This document provides an overview of biometric technology and its applications. It discusses how biometrics uses physiological or behavioral characteristics to automatically identify or verify individuals. Some key points:
- Biometrics can provide secure authentication by linking an event to a particular individual, as opposed to passwords or tokens which can be shared or stolen.
- Common biometric traits include fingerprints, iris scans, facial recognition, and voice recognition. Technologies are being integrated into devices like phones, laptops, and ATMs.
- Biometric systems have subsystems for data collection, transmission, signal processing, decision making, and data storage. Accuracy is measured by false acceptance and false rejection rates.
- While biometrics provides strong
This document summarizes a research paper on a multimodal biometric system using fingerprint and face for identification. The system uses two modalities - fingerprint and face - to achieve greater accuracy than single-feature systems. It extracts minutiae from fingerprints and uses eigenspace projection for face recognition. Matching scores from each modality are fused at the decision level to make the final identification. The system was tested on a database of 25 users, collecting multiple fingerprint and face images per user under controlled conditions. Experimental results showed the multimodal system achieved lower error rates than unimodal systems.
Biometrics is the most secure and suitable authentication tool. It is the automated method of recognizing a person based on a physiological or behavioral characteristic. Biometric authentication is used in computer Science for verifying human identity.
1. The document discusses biometrics as a means of identity verification and authentication using human physiological and behavioral characteristics like fingerprints, iris patterns, voice, etc.
2. Biometric systems work by collecting, transmitting, processing and storing biometric data to make decisions about identity verification. They are being used in applications like banking, border control, and device access.
3. While biometrics provide high security and convenience by eliminating reliance on tokens and passwords, systems need to balance accuracy rates and intrusiveness on user privacy. India is also witnessing growth in biometric solution developers and applications.
This article discusses the implementation of iris recognition in improving the security of border control systems in the United Arab Emirates. The article explains the significance of the implemented solution and the advantages the government has gained to-date. The UAE deployment of iris recognition technology is currently the largest in the world, both in terms of number of Iris records enrolled (more than 840,751) and number of iris comparisons performed daily 6,225,761,155 (6.2 billion) in ‘all-against-all’ search mode.
This document discusses keystroke biometrics as a biometric technique for user authentication. It begins with an introduction to biometrics and why it is preferable to traditional authentication methods. It then provides details on keystroke biometrics implementation, which involves analyzing the timing between keystrokes when a user types their password. The timing patterns are unique to each user and can be used to accurately identify users. The document also discusses performance measures, algorithms, and how graphing keystroke timing can be used to determine if a user is authentic or not.
This document presents information on biometrics technology. It discusses various biometric methods of verification including fingerprint, hand print, face measurement, retinal scanning, and DNA analysis. It also covers behavioral verification methods like typing, signature, and voice. The document discusses identification, applications, advantages, and limitations of biometrics technology. It provides percentages of usage of different verification methods and concludes that biometrics provides good security despite some limitations and expenses.
This document proposes developing an algorithm to identify individuals using their unique baseline brainwave patterns as a biometric. It aims to address identification issues with traditional methods, anticipate ethical issues, and determine the technology's legal position. The document reviews previous related research and defines objectives to develop an identification algorithm, highlight ethical impacts, and assess legality. It outlines preliminary design plans to achieve the objectives, including methods for acquiring, transforming, storing, and comparing brainwave data to identify individuals.
Multimodal Biometric endorsement for secure Internet banking using Skin Spect...IRJET Journal
This document proposes a multimodal biometric authentication system for secure internet banking using skin spectroscopy, finger knuckle texture, and finger nail recognition. It discusses the limitations of unimodal biometric systems and how a multimodal approach combining three biometrics—skin spectroscopy, knuckle texture, and nail plate analysis—can improve accuracy and security. The system aims to provide stronger authentication for internet banking transactions compared to traditional password or token-based systems.
