Facial recognition technology uses statistical measurements of facial features to determine identity digitally. While this allows for convenience, it also raises major privacy and security concerns. Facebook has developed Deepface, which can recognize faces in photos with 97.25% accuracy compared to 97.53% for humans. Deepface may help improve Facebook's facial recognition and could track people across physical stores. The Oregon DMV uses facial recognition to prevent fraudulent IDs, and police can identify people from video. However, facial analysis can reveal private sentiments from microexpressions and raise privacy implications if used without consent.
Biometric technology is a good fit for every enterprise due to these common factors. Most organizations have IT infrastructure that require secured logon, physical facilities where restricted access control need to be provided and employees who clock-in and clock-out at work. All these processes become faster and more secure by implementing biometric technology in an enterprise environment.
Facial recognition is a form of computer vision that uses faces to attempt to identify a person or verify a person’s claimed identity. Regardless of specific
Biometric technology is a good fit for every enterprise due to these common factors. Most organizations have IT infrastructure that require secured logon, physical facilities where restricted access control need to be provided and employees who clock-in and clock-out at work. All these processes become faster and more secure by implementing biometric technology in an enterprise environment.
Facial recognition is a form of computer vision that uses faces to attempt to identify a person or verify a person’s claimed identity. Regardless of specific
Mobile User Authentication Based On User Behavioral Pattern (MOUBE)CSCJournals
Smart devices are equipped with multiple authentication techniques and still remain prone to
attacks since all of these techniques require explicit user intervention. The purpose of this paper
is to capture the user behavior in order to use it as an implicit authentication technique.
In this paper, we introduce a novel authentication model to be used complementary to the
existing models; Particularly, the context of the user, the duration of usage of each application
and the occurrence time were examined and modeled using the cubic spline function as an
authentication technique. A software system composed of two software components has been
implemented on Android platform. Preliminary results show a 76% accuracy rate in determining
the rightful owner of the device.
Automatic Attendance system using Facial RecognitionNikyaa7
It is a boimetric based App,which is gradually evolving in the universal boimetric solution with a virtually zero effort from the user end when compared with other boimetric options.
A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source.
This slide is all about a detailed description of the Face Recognition System.
ANDROID UNTRUSTED DETECTION WITH PERMISSION BASED SCORING ANALYSISijitcs
Android smart phone is one of the fast growing mobile phones and because of these it the one of the most preferred target of malware developer. Malware apps can penetrate the device and gain privileges in which it can perform malicious activities such reading user contact, misusing of private information such as sending SMS and can harm user by exploiting the users private data which is stored in the device. The study is about implementation of detecting untrusted on android applications, which would be the basis of all future development regarding malware detection.
The smartphone users worldwide are not aware of the permissions as the basis of all malicious activities that could possibly operate in an android system and may steal personal and private information. Android operating system is an open system in which users are allowed to install application from any unsafe sites. However permission mechanism of and android system is not enough to guarantee the invulnerability of the application that can harm the user. In this paper, the permission scoring-based analysis that will scrutinized the installed permission and allows user to increase the efficiency of Android permission to inform user about the risk of the installed Android application, in this paper, the framework that would classify the level of sensitivity of the permission access by the application. The framework uses a formula that will calculate the sensitivity level of the permission and determine if the installed application is untrusted or not. Our result show that, in a collection of 26 untrusted application, the framework is able to correct and determine the application's behavior consistently and efficiently.
The Cybercriminal Approach to Mobile Fraud: Now They’re Getting SeriousIBM Security
Mobile devices have been targeted by cybercriminals for over seven years now. However, in 2014 things got serious. Cybercriminals realized that a major portion of eCommerce and online banking is moving to the mobile space, and with that companies are giving clients more options for larger transactions, and actions that were previously only performed on PCs. New PC grade malware appeared on mobile devices, some old PC tricks were transformed for mobile, and new mobile specific threats emerged. In this session we will analyze these threats using multiple customer case studies and Trusteer’s security team research data. We also take a look at the latest mobile threats, threats in development and mitigation tactics.
Using Geographical Location as an Authentication Factor to Enhance mCommerce ...CSCJournals
Smartphones are increasingly used to perform mCommerce applications whilst on the move. 50% of all Smartphone owners in the U.S. used their Smartphone for banking transactions in the first quarter of 2011. This is an increase of nearly 100% compared to the year before. Current techniques used to remotely authenticate the client to the service provider in an mCommerce application are based on “static” authentication factors like passwords or tokens. The fact that the client is on the move, whilst using these mCommerce applications is not considered or used to enhance the authentication security. This paper is concerned with including client’s geographical location as an important authentication factor to enhance security of mCommerce applications, especially those requiring robust client authentication. Techniques to integrate location as an authentication factor as well as techniques to generation location-based cryptographic keys are reviewed and discussed. This paper further outlines restrictions of location as an authentication factor and gives recommendations about correct usage of client’s location information for mCommerce application’s authentication on Smartphones.
