimal when compared to other domestic birds space, this is the second breeding, in terms of importance after the chicken. Therefore, in the case of a farm that works exclusively in the production of eggs, requires minimal work and free space, as well as reduced costs.

Keywords: Japanese quail, reproduction, eggs, biometrics, reproductive age

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

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Authors: Amina Smaï, Habiba Idouhar-Saadi, Safia Zenia, Fairouz Haddadj, Salaheddine Doumandji

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The poultry industry (chicken and egg consumption) has become important in Algeria, but that does not prevent other farms from beginning to position themselves on the ground like the turkey, guinea fowl, partridge and quail Japanese. The breeding importance of this last, reside, also in game meat, egg quality and their therapeutic role without forgetting its growth performance. To the same effect, a study was held at the center of Zeralda hunting on various parameters such as the weight and number of eggs laid and this in order to know better the potential of production and reproduction of domestic quail. Egg laying has started from the 8th week of reproductive age, their harvest and their counts are performed daily up to 32 weeks of age and more. We have given the biometrics of incubated eggs and unhatched eggs. The parameters studied were the weight, large and small diameter, density, volume, shell index and the shape index. The work revealed that the maximum weight in males is reached in the 11th week, against the female, he reached the 13th week of age. Indeed, there is a good correlation (R = 0.79) between the weight of females and egg production. The rate of unhatched eggs varies between 11 and 43%, these values are recorded respectively in breeding under the age of 25 and 43 weeks. Furthermore, the biometric parameters of hatched and unhatched eggs have differences that are marked, especially during the beginning and end of lay. Further results will be subsequently exploited. Indeed, rearing Japanese quail is easy in technical terms and does not require big investment but its practical application vigilance and daily presence of the breeder within the farm who oversees the hygiene and well-being of its poultry.

Keywords: Japanese quail, biometrics, eggs, unhatching eggs, reproduction

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Authors: Mokopane Charles Marakalala

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Research shows that mobile fraud has grown exponentially in South Africa during the lockdown caused by the COVID-19 pandemic. According to the South African Banking Risk Information Centre (SABRIC), fraudulent online banking and transactions resulted in a sharp increase in cybercrime since the beginning of the lockdown, resulting in a huge loss to the banking industry in South Africa. While the Financial Intelligence Centre Act, 38 of 2001, regulate financial transactions, it is evident that criminals are making use of technology to their advantage. Money-laundering ranks among the major crimes, not only in South Africa but worldwide. This paper focuses on the impact of biometric-based solutions in combatting mobile fraud at the South African Risk Information. SABRIC had the challenges of a successful mobile fraud; cybercriminals could hijack a mobile device and use it to gain access to sensitive personal data and accounts. Cybercriminals are constantly looting the depths of cyberspace in search of victims to attack. Millions of people worldwide use online banking to do their regular bank-related transactions quickly and conveniently. This was supported by the SABRIC, who regularly highlighted incidents of mobile fraud, corruption, and maladministration in SABRIC, resulting in a lack of secure their banking online; they are vulnerable to falling prey to fraud scams such as mobile fraud. Criminals have made use of digital platforms since the development of technology. In 2017, 13 438 instances involving banking apps, internet banking, and mobile banking caused the sector to suffer gross losses of more than R250,000,000. The final three parties are forced to point fingers at one another while the fraudster makes off with the money. A non-probability sampling (purposive sampling) was used in selecting these participants. These included telephone calls and virtual interviews. The results indicate that there is a relationship between remote online banking and the increase in money-laundering as the system allows transactions to take place with limited verification processes. This paper highlights the significance of considering the development of prevention mechanisms, capacity development, and strategies for both financial institutions as well as law enforcement agencies in South Africa to reduce crime such as money-laundering. The researcher recommends that strategies to increase awareness for bank staff must be harnessed through the provision of requisite training and to be provided adequate training.