This document summarizes a research paper on a multimodal biometric system using fingerprint and face for identification. The system uses two modalities - fingerprint and face - to achieve greater accuracy than single-feature systems. It extracts minutiae from fingerprints and uses eigenspace projection for face recognition. Matching scores from each modality are fused at the decision level to make the final identification. The system was tested on a database of 25 users, collecting multiple fingerprint and face images per user under controlled conditions. Experimental results showed the multimodal system achieved lower error rates than unimodal systems.
Biometrics is the most secure and suitable authentication tool. It is the automated method of recognizing a person based on a physiological or behavioral characteristic. Biometric authentication is used in computer Science for verifying human identity.
1. The document discusses biometrics as a means of identity verification and authentication using human physiological and behavioral characteristics like fingerprints, iris patterns, voice, etc.
2. Biometric systems work by collecting, transmitting, processing and storing biometric data to make decisions about identity verification. They are being used in applications like banking, border control, and device access.
3. While biometrics provide high security and convenience by eliminating reliance on tokens and passwords, systems need to balance accuracy rates and intrusiveness on user privacy. India is also witnessing growth in biometric solution developers and applications.
This article discusses the implementation of iris recognition in improving the security of border control systems in the United Arab Emirates. The article explains the significance of the implemented solution and the advantages the government has gained to-date. The UAE deployment of iris recognition technology is currently the largest in the world, both in terms of number of Iris records enrolled (more than 840,751) and number of iris comparisons performed daily 6,225,761,155 (6.2 billion) in ‘all-against-all’ search mode.
This document discusses keystroke biometrics as a biometric technique for user authentication. It begins with an introduction to biometrics and why it is preferable to traditional authentication methods. It then provides details on keystroke biometrics implementation, which involves analyzing the timing between keystrokes when a user types their password. The timing patterns are unique to each user and can be used to accurately identify users. The document also discusses performance measures, algorithms, and how graphing keystroke timing can be used to determine if a user is authentic or not.
This document presents information on biometrics technology. It discusses various biometric methods of verification including fingerprint, hand print, face measurement, retinal scanning, and DNA analysis. It also covers behavioral verification methods like typing, signature, and voice. The document discusses identification, applications, advantages, and limitations of biometrics technology. It provides percentages of usage of different verification methods and concludes that biometrics provides good security despite some limitations and expenses.
This document proposes developing an algorithm to identify individuals using their unique baseline brainwave patterns as a biometric. It aims to address identification issues with traditional methods, anticipate ethical issues, and determine the technology's legal position. The document reviews previous related research and defines objectives to develop an identification algorithm, highlight ethical impacts, and assess legality. It outlines preliminary design plans to achieve the objectives, including methods for acquiring, transforming, storing, and comparing brainwave data to identify individuals.
Multimodal Biometric endorsement for secure Internet banking using Skin Spect...IRJET Journal
This document proposes a multimodal biometric authentication system for secure internet banking using skin spectroscopy, finger knuckle texture, and finger nail recognition. It discusses the limitations of unimodal biometric systems and how a multimodal approach combining three biometrics—skin spectroscopy, knuckle texture, and nail plate analysis—can improve accuracy and security. The system aims to provide stronger authentication for internet banking transactions compared to traditional password or token-based systems.
This article argues that implementing biometrics, smart cards, and public key infrastructure (PKI) technologies together can deliver a robust digital identity system to address identity theft. Biometrics provide unique identification of individuals. Smart cards can store biometrics and public keys to verify identities. PKI establishes a framework for secure authentication and encryption through public/private key pairs. The article concludes this "technology trio" may enable trusted e-government and e-commerce by strongly authenticating virtual identities.
The document discusses the use of biometric authentication technologies like fingerprints for ATMs in rural India. It notes that biometric ATMs can help illiterate and barely literate rural residents access banking services by establishing their identity through biometrics rather than passwords. The document outlines some companies in India that are developing biometric solutions for ATMs, including fingerprint authentication systems. It also discusses the benefits of biometric ATMs, how biometric authentication systems work, and provides examples of different biometric technologies like fingerprint recognition and face recognition.