Fingereye: improvising security and optimizing ATM transaction time based on ...IJECEIAES
The tumultuous increase in ATM attacks using eavesdropping, shoulder-surfing, has risen great concerns. Attackers often target the authentication stage where a customer may be entering his login information on the ATM and thus use direct observation techniques by looking over the customer's shoulder to steal his passwords. Existing authentication mechanism employs the traditional password-based authentication system which fails to curb these attacks. This paper addresses this problem using the FingerEye. The FingerEye is a robust system integrated with iris-scan authentication. A customer’s profile is created at registration where the pattern in his iris is analyzed and converted into binary codes. The binary codes are then stored in the bank database and are required for verification prior to any transaction. We leverage on the iris because every user has unique eyes which do not change until death and even a blind person with iris can be authenticated too. We implemented and tested the proposed system using CIMB bank, Malaysia as case study. The FingerEye is integrated with the current infrastructure employed by the bank and as such, no extra cost was incurred. Our result demonstrates that ATM attacks become impractical. Moreover, transactions were executed faster from 6.5 seconds to 1.4 seconds.
Smartphone Remote Detection and Wipe System using SMSEditor IJCATR
The project based on mobile application which functions on an Android operating system. The objective of this which
enable the user to locate the mobile phone in a silent mode to General mode when it is misplaced as well as if it is lost and wipe the
data from the device. To create an account the user needs to provide his /her mobile number, a password and 4 trustworthy numbers
this completes the registration process. The application, which is still in a deactivation mode, will operate only when the phone is
misplaced and the user sends the set password/ pass code from one of the 4 trustworthy numbers to one’s own mobile number. This
will change the profile of the misplaced phone i.e. switch it from the silent mode to the sound mode. It will also send an
acknowledgement to the trustworthy number from which the user has sent the message. Furthermore, it will also provide the location
with and also if mobile is lost then we can take back up from another mobile by using same application, we can also wipe the data
remotely by sending the message.
LdotR - Panel Discussion - Digital Solutions for Digital ProblemsAshokKumar4108
A panel discussion with industry leaders on the tools and technologies that they use in order to fight the rapidly growing online infringement and protect their business and brands.
LUIS: A L IGHT W EIGHT U SER I DENTIFICATION S CHEME FOR S MARTPHONES IJCI JOURNAL
Smartphone usage has reached its peak. There has be
en a tremendous growth in the number of people
migrating from PCs to smart phones. Numerous scenar
ios such as loss of a phone, phone theft etc., can
lead to unauthorized use of one’s own smartphone. T
his raises the concern for securing personal and
private data. This project proposes a light weight
two level user identification scheme to recognize a
nd
authenticate the mobile phone based on the device h
olding and usage patterns. To validate the proposed
scheme, an application is created which takes a ges
ture input characterized by time of swiping the scr
een,
finger pressure, phone movements and location of sw
ipe on the screen through X and Y co-ordinate. A
threshold based matching scheme performs classifica
tion to find the true owner. Results show that the
scheme was able to achieve 90% true positives and 1
0% false positives with a 0.5% of battery usage.
Mobile User Authentication Based On User Behavioral Pattern (MOUBE)CSCJournals
Smart devices are equipped with multiple authentication techniques and still remain prone to
attacks since all of these techniques require explicit user intervention. The purpose of this paper
is to capture the user behavior in order to use it as an implicit authentication technique.
In this paper, we introduce a novel authentication model to be used complementary to the
existing models; Particularly, the context of the user, the duration of usage of each application
and the occurrence time were examined and modeled using the cubic spline function as an
authentication technique. A software system composed of two software components has been
implemented on Android platform. Preliminary results show a 76% accuracy rate in determining
the rightful owner of the device.
Automatic Attendance system using Facial RecognitionNikyaa7
It is a boimetric based App,which is gradually evolving in the universal boimetric solution with a virtually zero effort from the user end when compared with other boimetric options.
A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source.
This slide is all about a detailed description of the Face Recognition System.