Keywords: biometric-based solution, investigation, cybercrime, forensic investigation, fraud, combatting

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Authors: Kevin V. Bui, Richard A. Claytor, Elizabeth M. Priolo, Weihui Li

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Oxygen deprivation masks operate through the use of restricting valves as a means to reduce respiratory flow where flow is inversely proportional to the resistance applied. This produces the same effect as higher altitudes where lower pressure leads to reduced respiratory flow. Both increased resistance with restricting valves and reduce the pressure of higher altitudes make breathing difficultier and force breathing muscles (diaphragm and intercostal muscles) working harder. The process exercises these muscles, improves their strength and results in overall better breathing efficiency. Currently, these oxygen deprivation masks are purely mechanical devices without any electronic sensor to monitor the breathing condition, thus not be able to provide feedback on the breathing effort nor to evaluate the lung function. That is part of the reason that these masks are mainly used for high-level athletes to mimic training in higher altitude conditions, not suitable for patients or customers. The design aims to improve the current method of oxygen deprivation mask to include a larger scope of patients and customers while providing quantitative biometric data that the current design lacks. This will be accomplished by integrating sensors into the mask’s breathing valves along with data acquisition and Bluetooth modules for signal processing and transmission. Early stages of the sensor mask will measure breathing rate as a function of changing the air pressure in the mask, with later iterations providing feedback on flow rate. Data regarding breathing rate will be prudent in determining whether training or therapy is improving breathing function and quantify this improvement.

Keywords: oxygen deprivation mask, lung function, spirometer, Bluetooth

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Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Tomokazu Nagata, Jawid Ahmad Baktash

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The goal of this paper is to explore the use of formal methods for Electronic Identity Card System. Nowadays, one of the core research directions in a constantly growing distributed environment is the improvement of the communication process. The responsibility for proper verification becomes crucial. Formal methods can play an essential role in the development and testing of systems. The thesis presents two different methodologies for assessing correctness. Our first approach employs abstract interpretation techniques for creating a trace based model for Electronic Identity Card System. The model was used for building a semi decidable procedure for verifying the system model. We also developed the code for the eID System and can cover three parts login to system sending of Acknowledgment from user side, receiving of all information from server side and log out from system. The new concepts of impasse and spawned sessions that we introduced led our research to original statements about the intruder’s knowledge and eID system coding with respect to secrecy. Furthermore, we demonstrated that there is a bound on the number of sessions needed for the analysis of System.Electronic identity (eID) cards promise to supply a universal, nation-wide mechanism for user authentication. Most European countries have started to deploy eID for government and private sector applications. Are government-issued electronic ID cards the proper way to authenticate users of online services? We use the eID project as a showcase to discuss eID from an application perspective. The new eID card has interesting design features, it is contact-less, it aims to protect people’s privacy to the extent possible, and it supports cryptographically strong mutual authentication between users and services. Privacy features include support for pseudonymous authentication and per service controlled access to individual data items. The article discusses key concepts, the eID infrastructure, observed and expected problems, and open questions. The core technology seems ready for prime time and government projects deploy it to the masses. But application issues may hamper eID adoption for online applications.

Keywords: eID, event-B, Pro-B, formal method, message passing

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Authors: Marijana M. Ačanski, Kristian A. Pastor, Djura N. Vujić

