A Survey on Covid Safety System

In this paper a Raspberry Pi based automated solution system focused on the real-time face monitoring of people to detect both face masks and body temperature with the help of MLX90614 sensor has been proposed. This is implemented using Python Programming with OpenCV Library, TensorFlow, Dlib Module. A security clearance system is deployed that will allow that person to enter if they are wearing a face mask and their body temperature is in check with WHO guidelines. A programmed hand sanitizer apportioning machine is mechanized, non-contact, liquor-based hand sanitizer gadget. Liquor is essentially a dissolvable, and furthermore a generally excellent sanitizer when contrasted with fluid cleanser or strong cleanser, likewise it needn't bother with water to wash off since it is unpredictable furthermore, disintegrates in a split second after application to hands. It is too demonstrated that a convergence of >70% liquor can execute Covid in hands. Here, we have used IR sensor detects the hand put close to it, the Arduino Uno is utilized as a microcontroller, which detects the distance and the outcome isthe pump starts running out the hand sanitizer. Thus, the above said system will help the society by saving time and also helps in contaminating the spread of coronavirus. This can be implemented in public places such as colleges, schools, offices, shopping malls, etc. to inspect people. Keywords: Deep Learning, Open CV, Keras, Python, Tensor Flow, Computer Vision, Raspberry Pi, COVID-19, DLib, Arduino, Sensor, Sanitizer, Infrared sensor

Not too deep: Privacy, resistance, and the incorporation of social media in background checks

In May 2016, the United States Office of the Director of National Intelligence (ODNI) issued “Security Executive Agent Directive 5” (SEAD-5) (U.S. ODNI, 2016) authorizing the collection, use, and retention of social media information for the personnel security clearance process (PSCP), a process put in place to screen applicants for eligibility for national security and public trust positions. The incorporation of social media was a watershed moment for this process as social media, and even information from the entire Internet, had not been allowed into the investigation process before. The integration was not without resistance to the implementation, though, and backstage concerns about privacy emerged in Congressional hearings. What is most interesting to note, however, is that the resistance was for the most part in support of privacy for the potential employees of whom were receiving the check and the government’s obligations for the information collection; however, there was little, if any, mention of deeper, possibly problematic privacy concerns for the social media platforms and their mediated connections that co-create a second, derivative type of content beyond the access of their users. This paper examines the hearing “Incorporating social media into federal background investigations” in response to the SEAD-5 to see what the U.S. Congress did and did not discuss at the hearing and explores potential explanations for the inclusions/omissions, ultimately answering how those in charge of policies could have overlook deeper privacy complexities, and evaluating what this can mean for government, privacy, and policy researchers.

Ochrona informacji niejawnych w USA. Wybrane regulacje karne i administracyjne

Protection of classified information in the USA. Selected penal and administrative regulations The article discusses the administrative regulations regarding the classified information protection system in the USA. Moreover, it presents the effective penal code provisions directed against the disclosure of classified information in the USA and their interpretations. What is more, the paper presents the administrative provisions regulating the procedure for carrying out security background investigation of public administration officials in order to issue a security clearance which grants them access to classified information. Further, the reasons for the classification of information and its protection with an adequate classification clause are explained. On the basis of the analysis of US regulations, a conclusion is drawn that Polish legislation does not include a justification for depositaries of secrets who disclose classified information (without obtaining the affirmation from the authorities specified by law) to prosecute the perpetrators of crimes. This could be the basis to formulate postulates de lege ferenda. It should be noted that the article does not exhaust the topic, but only indicates selected issues of the protection system of classified information in the USA. Initiated study can be used to carry out in-depth comparative research in this field in the future. W artykule omówiono regulacje administracyjne związane z organizacją systemu ochrony informacji niejawnych, a także przedstawiono przepisy karne dotyczące ujawniania informacji niejawnych obowiązujące w USA wraz z ich interpretacją. Omówiono również przepisy administracyjne regulujące procedurę realizacji postępowań sprawdzających wobec urzędników administracji publicznej w celu wydania poświadczenia bezpieczeństwa umożliwiającego dostęp do informacji niejawnych. Ponadto wskazano przesłanki klasyfikacji informacji i obejmowania ich ochroną adekwatnej klauzuli niejawności. Na podstawie analizy przepisów USA między innymi sformułowano wniosek, że polskie ustawodawstwo nie obejmuje kontratypu, który uwalniałby od odpowiedzialności karnej depozytariuszy tajemnic przekazujących informacje niejawne (bez uzyskiwania zgody określonych prawem organów) w celu ścigania sprawców przestępstw. Powyższe może być podstawą legislacyjnego postulatu de lege ferenda, przy uwzględnieniu adekwatnych regulacji prawnych USA. Należy zaznaczyć, że artykuł nie wyczerpuje poruszanego tematu, a jedynie wskazuje wybrane zagadnienia ochrony informacji niejawnych USA. Może to zostać wykorzystane do przeprowadzenia w przyszłości pogłębionych badań komparatystycznych dotyczących przedmiotowego zagadnienia.