ANDROID UNTRUSTED DETECTION WITH PERMISSION BASED SCORING ANALYSISijitcs
Android smart phone is one of the fast growing mobile phones and because of these it the one of the most preferred target of malware developer. Malware apps can penetrate the device and gain privileges in which it can perform malicious activities such reading user contact, misusing of private information such as sending SMS and can harm user by exploiting the users private data which is stored in the device. The study is about implementation of detecting untrusted on android applications, which would be the basis of all future development regarding malware detection.
The smartphone users worldwide are not aware of the permissions as the basis of all malicious activities that could possibly operate in an android system and may steal personal and private information. Android operating system is an open system in which users are allowed to install application from any unsafe sites. However permission mechanism of and android system is not enough to guarantee the invulnerability of the application that can harm the user. In this paper, the permission scoring-based analysis that will scrutinized the installed permission and allows user to increase the efficiency of Android permission to inform user about the risk of the installed Android application, in this paper, the framework that would classify the level of sensitivity of the permission access by the application. The framework uses a formula that will calculate the sensitivity level of the permission and determine if the installed application is untrusted or not. Our result show that, in a collection of 26 untrusted application, the framework is able to correct and determine the application's behavior consistently and efficiently.
The Cybercriminal Approach to Mobile Fraud: Now They’re Getting SeriousIBM Security
Mobile devices have been targeted by cybercriminals for over seven years now. However, in 2014 things got serious. Cybercriminals realized that a major portion of eCommerce and online banking is moving to the mobile space, and with that companies are giving clients more options for larger transactions, and actions that were previously only performed on PCs. New PC grade malware appeared on mobile devices, some old PC tricks were transformed for mobile, and new mobile specific threats emerged. In this session we will analyze these threats using multiple customer case studies and Trusteer’s security team research data. We also take a look at the latest mobile threats, threats in development and mitigation tactics.
Using Geographical Location as an Authentication Factor to Enhance mCommerce ...CSCJournals
Smartphones are increasingly used to perform mCommerce applications whilst on the move. 50% of all Smartphone owners in the U.S. used their Smartphone for banking transactions in the first quarter of 2011. This is an increase of nearly 100% compared to the year before. Current techniques used to remotely authenticate the client to the service provider in an mCommerce application are based on “static” authentication factors like passwords or tokens. The fact that the client is on the move, whilst using these mCommerce applications is not considered or used to enhance the authentication security. This paper is concerned with including client’s geographical location as an important authentication factor to enhance security of mCommerce applications, especially those requiring robust client authentication. Techniques to integrate location as an authentication factor as well as techniques to generation location-based cryptographic keys are reviewed and discussed. This paper further outlines restrictions of location as an authentication factor and gives recommendations about correct usage of client’s location information for mCommerce application’s authentication on Smartphones.
Fingereye: improvising security and optimizing ATM transaction time based on ...IJECEIAES
The tumultuous increase in ATM attacks using eavesdropping, shoulder-surfing, has risen great concerns. Attackers often target the authentication stage where a customer may be entering his login information on the ATM and thus use direct observation techniques by looking over the customer's shoulder to steal his passwords. Existing authentication mechanism employs the traditional password-based authentication system which fails to curb these attacks. This paper addresses this problem using the FingerEye. The FingerEye is a robust system integrated with iris-scan authentication. A customer’s profile is created at registration where the pattern in his iris is analyzed and converted into binary codes. The binary codes are then stored in the bank database and are required for verification prior to any transaction. We leverage on the iris because every user has unique eyes which do not change until death and even a blind person with iris can be authenticated too. We implemented and tested the proposed system using CIMB bank, Malaysia as case study. The FingerEye is integrated with the current infrastructure employed by the bank and as such, no extra cost was incurred. Our result demonstrates that ATM attacks become impractical. Moreover, transactions were executed faster from 6.5 seconds to 1.4 seconds.
Smartphone Remote Detection and Wipe System using SMSEditor IJCATR
The project based on mobile application which functions on an Android operating system. The objective of this which
enable the user to locate the mobile phone in a silent mode to General mode when it is misplaced as well as if it is lost and wipe the
data from the device. To create an account the user needs to provide his /her mobile number, a password and 4 trustworthy numbers
this completes the registration process. The application, which is still in a deactivation mode, will operate only when the phone is
misplaced and the user sends the set password/ pass code from one of the 4 trustworthy numbers to one’s own mobile number. This
will change the profile of the misplaced phone i.e. switch it from the silent mode to the sound mode. It will also send an
acknowledgement to the trustworthy number from which the user has sent the message. Furthermore, it will also provide the location
with and also if mobile is lost then we can take back up from another mobile by using same application, we can also wipe the data
remotely by sending the message.