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The identification of lipid and soluble sugar components in flour samples of different cultivars belonging to common oat species (Avena sativa L.) was performed: spring oat, winter oat and hulless oat. Fatty acids were extracted from flour samples with n-hexane, and derivatized into volatile methyl esters, using TMSH (trimethylsulfonium hydroxide in methanol). Soluble sugars were then extracted from defatted and dried samples of oat flour with 96% ethanol, and further derivatized into corresponding TMS-oximes, using hydroxylamine hydrochloride solution and BSTFA (N,O-bis-(trimethylsilyl)-trifluoroacetamide). The hexane and ethanol extracts of each oat cultivar were analyzed using GC-MS system. Lipid and simple sugar compositions are very similar in all samples of investigated cultivars. Chemometric tool was applied to numeric values of automatically integrated surface areas of detected lipid and simple sugar components in their corresponding derivatized forms. Hierarchical cluster analysis shows a very high similarity between the investigated flour samples of oat cultivars, according to the fatty acid content (0.9955). Moderate similarity was observed according to the content of soluble sugars (0.50). These preliminary results support the idea of establishing methods for oat flour authentication, and provide the means for distinguishing oat flour samples, regardless of the variety, from flour samples made of other cereal species, just by lipid and simple sugar profile analysis.

Keywords: oat cultivars, lipid composition, soluble sugar composition, GC-MS, chemometrics, authentication

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Authors: B. S. Akhmetov, S. T. Akhmetova, A. I. Ivanov, T. S. Kartbayev, A. Y. Malygin

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The problem of training of a network of artificial neurons in biometric appendices is that this process has to be completely automatic, i.e. the person operator should not participate in it. Therefore, this article discusses the issues of training the network of artificial neurons and the description of the non-iterative learning algorithm of artificial neuron.

Keywords: artificial neuron, biometrics, biometrical applications, learning of neuron, non-iterative algorithm

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Authors: Olakanmi Oladayo Olufemi, Bamifewe Olusegun James, Badmus Yaya Opeyemi, Adegoke Kayode

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The wireless sensor network (WSN) has made a significant contribution to the emergence of various intelligent services or cloud-based applications. Most of the time, these data are stored on a cloud platform for efficient management and sharing among different services or users. However, the sensitivity of the data makes them prone to various confidentiality and performance-related attacks during and after harvesting. Various security schemes have been developed to ensure the integrity and confidentiality of the WSNs' data. However, their specificity towards particular attacks and the resource constraint and heterogeneity of WSNs make most of these schemes imperfect. In this paper, we propose a secure variance-aware routing and authentication scheme with two-tier verification to collect, share, and manage WSN data. The scheme is capable of classifying WSN into different subnets, detecting any attempt of wormhole and black hole attack during harvesting, and enforcing access control on the harvested data stored in the cloud. The results of the analysis showed that the proposed scheme has more security functionalities than other related schemes, solves most of the WSNs and cloud security issues, prevents wormhole and black hole attacks, identifies the attackers during data harvesting, and enforces access control on the harvested data stored in the cloud at low computational, storage, and communication overheads.

Keywords: data block, heterogeneous IoT network, data harvesting, wormhole attack, blackhole attack access control

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Authors: Soheir El-Shazly, Gouda Abdel-Gawad, Yasser Salama, Dina Sayed

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Twelve species belonging to genus Carolia Cantraine, 1838 were recorded from nine localities in the Tertiary rocks of the Tethys, Atlantic and Eastern Pacific Provinces. During The Eocene two species were collected from Indian-Pakistani region, two from North Africa (Libya, Tunis and Algeria), one from Jamaica and two from Peru. The Oligocene shows its appearance in North America (Florida) and Argentina. The genus showed its last occurrence in the Miocene rocks of North America (Florida) before its extinction. In Egypt, the genus was diversified in the Eocene rocks and was represented by four species and two subspecies. The paleobiogeographic distribution of Genus Carolia Cantraine, 1838 indicates that it appeared in the Lower Eocene of West Indian Ocean and migrated westward flowing circumtropical Tethys Current to the central Tethyan province, where it appeared in North Africa and continued its dispersal westward to the Atlantic Ocean and arrived Jamaica in the Middle Eocene. It persisted in the Caribbean Sea and appeared later in the Oligocene and Miocene rocks of North America (Florida). Crossing Panama corridor, the genus migrated to the south Eastern Pacific Ocean and was collected from the Middle Eocene of Peru. The appearance of the genus in the Oligocene of the South Atlantic Coast of Argentina may be via South America Seaway or its southward migration from Central America to Austral Basin. The thickening of the upper valve of the genus, after the loss of its byssus to withstand the current action, caused inability of the animal to carry on its vital activity and caused its extinction. The biometric study of Carolia placunoides Cantraine, 1938 from thhe Eocene of Egypt, indicates that the distance between the muscle scars in the upper valve increases with the closure of the byssal notch.