This document is a report on biometric sensors written by Arhind Kumar Gautam for his Information Technology department. It contains an introduction to biometric sensors, a history of biometrics, definitions of biometric terms, descriptions of different types of biometric sensors including physical (fingerprint, face recognition, retina scan) and behavioral (voice recognition, signature) biometrics. It also discusses future applications of biometrics and provides a conclusion on biometric sensors.
This document presents an overview of biometric technologies. It defines biometrics as the science of measuring and analyzing biological data for authentication purposes, such as fingerprints, iris patterns, and voice. The document outlines the basic components of biometric systems including readers, software, and databases. It also categorizes biometrics as physiological (face, fingerprints, etc.) or behavioral (signature, voice). The document discusses several biometric modalities like fingerprint, face, iris and voice recognition and their uses. It covers issues around privacy, cancelable biometrics, and soft biometrics. Overall, the document provides a high-level introduction to biometrics and their applications.
The document summarizes biometric security and fingerprint recognition technology. It defines biometrics as using physical or behavioral traits like fingerprints, iris, face, voice or handwriting to identify individuals. Fingerprints are widely used for authentication and various fingerprint recognition techniques are described, including minutiae-based matching of ridge endings and bifurcations. Applications of fingerprint biometrics include security systems, criminal identification, and border control. Emerging areas include 3D and multi-view fingerprint capture to overcome limitations of contact sensors.
Case study on Usage of Biometrics (Cryptography)Bhargav Amin
This document provides an overview of biometrics and biometric authentication systems. It discusses the history of biometrics, how biometric systems work, performance considerations, different biometric modalities like fingerprints, face recognition and iris recognition. It also covers factors to consider when deciding whether to use biometric technology, different types of biometric systems, and examples of biometric implementation in areas like ATMs, law enforcement and networking. The document aims to provide a comprehensive look at biometrics and its usage.
This document provides an overview of blind authentication, a secure crypto-biometric authentication protocol. It begins with an introduction discussing the primary concerns with biometric authentication systems, such as template protection, user privacy, trust issues between users and servers, and network security. It then reviews related work on addressing these concerns. The document proceeds to explain the blind authentication process, which involves feature extraction, enrollment with a trusted third party, and authentication between a user and server. Features of blind authentication include strong encryption for template protection and privacy while maintaining authentication accuracy. Advantages are template security, non-repudiation, and revocability.
Network security is enhanced through biometrics authentication which uses unique physical traits to verify user identity. Biometrics is more secure than passwords since traits cannot be forgotten, stolen, or easily copied. The document discusses common biometric traits like fingerprints, iris scans, and voice recognition. It explains how biometric systems work by enrolling traits during initial use then comparing submitted traits to stored information for authentication. Biometrics provides stronger security for networks and systems by using the human body as a verification method.
Biometrics refers to the statistical analysis of biological characteristics to identify or verify individuals. It uses automated methods and pattern recognition to analyze physiological or behavioral traits unique to each person, such as fingerprints, iris patterns, voiceprints, and hand geometry. Biometric systems collect and analyze these traits to identify individuals with high accuracy. Major applications of biometrics include security systems, smart cards, and mobile device authentication. Future areas of biometrics may involve DNA scanning, ear shape analysis, and vein pattern recognition.
A brief overview of biometric authentication and the benefits it can have on your business and its overall security. Is biometric authentication something you should be looking into? Find out now...
This document discusses biometric security methods for mobile devices. It begins with an introduction to biometrics and how biometric authentication works. Then it discusses some key biometric security methods used by Apple iPhone and Samsung Galaxy mobile phones, including Touch ID fingerprint scanning and iris scanning. It explains how Apple and Samsung use encrypted enclaves and digital identifiers to securely store biometric data on the devices without transmitting it to external servers. Overall the document examines how leading mobile manufacturers are advancing biometric security features to authenticate users and protect sensitive data on smartphones.