LdotR - Panel Discussion - Digital Solutions for Digital ProblemsAshokKumar4108
A panel discussion with industry leaders on the tools and technologies that they use in order to fight the rapidly growing online infringement and protect their business and brands.
LUIS: A L IGHT W EIGHT U SER I DENTIFICATION S CHEME FOR S MARTPHONES IJCI JOURNAL
Smartphone usage has reached its peak. There has be
en a tremendous growth in the number of people
migrating from PCs to smart phones. Numerous scenar
ios such as loss of a phone, phone theft etc., can
lead to unauthorized use of one’s own smartphone. T
his raises the concern for securing personal and
private data. This project proposes a light weight
two level user identification scheme to recognize a
nd
authenticate the mobile phone based on the device h
olding and usage patterns. To validate the proposed
scheme, an application is created which takes a ges
ture input characterized by time of swiping the scr
een,
finger pressure, phone movements and location of sw
ipe on the screen through X and Y co-ordinate. A
threshold based matching scheme performs classifica
tion to find the true owner. Results show that the
scheme was able to achieve 90% true positives and 1
0% false positives with a 0.5% of battery usage.
Facial Recognization
Introduction:
A type of biometric technology called facial recognition uses algorithms to recognize and
confirm a person's identity based on their facial traits. To generate a face template, the
system examines a person's distinctive facial features, such as the separation between their
eyes, the lines of their jawline, and the shape of their nose. The person's identity is then
verified by comparing this template to a database of pictures.
There are several uses for facial recognition technology, including:
Controlling access to guarded locations or seeing possible risks in public areas is a security
risk.
Advertising: to target customers based on their age, gender, and other demographic
characteristics.
Identifying and locating suspects, monitoring illegal activity, and assisting with
investigations.
The use of facial recognition has generated a great deal of discussion around the world due
to worries about accuracy, bias, and privacy. The advantages and disadvantages of facial
recognition will be explored in this article, along with some frequently asked questions
regarding this cutting-edge technology.
The advantages of facial recognition:
Numerous benefits of facial recognition technology make it a desirable alternative for
organizations, governments, and people in general. The following are some advantages of
facial recognition:
Greater Security:
Access to sensitive spaces like offices, labs, and data centers can be restricted using facial
recognition technology. Contrary to conventional security systems, which rely on users to
memorize and enter passwords or swipe cards, facial recognition technology can recognize
people automatically. This removes the possibility of having credentials lost or stolen, which
lowers the possibility of security breaches.
Facial recognition is helpful in public areas because it can spot possible dangers like
criminals or terrorists. Authorities can be immediately notified about people on watchlists or
with criminal histories by security cameras with facial recognition technology.
Convenience:
Technology for facial recognition is practical and simple to use. Passwords, ID cards, and
other tangible forms of identification are no longer required. For instance, all you have to do
to unlock your phone is stare at it. This makes facial recognition a well-liked option among
customers who value practicality and simplicity.
Marketing Perspectives:
Data on consumer behavior can also be gathered using facial recognition technologies.
Businesses can get crucial information about how customers respond to various items and
marketing by examining customer demographics and facial expressions. Then, by tailoring
marketing initiatives, this information can enhance client satisfaction.
Negative aspects of facial recognition:
Face recognition technology has a lot of advantages, but it also has a lot of disadvantages.
The following are some of the major drawbacks of facial recognition:
A Smart Receptionist Implementing Facial Recognition and Voice InteractionCSCJournals
The purpose of this research is to implement a smart receptionist system with facial recognition and voice interaction using deep learning. The facial recognition component is implemented using real time image processing techniques, and it can be used to learn new faces as well as detect and recognize existing faces. The first time a customer uses this system, it will take the person’s facial data to create a unique user facial model, and this model will be triggered if the person comes the second time. The recognition is done in real time and after which voice interaction will be applied. Voice interaction is used to provide a life-like human communication and improve user experience. Our proposed smart receptionist system could be integrated into the self check-in kiosks deployed in hospitals or smart buildings to streamline the user recognition process and provide customized user interactions. This system could also be used in smart home environment where smart cameras have been deployed and voice assistants are in place.
AI and Machine Learning In Cybersecurity | A Saviour or Enemy?SahilRao25
Let's take a look at implementations of AI or machine learning in the cybersecurity world. To know more: https://www.softwarefirms.co/blog/ai-and-machine-learning-in-cybersecurity-a-saviour-or-enemy?utm_source=Social+media&utm_medium=Traffic&utm_campaign=SR
AI Approach for Iris Biometric Recognition Using a Median FilterNIDHI SHARMA
The Artificial Intelligence approach is used for Iris recognition by understanding the distinctive and measurable characteristics of the human body such as a person’s face, iris, DNA, fingerprints, etc. AI methods analyzed the attributes like iris images. Privacy and Security being a major concern nowadays, Recognition Technique can find numerous applications.
