Facial recognition technology has advanced significantly and is now used widely for security and identification purposes. Facebook has developed Deepface, a facial recognition system that can identify faces in photos with 97.25% accuracy comparable to humans. Deepface may soon be used commercially by Facebook to improve its facial recognition and potentially track people across the physical world as they shop from store to store. However, facial recognition also raises privacy concerns as it can analyze subtle facial expressions without consent and reveal private sentiments.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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.
