400 research outputs found
TAS: Risk Analysis & Clustered Sensors
This paper briefly introduces a general view on tomorrow’s border control system and EU inter-BCP real time information sharing, exploring and proposing new operational methods and solutions for border control procedures to increase the efficacy and efficiency of the whole security screening system at the same time reducing the efforts (costs/resources). The general description of the system logic and architecture introduces the core of the solution, the Trust Assessment System. A “black box” based on risk analysis and advanced machine learning algorithms aimed to assign a Traveller Trust Score to each single individual intentioned to cross the border. Main benefits are: improved checkpoint throughput, improved situational awareness and level of security, better traveller experience, optimisation of resources. The concept is that the traveller risk evaluation starts as soon as she/he applies for a visa, a passport or books a trip by whatever means of transport
Improving Border Check Point Security
Risk-based screening at border crossing
As international travel flows continue to rise, there is growing pressure to process large volumes of people and goods at EU crossing points without creating bottlenecks; at the same time, there is a need to provide better security at the “external” borders (land, sea, air), which are entry points into the EU, keeping technology costs related to border crossing points (BCP – extended control area ) as low as possible. Furthermore, the casting of the information net and the reliability of information need to be accurate; moreover, building of trust between parties and the sharing of data are as important as technology advancement. While security cannot be compromised, the traveller’s experience should be positive. Trans-border crime causes border instability and vice-versa; hence strengthening border control helps to reduce crime, apprehend terrorists and detect prohibited weapons thus making the EU a safer place. Yet, at the same time, measures need to be appropriate, in terms of efficiency (i.e. large numbers of crossings require quick control checks; maintaining the current level of checks is becoming increasingly expensive), while assuring the effectiveness (i.e. potential threats have to be detected, whereas bona fide crossings should be made smoother or seamless). In order to achieve such goals, risk-based methods and systems for screening at border crossing must be defined and actually implemented . The use of smart and novel detection technology along with advanced data analytics can truly help to improve detection of potentially dangerous people and goods while limiting to fewer accurate checks informed by pre-selected and preliminary (and non-disruptive) risk-based analysis of the flows, in respect of the quality of life of the traveller, and adding economic vitality to the union of states.
There is a need to define tomorrow’s European's border control system and inter BCP real time information sharing, exploring and proposing new operational methods and solutions for border control procedures and identify new paths toward the effective and efficient adoption in real scenarios. The primary objective will be to provide the border control operators and practitioners with enhanced situational awareness, and capabilities to timely and proper identification of potentially dangerous people and goods, thus preventing smuggling and human trafficking. This can be achieved through an economically sustainable technological improvement at European Crossing Points based on risk analysis working on two main levels: customised configuration of BCPs and Risk Based Screening that combines information from multiple sources and can start already when the traveller is planning his or her journey. This early and proactive risk analysis results in an evaluation that represents an input to cross-border checks enabling the identification of bona-fide travellers, with the ultimate goal of improving the accuracy and effectiveness of border crossing activities while reducing costs.
The collection and analysis of information from multiple sources represents an important factor of innovation, as the risk assessment will be based on: information provided by the traveller on a voluntary basis (duly checked), agreement with “carriers” and destination managers, as well as sensors, PNR, criminal databases and other relevant resources (such as social media, that might provide additional info or weak signal on travellers’ movement and intentions). The usage of multiple sources of information is motivated by the following reasons:
• “Official” data (such as PNR or traditional security databases) do not often allow to achieve a whole picture of travellers’ movement due to the lack of pieces of information;
• “Weak signals” on travellers’ movement (provided by or extracted from additional data sources such as social media) can complement such a picture;
• The information on travellers’ movements is not enough for assessing the risk level of passengers: we also need information on people behaviour and other attitudes to create an effective (and informed) risk profile to support decisions at the checkpoints. Additional sources such as social media and sensors can provide relevant information to inform advanced analytics with the aim of assessing such a risk profile and perform the so-called “digital screening” .