Keywords: Atlantic, carolia, paleobiogeography, tethys

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Authors: Hela Gargouri, Nizar Moalla, Hassen Hadj Kacem

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Meat adulteration affecting the safety and quality of food is becoming one of the main concerns of public interest across the world. The drastic consequences on the meat industry highlighted the urgent necessity to control the products' quality and to point out the complexity of both supply and processing circuits. Due to the expansion of this problem, the authentic testing of foods, particularly meat and its products, is deemed crucial to avoid unfair market competition and to protect consumers from fraudulent practices of meat adulteration. The adoption of authentication methods by the food quality-control laboratories is becoming a priority issue. However, in some developing countries, the number of food tests is still insignificant, although a variety of processed and traditional meat products are widely consumed. Little attention has been paid to provide an easy, fast, reproducible, and low-cost molecular test, which could be conducted in a basic laboratory. In the current study, the 359 bp fragment of the cytochrome-b gene was mapped by PCR-RFLP using firstly fresh biological supports (DNA and meat) and then turkey salami as an example of commercial processed meat. This technique has been established through several optimizations, namely: the selection of restriction enzymes. The digestion with BsmAI, SspI, and TaaI succeed to identify the seven included animal species when meat is formed by individual species and when the meat is a mixture of different origin. In this study, the PCR-RFLP technique using universal primer succeed to meet our needs by providing an indirect sequencing method identifying by restriction enzymes the specificities characterizing different species on the same amplicon reducing the number of potential tests.

Keywords: adulteration, animal species, authentication, meat, mtDNA, PCR-RFLP

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Authors: Krish Batra

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The advent of open banking has revolutionized the financial services industry by fostering innovation, enhancing customer experience, and promoting competition. However, this paradigm shift towards more open and interconnected banking ecosystems has introduced complex cybersecurity challenges. This research paper delves into the multifaceted cybersecurity landscape of open banking, highlighting the vulnerabilities and threats inherent in sharing financial data across a network of banks and third-party providers. Through a detailed analysis of recent data breaches, phishing attacks, and other cyber incidents, the paper assesses the current state of cybersecurity within the open banking framework. It examines the effectiveness of existing security measures, such as encryption, API security protocols, and authentication mechanisms, in protecting sensitive financial information. Furthermore, the paper explores the regulatory response to these challenges, including the implementation of standards such as PSD2 in Europe and similar initiatives globally. By identifying gaps in current cybersecurity practices, the research aims to propose a set of robust, forward-looking strategies that can enhance the security and resilience of open banking systems. This includes recommendations for banks, third-party providers, regulators, and consumers on how to mitigate risks and ensure a secure open banking environment. The ultimate goal is to provide stakeholders with a comprehensive understanding of the cybersecurity implications of open banking and to outline actionable steps for safeguarding the financial ecosystem in an increasingly interconnected world.

Keywords: open banking, financial services industry, cybersecurity challenges, data breaches, phishing attacks, encryption, API security protocols, authentication mechanisms, regulatory response, PSD2, cybersecurity practices

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Authors: Mojtaba Fayaz, Richard Hallal