8 facial recognition apps that will rule 2020!Concetto Labs
Looking forward to building facial recognition apps? Concetto Labs is a top-notch face recognition app development company. If you have a unique face app development idea then contact us now.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
2. Facial recognition is a type of biometric technology that uses statistical measurements of
people’s features to digitally determine identity.Though facial recognition can allow for more
ease in day to day life, it comes with major security and privacy issues that might cause concerns
for users.
Facebook, Oregin Department of Motor vehicles etc. use these facial recognition
systems for various purposes.
Facebook’s facial recognition tool called Deepface is nearly as accurate the human
brain in recognizing a face.It can compare 2 photos and compare it with 97.25% accuracy
whether the photos shows the same face.Humans are able to perform the same task with 97.53%
accuracy.Deepface was developed by facebook’s AI research group in California.Deepface soon
will be ready for commercial use, most likely to help facebook improve the accuracy of its
existing facial recognition capabilities.Deepface might also be used for real world facial-
tracking.
The Oregon Department of Motor Vehicles uses facial recognition to ensure that
drivers licenses, instruction permits,and ID cards are not issued under false names.Police can
capture a 3D video and upload it to an image gallery for comparison to identify people with prior
criminal records or outstanding warrants.
Facial analysis has progressed beyond scruitinizing static features.Frame by frame
analysis can isolate involuntary millisecond-long expressions,revealing private sentiments.While
these insights can drive productive endeavours,they are fraught with privacy implications.
Emotient, another expression analysis start up located in California, received a 6
million infusion of funds in early2014 to support glassware for retail salespeople.Emotient is
confident that the ability to objectively and accurately gauge customer emotions will give retail
teams more tools to increase sales, but customer response to being recorded by cameras
embedded in smartglass is uncertain.
Face recognition technology has come a longway.However, next generation face
recognition systems are going to have widespread application in smart environments-where
computers and machines are more likely helpful to assistants.
3. QUESTIONS AND ANSWERS
1. What are some of the benefits of using facial recognition technology?Describe some
current and future applications of this technology.
Some of the benefits of facial recognition technology are:
Increased Security: One of the biggest pros of facial recognition technology is that it
enhances safety and security. From government agencies to personal use, there is an
increasing demand for advanced security and surveillance systems. Organizations can
easily identify and track anyone who comes onto the premises, and they can easily flag
visitors who aren’t welcome. It can be very helpful when it comes to finding potential
terrorists. Plus, there is no key, badge, or password that can be stolen or lost.
Fast and Accurate: With the ever-increasing demand for speed and the growing number
of cyberattacks, having fast and accurate technology is key. Facial recognition
technology provides verification that is convenient, quick, and accurate. Although
possible, it is very difficult to fool facial recognition technology, which makes it
beneficial in helping prevent fraud.
No Contact: Facial recognition is preferred over fingerprint scanning because of its non-
contact process. People don’t have to worry about the potential drawbacks related to
fingerprint identification technology, such as germs or smudges.
Deepface soon will be ready for commercial use, most likely to help facebook improve
the accuracy of its existing facial recognition capabilities.Deepface might also be used for real
world facial-tracking.Foe example, monitoring someone’s shopping habits as that person moves
from physical store to store.
The Oregon Department of Motor Vehicles uses facial recognition to ensure that drivers
licenses, instruction permits,and ID cards are not issued under false names.Police can capture a
3D video and upload it to an image gallery for comparison to identify people with prior criminal
records or outstanding warrants.
4. 2.How does facial recognition technology threaten the protection of individual privacy?
Facial analysis has progressed beyond scruitinizing static features.Frame by frame
analysis can isolate involuntary millisecond-long expressions,revealing private sentiments.While
these insights can drive productive endeavours,they are fraught with privacy implications.For
example , do you want the person conducting the job interview to be able to review a videotape ,
identify fleeting moments of confusion or indecision and decide against hiring you.
3.Would you like deepface to track your activities on facebook and in the physical world?
Deepface is nearly as accurate the human brain in recognizing a face.It can compare 2
photos and compare it with 97.25% accuracy whether the photos shows the same face.Humans
are able to perform the same task with 97.53% accuracy.Deepface was developed by facebook’s
AI research group in California.Deepface soon will be ready for commercial use, most likely to
help facebook improve the accuracy of its existing facial recognition capabilities.Deepface might
also be used for real world facial-tracking.