A Comparison Based Study on Biometrics for Human RecognitionIOSR Journals
Abstract: A biometric system provides automatic recognition of an individual based on a unique feature or
characteristic possessed by the individual. These biometric characteristic may physiological or behavioral.
Unlike other identification methods such as id proof, tokens and password, the distinct aspect of biometric
recognition comes into light from randomly distributed features in human being. In this paper, I describe the
novel comparison based upon various aspects to make easy selection for biometric device deployment in specific
environment. This paper proposes a comparison among all kind of biometric system available in the society.
The existing computer security systems used at various places like banking, passport, credit cards, smart cards,
PIN , access control and network security are using username and passwords for person identification.
Biometric systems also introduce an aspect of user convenience; it means one can be authorized by representing
himself or herself. In this paper, the main focus is on working principal of biometric technique, the various
biometrics systems and their comparisons.
Keywords: Biometrics, authentication, identification, recognition
Privacy advocates in the UK are questioning the use of biometric identification in schools for children under 16. There are concerns about privacy, data security, lack of parental consent, and the rationale for using biometrics. Administrators counter that biometrics are like ID cards, data is proprietary, and regulation is set locally. To address these issues, a survey will gather public attitudes towards data aggregation, biometrics deployment, RFID, security, and privacy to help understand perspectives.
This document discusses incorporating biometrics like fingerprints and facial recognition into identification systems like driver's licenses and national IDs. It describes AVANTE's biometric registration solutions, which capture biometrics digitally and store them on RFID smart cards. The system is designed to securely register voters by capturing their photos, fingerprints, and signatures biometrically. It aims to prevent counterfeiting and tampering while complying with international biometric standards.
This study evaluated fingerprint quality across two populations, elderly and young, in order to assess age and moisture as potential factors affecting utility image
quality. Specifically, the examination of these variables was conducted on a population over the age of 62, and a
population between the ages of 18 and 25, using two fingerprint recognition devices (capacitance and optical). Collected individual variables included: age, gender,
ethnic background, handedness, moisture content of each index finger, occupation(s), subject's use of hand moisturizer, and prior usage of fingerprint devices. Computed performance measures included failure to
enroll, and quality scores. The results indicated there was statistically significant evidence that both age and moisture affected effectiveness image quality of each index finger at a=0.01 on the optical device, and there was statistically significant evidence that age affected effectiveness image quality of each index finger on the capacitance device, but moisture was only significant for
the right index finger at a=0.01.
1. The document discusses how biometrics can enhance network security by providing unique authentication through physical traits like fingerprints, iris scans, and voice patterns.
2. Biometric systems work by enrolling users through capturing traits, storing trait data, and comparing new trait inputs to what is on file for authentication.
3. Common biometric technologies discussed are fingerprints, iris scanning, handwriting analysis, voiceprints, vein patterns, which can all uniquely identify individuals for security purposes. The document argues that biometrics provide more secure authentication than passwords.
Presented during the Open Source Conference 2012, organized by Accenture and Redhat on December 14th 2012. This presentation discusses Identity Analytics.
By Cyrille Bataller, Managing Director, Accenture Technology Labs
Biometric System Penetration in Resource Constrained Mobile Deviceijbbjournal
This document discusses implementing biometric authentication on mobile devices as a more secure alternative to passwords and PINs. It summarizes that as mobile devices take on more functions, data security is increasingly important. Biometric authentication using characteristics like fingerprints, iris scans, or facial recognition could provide secure and convenient access to mobile devices and data. The document also outlines some of the challenges to implementing biometric security on resource-constrained mobile devices, such as limited battery life, processing power, and screen/keyboard size.
This document discusses content-based image mining techniques for image retrieval. It provides an overview of image mining, describing how image mining goes beyond content-based image retrieval by aiming to discover significant patterns in large image collections according to user queries. The document reviews several existing image mining techniques, including those using color histograms, texture analysis, clustering algorithms like k-means, and association rule mining. It discusses challenges in developing universal image retrieval methods and proposes combining low-level visual features with high-level semantic features. Overall, the document surveys the state of the art in content-based image mining and retrieval.