Fraud within and against the Commonwealth: the most harmful frauds, 2016-17 to 2018-19

Fraud threats facing the Commonwealth arise principally from two areas: individuals employed by the Commonwealth or contractors (internal fraud); and customers/clients of the Commonwealth, third-party providers, vendors, or members of the public, in Australia or overseas (external fraud). The current report presents the information about the most harmful internal and external frauds committed against the Commonwealth in 2018–19, compared with those reported in 2016–17 and 2017–18. Data come from finalised fraud investigations that were reported by Commonwealth entities in response to the Australian Institute of Criminology’s annual fraud census. The findings show that losses from both the most harmful internal and external frauds were lower in 2018–19 than in 2017–18. In 2018–19, 44 percent of respondents identified the most harmful internal fraud perpetrator as having been employed with the entity for longer than seven years. The majority of the most harmful internal frauds were committed by individuals with either no security clearance or an unknown clearance status. In 2018–19, a higher proportion of perpetrators received a sentence of imprisonment following conviction for the most harmful external frauds than internal frauds. In 2018–19, the most common fraud control weaknesses identified were perpetrators overriding existing internal controls and the lack of knowledge concerning fraud risks.

The Intention of Passengers towards Repeat Use of Biometric Security for Sustainable Airport Management

More and more these days, airport security is having to adapt to a greater number of passengers while keeping within finer margins of precision when it comes to clearing passengers for security clearance. Therefore, analyzing potential upgrades in the security process and adopting them in a way that does not impact passenger experience has become a key activity for airport managers. One viable technological solution that is not only effective but also efficient is biometric security. This technology allows for passengers to safely clear security based on their unique biometric features. Despite its promise, airports and passengers alike are slow to adopt its use. Additionally, there were few studies that revealed insights into passengers’ intentions toward repeat use of biometric security. Hence, in our novel attempts to uncover the underlying reasons, we implemented a study on passengers’ initial and repeat usage intention based on perceived benefits and risks of biometric security technology. Based on 327 survey responses, we employed the use of SEM to extract first- and second-order constructs before evaluating our hypotheses on a finally accepted model. To be aligned with the novel attempt of this research, the results showed that both the perceived benefits and risks have a significant impact on passenger’s initial and repeat use intention of biometric security. Therefore, for all practitioners engaged in sustainable airport management, strong consideration from this research should help in creating value for passengers while mitigating the risks of adopting biometric security within airport security settings.

Machine Learning Based Robust Access for Multimodal Biometric Recognition

For organizations requiring high security clearance, multimodal sources of biometric scans are preferred. Computational models for the unimodal biometric scans have so far been well recognized but research into multimodal scans and their models have been gaining momentum recently. For every biometric we used separately feature extraction techniques and we combined those features in efficient way to get robust combination. In this paper, a novel method for fusion of the scan images from the different modes has been introduced. The method is based on representation of data in terms of its sparsity. Feature coupling and correlation information are obtained from the biometric images. The images from each mode are fused by taking into account a quality measure. The algorithms are kernelised so as to handle nonlinear data efficiently. The result of the proposed system is compared to already existing image fusion methods to show its advantage over them.