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This study examines the various types of dangers that our virtual environment is vulnerable to, including how it can be attacked and how to avoid/secure our data. The terrain of cyberspace is never completely safe, and Covid- 19 has added to the confusion, necessitating daily periodic checks and evaluations. Cybercriminals have been able to enact with greater skill and undertake more conspicuous and sophisticated attacks while keeping a higher level of finesse by operating from home. Different types of cyberattacks, such as operation-based attacks, authentication-based attacks, and software-based attacks, are constantly evolving, but research suggests that software-based threats, such as Ransomware, are becoming more popular, with attacks expected to increase by 93 percent by 2020. The effectiveness of cyber frameworks has shifted dramatically as the pandemic has forced work and private life to become intertwined, destabilising security overall and creating a new front of cyber protection for security analysis and personal. The high-rise formats in which cybercrimes are carried out, as well as the types of cybercrimes that exist, such as phishing, identity theft, malware, and DDoS attacks, have created a new front of cyber protection for security analysis and personal safety. The overall strategy for 2022 will be the introduction of frameworks that address many of the issues associated with offsite working, as well as education that provides better information about commercialised software that does not provide the highest level of security for home users, allowing businesses to plan better security around their systems.

Keywords: cyber security, authentication, software, hardware, malware, COVID-19, threat actors, awareness, home users, confidentiality, integrity, availability, attacks

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Authors: Sultan Alharby, Nick Harris, Alex Weddell, Jeff Reeve

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The concept of the Internet of Things (IoT) has received much attention over the last five years. It is predicted that the IoT will influence every aspect of our lifestyles in the near future. Wireless Sensor Networks are one of the key enablers of the operation of IoTs, allowing data to be collected from the surrounding environment. However, due to limited resources, nature of deployment and unattended operation, a WSN is vulnerable to various types of attack. Security is paramount for reliable and safe communication between IoT embedded devices, but it does, however, come at a cost to resources. Nodes are usually equipped with small batteries, which makes energy conservation crucial to IoT devices. Nevertheless, security cost in terms of energy consumption has not been studied sufficiently. Previous research has used a security specification of 802.15.4 for IoT applications, but the energy cost of each security level and the impact on quality of services (QoS) parameters remain unknown. This research focuses on the cost of security at the IoT media access control (MAC) layer. It begins by studying the energy consumption of IEEE 802.15.4 security levels, which is followed by an evaluation for the impact of security on data latency and throughput, and then presents the impact of transmission power on security overhead, and finally shows the effects of security on memory footprint. The results show that security overhead in terms of energy consumption with a payload of 24 bytes fluctuates between 31.5% at minimum level over non-secure packets and 60.4% at the top security level of 802.15.4 security specification. Also, it shows that security cost has less impact at longer packet lengths, and more with smaller packet size. In addition, the results depicts a significant impact on data latency and throughput. Overall, maximum authentication length decreases throughput by almost 53%, and encryption and authentication together by almost 62%.

Keywords: energy consumption, IEEE 802.15.4, IoT security, security cost evaluation

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Authors: Chih-Ping Chang

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Different from traditional objective evidence, social media evidence has its own characteristics with easily tampering, recoverability, and cannot be read without using other devices (such as a computer). Simply taking a screenshot from social network sites must be questioned its original identity. When the police search and seizure digital information, a common way they use is to directly print out digital data obtained and ask the signature of the parties at the presence, without taking original digital data back. In addition to the issue on its original identity, this conduct to obtain evidence may have another two results. First, it will easily allege that is tampering evidence because the police wanted to frame the suspect and falsified evidence. Second, it is not easy to discovery hidden information. The core evidence associated with crime may not appear in the contents of files. Through discovery the original file, data related to the file, such as the original producer, creation time, modification date, and even GPS location display can be revealed from hidden information. Therefore, how to show this kind of evidence in the courtroom will be arguably the most important task for ruling social media evidence. This article, first, will introduce forensic software, like EnCase, TCT, FTK, and analyze their function to prove the identity with another digital data. Then turning back to the court, the second part of this article will discuss legal standard for authentication of social media evidence and application of that forensic software in the courtroom. As the conclusion, this article will provide a rethinking, that is, what kind of authenticity is this rule of evidence chase for. Does legal system automatically operate the transcription of scientific knowledge? Or furthermore, it wants to better render justice, not only under scientific fact, but through multivariate debating.