The document discusses feature selection and classification methods for detecting denial-of-service (DoS) attacks in intrusion detection systems. It proposes using Random Forests for feature selection and k-Nearest Neighbors for classification on the KDD99 dataset. Experimental results show that the proposed approach of using Random Forests to select important features before classifying with k-Nearest Neighbors increases detection accuracy while decreasing false positives compared to other algorithms.
This article argues that implementing biometrics, smart cards, and public key infrastructure (PKI) technologies together can deliver a robust digital identity system to address identity theft. Biometrics provide unique identification of individuals. Smart cards can store biometrics and public keys to verify identities. PKI establishes a framework for secure authentication and encryption through public/private key pairs. The article concludes this "technology trio" may enable trusted e-government and e-commerce by strongly authenticating virtual identities.
The document discusses the use of biometric authentication technologies like fingerprints for ATMs in rural India. It notes that biometric ATMs can help illiterate and barely literate rural residents access banking services by establishing their identity through biometrics rather than passwords. The document outlines some companies in India that are developing biometric solutions for ATMs, including fingerprint authentication systems. It also discusses the benefits of biometric ATMs, how biometric authentication systems work, and provides examples of different biometric technologies like fingerprint recognition and face recognition.
This document is a report on biometric sensors written by Arhind Kumar Gautam for his Information Technology department. It contains an introduction to biometric sensors, a history of biometrics, definitions of biometric terms, descriptions of different types of biometric sensors including physical (fingerprint, face recognition, retina scan) and behavioral (voice recognition, signature) biometrics. It also discusses future applications of biometrics and provides a conclusion on biometric sensors.
This document presents an overview of biometric technologies. It defines biometrics as the science of measuring and analyzing biological data for authentication purposes, such as fingerprints, iris patterns, and voice. The document outlines the basic components of biometric systems including readers, software, and databases. It also categorizes biometrics as physiological (face, fingerprints, etc.) or behavioral (signature, voice). The document discusses several biometric modalities like fingerprint, face, iris and voice recognition and their uses. It covers issues around privacy, cancelable biometrics, and soft biometrics. Overall, the document provides a high-level introduction to biometrics and their applications.
The document summarizes biometric security and fingerprint recognition technology. It defines biometrics as using physical or behavioral traits like fingerprints, iris, face, voice or handwriting to identify individuals. Fingerprints are widely used for authentication and various fingerprint recognition techniques are described, including minutiae-based matching of ridge endings and bifurcations. Applications of fingerprint biometrics include security systems, criminal identification, and border control. Emerging areas include 3D and multi-view fingerprint capture to overcome limitations of contact sensors.
Case study on Usage of Biometrics (Cryptography)Bhargav Amin
This document provides an overview of biometrics and biometric authentication systems. It discusses the history of biometrics, how biometric systems work, performance considerations, different biometric modalities like fingerprints, face recognition and iris recognition. It also covers factors to consider when deciding whether to use biometric technology, different types of biometric systems, and examples of biometric implementation in areas like ATMs, law enforcement and networking. The document aims to provide a comprehensive look at biometrics and its usage.
This document provides an overview of blind authentication, a secure crypto-biometric authentication protocol. It begins with an introduction discussing the primary concerns with biometric authentication systems, such as template protection, user privacy, trust issues between users and servers, and network security. It then reviews related work on addressing these concerns. The document proceeds to explain the blind authentication process, which involves feature extraction, enrollment with a trusted third party, and authentication between a user and server. Features of blind authentication include strong encryption for template protection and privacy while maintaining authentication accuracy. Advantages are template security, non-repudiation, and revocability.
Network security is enhanced through biometrics authentication which uses unique physical traits to verify user identity. Biometrics is more secure than passwords since traits cannot be forgotten, stolen, or easily copied. The document discusses common biometric traits like fingerprints, iris scans, and voice recognition. It explains how biometric systems work by enrolling traits during initial use then comparing submitted traits to stored information for authentication. Biometrics provides stronger security for networks and systems by using the human body as a verification method.
