Enhancing banknote authentication by guiding attention to security features and manipulating prevalence expectancy

All banknotes have security features which are intended to help determine whether they are false or genuine. Typically, however, the general public has limited knowledge of where on a banknote these security features can be found. Here, we tested whether counterfeit detection can be improved with the help of salient elements, designed to guide bottom-up visuospatial attention. We also tested the influence of the participant’s a priori level of trust in the authenticity of the banknote. In an online study (N = 422), a demographically diverse panel of Dutch participants distinguished genuine banknotes from banknotes with one (left- or right-sided) counterfeited security feature. Either normal banknotes (without novel design elements) or banknotes that contained a salient element (a pink rectangular frame) were presented for 1 s. To manipulate the participant’s level of trust, trials were administered in three blocks, whereby at the start of each block, participants were instructed that either one third, one half, or two thirds of the upcoming banknotes were counterfeit (though the true ratio was always 1:1). We hypothesized (i) that in the presence of a salient element, counterfeits would be better detected when the location of the salient element aligned with the location of the counterfeited security feature—i.e. that it would act as an attentional cue; and (ii) that this effect would be stronger with lower trust. Our hypotheses were partly confirmed: counterfeit detection improved with ‘valid cues’ and decreasing trust, but the level of trust did not modulate the cueing effect. As the overall detection performance was rather poor, we replicated the study with a sample of university students (N = 66), this time presenting stimuli until response. While indeed observing better overall performance, all other patterns were replicated. Our results provide evidence that attention can be guided to enhance banknote authentication.

PaaS Platform Securityenhancement Using Fuzzy and Trust Based Signature

The study of PaaS platform security enhancement has occupied scholars from a number of disciplines, in previous works has so many security issues like Security problems can be a big barrier to cloud computing. System servers require trustworthy security measures to different data domains according to the system servers own operating mechanism. Problem is constructed by filtering out those cloud providers not conforming to high-level security requirements. By including low-level security requirements to be used for filtering the cloud provider space and formulating the optimisation function. To overcome all the above drawbacks our proposed work mainly focused on the security of Platform-as-a-Service (PaaS) as well as the most critical security issues that were documented regarding PaaS infrastructure. This work has two main aspects: First, suitable access control on user personal data, VMs and platform services and Second planning and adapting application deployments based on security requirements. In Fuzzy based access control to information sources is mainly realised by exploiting the CDO security feature. In Security feature code was modified to map the class and packet filter for any specific permission to our own class. If the Identity Provider (IdP) has included public security information on the two main parts in the small token on which Trust based Signature elements are placed, i.e., the whole token or the assertions included, this public key is used to validate the respective signature. The experimental results will show that our proposed method outperforms the traditional methods. Our proposed methodology was implemented in the platform of JAVA.

Evaluation of High Speed Communication Interfaces for Next Generation Secure Element

Secure element is a microprocessor chip that provides a secure environment to store the data, execute the applications and communicate the data to external entities securely. As secure element provides a promising security feature, it is used in various domains like IOT, automobile and mobile phones. Nowadays, the size of the security key and size of the data to be processed are increasing whereas the processing time of the secure element is expected to reduce. As the data size increases, the time to communicate the data between secure element and host increases. Host and secure element are connected via SPI over ISO IEC 7816-4 (T1) communication interface. In this paper, we evaluate the throughput of SPI over ISO IEC 7816-4 (T1) interface which is widely used in smart card domains. Throughput of the interface is evaluated by examining the time spent at communication interface for varying data size. We focus on understanding the parameters that affect the throughput of the SPI over T1 interface.

Smart Polling System

Smart polling system is an android application that facilitates user (voter), nominee and administrator (who will be in charge and will verify all the user information) to participate in online voting. Our smart polling system is highly secured, and it has a simple and interactive user interface. The proposed online portal is secured and have unique security feature such as unique id generation that adds another layer of security (except login id and password) and gives admin the ability to verify the user information and to decide whether he is eligible to vote or not. It also creates and manages voting and election details as all the users must login by user name and password and click on candidates to register vote.

Smart Safe Deposit Box Based on Internet of Things

The development of Internet of Things technology today is overgrowing in various fields, one of which is security. Safe-deposit box system is considered less safe because there is no warning to the owner. This study proposes a safe deposit box system that has a token security feature based on the internet of things. This system uses a webcam that functions to take pictures automatically. The image is sent to the server via the FTP protocol. It has two levels of users, namely admin, and guest. This system has a warning alarm, and notifications feature that works when the safe door is opened by force. Keyword: internet of things, safe deposit box

Development of an Approach for Creating and Storing the Information with the Help of Unity and AR Core SDK

Storing the information in the compact manner which is also easy to access is very difficult during these days. But with the help of AR (Augmented Reality) it is possible to place the notes and information in place without creating mess about it. A note keeping system inputs the note and the place on which it should be placed. This feature can be developed using unity and ARCore Sdk. AR Notekeeper is an AR based application in which user can create Notes and To Do Lists and not only just create them but store them in real word virtually using Augmented Reality with a passcode security feature. This functionality not only allows to keep their notes in a place which is known to only them but also ensures it stays there.

Multi-scale personnel deep feature detection algorithm based on Extended-YOLOv3

Tens of thousands of work-related injuries and deaths are reported in the construction industry each year, and a high percentage of them are due to construction workers not wearing safety equipment. In order to address this safety issue, it is particularly necessary to automatically identify people and detect the safety characteristics of personnel at the same time in the prefabricated building. Therefore, this paper proposes a depth feature detection algorithm based on the Extended-YOLOv3 model. On the basis of the YOLOv3 network, a security feature recognition network and a feature transmission network are added to achieve the purpose of detecting security features while identifying personnel. Firstly, a security feature recognition network is added side by side on the basis of the YOLOv3 network to analyze the wearing characteristics of construction workers. Secondly, the S-SPP module is added to the object detection and feature recognition network to broaden the features of the deep network and help the network extract more useful features from the high-resolution input image. Finally, a special feature transmission network is designed to transfer features between the construction worker detection network and the security feature recognition network, so that the two networks can obtain feature information from the other network respectively. Compared with YOLOv3 algorithm, Extended-YOLOv3 in this paper adds security feature recognition and feature transmission functions, and adds S-SPP module to the object detection and feature recognition network. The experimental results show that the Extended-YOLOv3 algorithm is 1.3% better than the YOLOV3 algorithm in AP index.