We can consider the “additional” information according to the “fitness for purpose” approach, taking into account the practicability in collecting them and the “user acceptance”. The outlined solution is a system of systems, where multiple sources providing heterogeneous data will be organised, modelled and processed, based on a set of novel data analytics and analysis algorithms. Through adaptive cost-effective solutions for border crossing points and selective checks, the main aims is to quickly identify “bona-fide” travellers through the collection of relevant information about each single traveller from the time the travel ticket is bought or visa is issued, thus creating (as much as reasonably practicable) a personal trust profile for each traveller approaching EU crossing points
TAS: TRUST ASSESSMENT SYSTEM
The present paper briefly introduces a general view on tomorrow’s border control system and EU inter-BCP real time information sharing, exploring and proposing new operational methods and solutions for border control procedures to increase the efficacy and efficiency of the whole security screening system at the same time reducing the efforts (costs/resources). The general description of the system logic and architecture introduces the core of the solution, the Trust Assessment System. A “black box” based on risk analysis and advanced machine learning algorithms aimed to assign a Traveller Trust Score to each single individual intentioned to cross the border. Main benefits are: improved checkpoint throughput, improved situational awareness and level of security, better traveller experience, optimisation of resources. The concept is that the traveller risk evaluation starts as soon as she/he applies for a visa, a passport or books a trip by whatever means of transport
From Identification to Identity Theft: Public Perceptions of Biometric Privacy Harms
Central to understanding biometric privacy is the question of biometric privacy harms. How much do people value biometric privacy, and what evils should biometric privacy laws seek to avert? This Article addresses these questions by surveying two nationally representative samples to determine what does, and does not, worry people in the context of biometrics. The results show that many people are deeply concerned about biometric privacy in the consumer context, that they are willing to sacrifice real benefits to preserve biometric privacy, and that those who are concerned with biometric privacy attribute their concern to many factors that are not directly related to data security, particularly public tracking. Further, people’s level of comfort with biometric data collection differs sharply depending on the uses to which the data will be put and not just on the type of data collected. These nuanced attitudes about biometric privacy are in sharp conflict with a purely data security approach to biometric harms, and therefore have substantial implications both for future legislative consideration as well as current standing litigation
The Micro-Politics of Border Control: Internal Struggles at Canadian Customs
This dissertation explores the remaking of Canadian customs from the point of view of border officers tasked with processing trucks and commodities. Historically employed for tax collection, border authorities have gradually been incorporated into security provision and trade facilitation. This has entailed the pluralization of public and private actors who have a stake in border regulation as well as the design of a series of organizational reforms, new customs programs, border technologies and intelligence-led policing strategies. As a result, there has been a disembedding of borderwork and a displacement of decision-making away from ports of entry. Frontline security professionals negotiate these changes in ways that have consequences for our understanding of border priorities. In response to the consequences of this new division of labour, including their loss of clout in the security field, customs officers attempt to maintain their hold on border responsibilities by relying on their discretionary powers. Meanwhile, they emphasize the potentially dangerous aspects of their work over the more administrative by deploying an enforcement narrative––one that has recently found its concrete application in their union's successful campaign to obtain arming for its members. While an analysis of the "pistolization" of borderwork indicates the progressive adoption of a policing sensibility by border officers, an examination of their restructured professional socialization reveals the emergence of distinct generational approaches to borderwork. Hiring and training play a central part in shaping "old ways" and "new ways" of doing borderwork. Anchored in divergent temporalities of border control, these internal categorizations of skills and attitudes point to the new registers of distinction mobilized by officers as they negotiate a transitioning security field
Global privacy concerns of facial recognition big data
Facial recognition technology is a system of automatic acknowledgement that recognizes individuals by categorizing specific features of their facial structure to link the scanned information to stored data. Within the past few decades facial recognition technology has been implemented on a large scale to increase the security measures needed to access personal information. This has been specifically used in surveillance systems, social media platforms, and mobile device access control. The extensive use of facial recognition systems has created challenges as it relates to biometric information control and privacy concerns. This concern raises the cost and benefit analysis of an individual’s security versus his/her privacy. Due to the contactless ability of facial recognition identification, the global market of this technology is expected to increase considerably over the next decade. This expansion implies the requirements of additional legal regulations in regard to the use of facial recognition technology. Data privacy laws have been passed in over 80 countries around the world and several states within the United States have created laws that apply to this form of technology. However increased action should be taken on a national level to enact stricter regulations in regard to biometric data collection and use
The International Review | 2012 Fall/Winter
Should nations regulate digital photo editing?
Protecting the privacy of biometric data: National and international efforts
How do nations and international law address bribery?https://digitalcommons.nyls.edu/international_review_newsletter/1002/thumbnail.jp
Integrating Google Earth Engine and Decametric Sentinel 2 Images for Analysis of Vegetation Pre and Post the Disaster at Brumadinho, Brazil
This paper presents the application of the normalized difference vegetation index to assess the vegetation dynamics for the period between years 2017 and 2021 at Brumadinho, MG, Brazil. The normalized difference vegetation index was calculated using a Google Earth Engine script applying Sentinel 2 data with a spatial resolution of 10 meters, to quantify the extent of the affected area and assess the vegetation dynamic after the disaster. The Dwass-Steel-Crichlow-Fligner test for nonparametric data was used for a pairwise comparison between years and the confidence interval was calculated using bootstrap with 9999 repetitions. The total area affected by the dam brake was 2662 ha. The NDVI values presented a statistically significant decrease from 2017 to 2019, with little increase until 2021. Mean NDVI values were 0.314003 [0.31028; 0.317564], 0.339887 [0.336591; 0.343231], 0.145814 [0.144004; 0.1476], 0.1495 [0.147676; 0.15128], and 0.15572 [0.153727; 0.15774] for 2017–2021, respectively. According to the results, we conclude that the vegetation in the affected area did not fully recover
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