Biometrics refers to the statistical analysis of biological characteristics to identify or verify individuals. It uses automated methods and pattern recognition to analyze physiological or behavioral traits unique to each person, such as fingerprints, iris patterns, voiceprints, and hand geometry. Biometric systems collect and analyze these traits to identify individuals with high accuracy. Major applications of biometrics include security systems, smart cards, and mobile device authentication. Future areas of biometrics may involve DNA scanning, ear shape analysis, and vein pattern recognition.
A brief overview of biometric authentication and the benefits it can have on your business and its overall security. Is biometric authentication something you should be looking into? Find out now...
This document discusses biometric security methods for mobile devices. It begins with an introduction to biometrics and how biometric authentication works. Then it discusses some key biometric security methods used by Apple iPhone and Samsung Galaxy mobile phones, including Touch ID fingerprint scanning and iris scanning. It explains how Apple and Samsung use encrypted enclaves and digital identifiers to securely store biometric data on the devices without transmitting it to external servers. Overall the document examines how leading mobile manufacturers are advancing biometric security features to authenticate users and protect sensitive data on smartphones.
A Comparison Based Study on Biometrics for Human RecognitionIOSR Journals
Abstract: A biometric system provides automatic recognition of an individual based on a unique feature or
characteristic possessed by the individual. These biometric characteristic may physiological or behavioral.
Unlike other identification methods such as id proof, tokens and password, the distinct aspect of biometric
recognition comes into light from randomly distributed features in human being. In this paper, I describe the
novel comparison based upon various aspects to make easy selection for biometric device deployment in specific
environment. This paper proposes a comparison among all kind of biometric system available in the society.
The existing computer security systems used at various places like banking, passport, credit cards, smart cards,
PIN , access control and network security are using username and passwords for person identification.
Biometric systems also introduce an aspect of user convenience; it means one can be authorized by representing
himself or herself. In this paper, the main focus is on working principal of biometric technique, the various
biometrics systems and their comparisons.
Keywords: Biometrics, authentication, identification, recognition
Privacy advocates in the UK are questioning the use of biometric identification in schools for children under 16. There are concerns about privacy, data security, lack of parental consent, and the rationale for using biometrics. Administrators counter that biometrics are like ID cards, data is proprietary, and regulation is set locally. To address these issues, a survey will gather public attitudes towards data aggregation, biometrics deployment, RFID, security, and privacy to help understand perspectives.
This document discusses incorporating biometrics like fingerprints and facial recognition into identification systems like driver's licenses and national IDs. It describes AVANTE's biometric registration solutions, which capture biometrics digitally and store them on RFID smart cards. The system is designed to securely register voters by capturing their photos, fingerprints, and signatures biometrically. It aims to prevent counterfeiting and tampering while complying with international biometric standards.
This study evaluated fingerprint quality across two populations, elderly and young, in order to assess age and moisture as potential factors affecting utility image
quality. Specifically, the examination of these variables was conducted on a population over the age of 62, and a
population between the ages of 18 and 25, using two fingerprint recognition devices (capacitance and optical). Collected individual variables included: age, gender,
ethnic background, handedness, moisture content of each index finger, occupation(s), subject's use of hand moisturizer, and prior usage of fingerprint devices. Computed performance measures included failure to
enroll, and quality scores. The results indicated there was statistically significant evidence that both age and moisture affected effectiveness image quality of each index finger at a=0.01 on the optical device, and there was statistically significant evidence that age affected effectiveness image quality of each index finger on the capacitance device, but moisture was only significant for
the right index finger at a=0.01.
1. The document discusses how biometrics can enhance network security by providing unique authentication through physical traits like fingerprints, iris scans, and voice patterns.
2. Biometric systems work by enrolling users through capturing traits, storing trait data, and comparing new trait inputs to what is on file for authentication.
3. Common biometric technologies discussed are fingerprints, iris scanning, handwriting analysis, voiceprints, vein patterns, which can all uniquely identify individuals for security purposes. The document argues that biometrics provide more secure authentication than passwords.