Keywords: federal rule of evidence, internet forensic, printouts as evidence, social media evidence, United States v. Vayner

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Authors: Kleche Myriam, Ziane Nadia, Berrebbah Houria, Djebar Mohammed Reda

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The Phytoremediation has now become a necessity. Thus, in our work, we are interested in the biological wastewater treatment of Oued Meboudja. The physicochemical analysis of water after treatment showed a significant reduction of suspended matter, COD and BOD5 and rate of metals in roots for example iron and zinc. We also highlighted some significant changes in biometric and physiological parameters such as increasing the number of roots and increased respiratory metabolism through the oxygen consumption in isolated roots of Phragmites australis, placed in a polluted environment.

Keywords: phragmites australis, roots, phytoremediation, iron, zinc

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Authors: Radka Sefcu, Vaclava Antuskova, Ivana Turkova

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A growing market with modern artworks of a high price leads to the creation and selling of artwork counterfeits. Material analysis is an important part of the process of assessment of authenticity. Knowledge of materials and techniques used by original authors is also necessary. The contribution presents possibilities of non-invasive methods of structural analysis in research on paintings. It was proved that unambiguous identification of many art materials is feasible without sampling. The combination of Raman spectroscopy with FTIR-external reflection enabled the identification of pigments and binders on selected artworks of prominent Czech painters from the first half of the 20th century – Josef Čapek, Emil Filla, Václav Špála and Jan Zrzavý. Raman spectroscopy confirmed the presence of a wide range of white pigments - lead white, zinc white, titanium white, barium white and also Freeman's white as a special white pigment of painting. Good results were obtained for red, blue and most of the yellow areas. Identification of green pigments was often impossible due to strong fluorescence. Oil was confirmed as a binding medium on most of the analyzed artworks via FTIR - external reflection. Collected data present the valuable background for the determination of art materials characteristic for each painter (his palette) and its development over time. Obtained results will further serve as comparative material for the authentication of artworks. This work has been financially supported by the project of the Ministry of the Interior of the Czech Republic: The Development of a Strategic Cluster for Effective Instrumental Technological Methods of Forensic Authentication of Modern Artworks (VJ01010004).

Keywords: non-invasive analysis, Raman spectroscopy, FTIR-external reflection, forgeries

Procedia PDF Downloads 147

Authors: Muhammad Mehran Arshad Khan, Chengliang Wang, Zou Minhui, Danyal Badar Soomro

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Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.

Keywords: authentication, key-session, security, wireless sensors

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Authors: Felix O. Omosele

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Several studies have established that electronic voting machines are prone to multi-faceted challenges. One of which is their capacity to lose votes after the ballots might have been cast. Therefore, the international consensus appears to favour the use of electronic voting machines that are accompanied with verifiable audit paper audit trail (VVPAT). At present, there is no known study that has evaluated the impacts (or otherwise) of this verification and auditing on the authentication, admissibility and evidential weight of electronically-obtained electoral data. This legal inquiry is important as elections are sometimes won or lost in courts and on the basis of such data. This gap will be filled by the present research work. Using the United States of America as a case study, this paper employed a qualitative legal analysis of several of its appellate courts’ judicial opinions. This analysis equally unearths the necessary statutory rules and regulations that are important to the research problem. The objective of the research is to highlight the roles played by VVPAT on electoral evidence- as seen from the eyes of the court. The preliminary outcome of this qualitative analysis shows that the admissibility and weight attached to ‘Computer Evidence from e-voting machines (CEEM)’ are often treated with general standards applied to other computer-stored evidence. These standards sometimes fail to embrace the peculiar challenges faced by CEEM, particularly with respect to their tabulation and transmission. This paper, therefore, argues that CEEM should be accorded unique consideration by courts. It proposes the development of a legal standard which recognises verification and auditing as ‘weight enhancers’ for electronically-obtained electoral data.