Presented during the Open Source Conference 2012, organized by Accenture and Redhat on December 14th 2012. This presentation discusses Identity Analytics.
By Cyrille Bataller, Managing Director, Accenture Technology Labs
Biometric System Penetration in Resource Constrained Mobile Deviceijbbjournal
This document discusses implementing biometric authentication on mobile devices as a more secure alternative to passwords and PINs. It summarizes that as mobile devices take on more functions, data security is increasingly important. Biometric authentication using characteristics like fingerprints, iris scans, or facial recognition could provide secure and convenient access to mobile devices and data. The document also outlines some of the challenges to implementing biometric security on resource-constrained mobile devices, such as limited battery life, processing power, and screen/keyboard size.
This document discusses content-based image mining techniques for image retrieval. It provides an overview of image mining, describing how image mining goes beyond content-based image retrieval by aiming to discover significant patterns in large image collections according to user queries. The document reviews several existing image mining techniques, including those using color histograms, texture analysis, clustering algorithms like k-means, and association rule mining. It discusses challenges in developing universal image retrieval methods and proposes combining low-level visual features with high-level semantic features. Overall, the document surveys the state of the art in content-based image mining and retrieval.
The document discusses feature selection and classification methods for detecting denial-of-service (DoS) attacks in intrusion detection systems. It proposes using Random Forests for feature selection and k-Nearest Neighbors for classification on the KDD99 dataset. Experimental results show that the proposed approach of using Random Forests to select important features before classifying with k-Nearest Neighbors increases detection accuracy while decreasing false positives compared to other algorithms.
Este documento parece ser un informe de varias páginas. No hay información sustantiva proporcionada en el texto dado, solo una lista de números de página. Por lo tanto, no es posible proporcionar un resumen significativo con la información proporcionada.
Este documento provee información sobre los desórdenes alimenticios como la anorexia nerviosa y la bulimia nerviosa. Explica que estos trastornos son el resultado de factores psicológicos, familiares, genéticos, ambientales y sociales. También describe los síntomas y posibles complicaciones médicas de cada trastorno y resalta la importancia de buscar tratamiento médico y terapéutico para poder recuperarse de manera saludable.
El documento proporciona orientaciones para crear una página web para un centro educativo utilizando la plataforma educativa de Castilla y León. Explica los pasos para diseñar la página web, incluyendo la creación de carpetas y secciones, y recomienda herramientas como el gestor de contenidos e-ducativa para administrar la página de manera sencilla.
The document discusses a proposed approach for personal identification using palmprint biometrics based on principal line extraction. It begins with an abstract summarizing preprocessing using Gaussian filtering and ROI extraction to smooth images and isolate the palm region. Canny edge detection is then used to extract principal lines by analyzing edge direction and gradient strength. The lines are traced and non-maximum edges suppressed to extract key lines. Templates are generated by dividing images into blocks and identifying those containing lines. Identification is performed by comparing templates to stored ones using distance matching. The document then provides context on palmprint identification and prior approaches before detailing the proposed Canny edge detection based method.
The document discusses improving presentation slides and avoiding depression. It notes that depression is a common illness that interferes with daily life but most people can get better with treatment. The document also states that slides with poor images and formatting can cause depression or put audiences to sleep. It encourages taking the time to develop good, thoughtful slides rather than relying on lazy templates or bullet points.
Recognizing the fact usernames passwords are the weakest link in an.docxdanas19
Recognizing the fact usernames passwords are the weakest link in an organization’s security system because username and password are shareable, and most passwords and usernames are vulnerable and ready to be cracked with a variety of methods using adopting a record number of devices and platforms connected to the Internet of Things daily and at an alarming rate.
Provide the all-inclusive and systematic narratives of the impact of physical biometric operations on the current and future generation.