Keywords: admissibility of computer evidence, electronic voting, qualitative legal analysis, voting machines in the USA

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Authors: Dana Alina Magdas, Nicoleta Simona Vedeanu, Ioana Feher, Rares Stiufiuc

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Food and beverages authentication using rapid and non-expensive analytical tools represents nowadays an important challenge. In this regard, the potential of vibrational techniques in food authentication has gained an increased attention during the last years. For wines discrimination, Raman spectroscopy appears more feasible to be used as compared with IR (infrared) spectroscopy, because of the relatively weak water bending mode in the vibrational spectroscopy fingerprint range. Despite this, the use of Raman technique in wine discrimination is in an early stage. Taking this into consideration, the wine discrimination potential of surface-enhanced Raman scattering (SERS) technique is reported in the present work. The novelty of this study, compared with the previously reported studies, concerning the application of vibrational techniques in wine discrimination consists in the fact that the present work presents the wines differentiation based on the individual signals obtained from deconvoluted spectra. In order to achieve wines classification with respect to variety, geographical origin and vintage, the peaks intensities obtained after spectra deconvolution were compared using supervised chemometric methods like Linear Discriminant Analysis (LDA). For this purpose, a set of 20 white Romanian wines from different viticultural Romanian regions four varieties, was considered. Chemometric methods applied directly to row SERS experimental spectra proved their efficiency, but discrimination markers identification found to be very difficult due to the overlapped signals as well as for the band shifts. By using this approach, a better general view related to the differences that appear among the wines in terms of compositional differentiation could be reached.

Keywords: chemometry, SERS, variety, wines discrimination

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Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

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Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

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Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

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Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: biometrics, deep learning, handwriting, signature forgery

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Authors: Rashid Mahmood

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The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields.

Keywords: IDS, cloud, naas, detection

Procedia PDF Downloads 286

Authors: Priya Saha, Sourav Dey Roy Jr., Debotosh Bhattacharjee, Mita Nasipuri, Barin Kumar De, Mrinal Kanti Bhowmik

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Biometric face recognition technology (FRT) has gained a lot of attention due to its extensive variety of applications in both security and non-security perspectives. It has come into view to provide a secure solution in identification and verification of person identity. Although other biometric based methods like fingerprint scans, iris scans are available, FRT is verified as an efficient technology for its user-friendliness and contact freeness. Accurate facial feature localization plays an important role for many facial analysis applications including biometrics and emotion recognition. But, there are certain factors, which make facial feature localization a challenging task. On human face, expressions can be seen from the subtle movements of facial muscles and influenced by internal emotional states. These non-rigid facial movements cause noticeable alterations in locations of facial landmarks, their usual shapes, which sometimes create occlusions in facial feature areas making face recognition as a difficult problem. The paper proposes a new hybrid based technique for automatic landmark detection in both neutral and expressive frontal and near frontal face images. The method uses the concept of thresholding, sequential searching and other image processing techniques for locating the landmark points on the face. Also, a Graphical User Interface (GUI) based software is designed that could automatically detect 16 landmark points around eyes, nose and mouth that are mostly affected by the changes in facial muscles. The proposed system has been tested on widely used JAFFE and Cohn Kanade database. Also, the system is tested on DeitY-TU face database which is created in the Biometrics Laboratory of Tripura University under the research project funded by Department of Electronics & Information Technology, Govt. of India. The performance of the proposed method has been done in terms of error measure and accuracy. The method has detection rate of 98.82% on JAFFE database, 91.27% on Cohn Kanade database and 93.05% on DeitY-TU database. Also, we have done comparative study of our proposed method with other techniques developed by other researchers. This paper will put into focus emotion-oriented systems through AU detection in future based on the located features.

Keywords: biometrics, face recognition, facial landmarks, image processing

Procedia PDF Downloads 381