An Integrated Approach of Physical Biometric Authentication System
Objective
Per Fennelly (2017), every human being is created differently with physical and behavioral traits that are unique; and everyone’s fingerprints, iris, facial feature and body types are entirely different from one another. The effective and efficient use of biometric technology will play a key role in automating a new method of identifying living person based on individual physiological and behavioral characteristics. Protecting sensitive information from vulnerable access by unauthorized users is paramount in our digital world and attempting to identify and mitigating such operation is becoming very challenging and troubling to the entire human society.
Biometric authentication-based identity is playing a vital role in security operations. Traditional authentication approach used to identity logon, logout, username, passwords are no longer enough to battle the identity and security crisis. Physical Biometric processes often allow the authentication of an individual personal data to be stored in a document format for future references. The comparison is often used to determine whether the biometric characteristics of individual match the previously information recorded in the document. Physical biometric systems have proven to be very effective in verification and identification processes.
Physical biometric identification and recognition processes are classified in three groupings including acquisition, feature extraction and comparison. Traditionally, biometric characteristics are acquired through measurements, such as a camera, microphone, fingerprint scanner, gathering of specific characteristics and creation of digital representation, photograph, a voice recording and scanned fingerprint. Most naturally significant areas supporting physical biometric process include corners of the eyes, mouth, nose, chin and likely to be identified by human inspection and through an automated biometric process.
Biometric Access Control is a security system used to provides conditional access after scanning for unique physical characteristics including installing Biometric Access at ATM’s and other public facilities to safeguard financial data. Indeed, when faces, fingers, irises and veins are scanned such data are converted into digital format and a complex algorithm is used to make a match. Such physical biometric processes .
- Biometrics such as fingerprints, iris scans, and facial recognition are increasingly being used for security and identification purposes in applications like access control, e-commerce, banking, and computer login to enhance security. Fingerprint recognition is a mature biometric technique used in this research.
- However, biometrics also present cybersecurity risks if the biometric data is stolen or systems are circumvented. Hackers could potentially force individuals to provide biometric samples or use facsimiles to gain unauthorized access to systems. Proper management of biometric data and systems is needed to mitigate risks.
Facial Feature Recognition Using Biometricsijbuiiir1
Face recognition is one of the few biometric methods that possess the merits of both high accuracy and low intrusiveness. Biometric requires no physical interaction on behalf of the user. Biometric allows to perform passive identification in a one to many environments. Passwords and PINs are hard to remember and can be stolen or guessed; cards, tokens, keys and the like can be misplaced, forgotten, purloined or duplicated; magnetic cards can become corrupted and unreadable. However individuals biological traits cannot be misplaced, forgotten, stolen or forged.
Biometric authentication uses unique human physical and behavioral characteristics for authentication purposes. Physical biometrics include fingerprints, facial patterns, iris scans, and retinal patterns. Behavioral biometrics analyze keystrokes, gait, voice, mouse movements, signatures, and cognition. Biometrics provide stronger authentication than passwords alone but have disadvantages like inability to change compromised biometrics and potential for "master fingerprints" to trick some devices. Biometrics are increasingly used for consumer, government, and corporate authentication.
The document is a seminar presentation on biometrics. It defines biometrics as the science of measuring and analyzing biological data, particularly for authentication purposes such as fingerprints, eye retinas, and facial patterns. It discusses how biometrics can be used for identification and verification. It also covers different categories of biometrics like fingerprints, facial recognition, iris recognition, and more. It discusses the advantages like uniqueness and disadvantages like cost. In conclusion, biometrics is widely used due to its convenience, flexibility, and stability over time.
Biometrics can be used to improve cybersecurity by integrating biometric authentication into daily operations. Biometrics uses unique physical traits like fingerprints, facial recognition, or iris scans to verify a user's identity. While biometrics provides convenient authentication as physical traits are difficult to steal or forget, there are also privacy concerns over collection and potential misuse of biometric data without user consent. The document discusses various biometric technologies, their applications, benefits for cybersecurity, and challenges regarding privacy and potential workarounds to strengthen biometric data protection.
The document discusses the technology of the future. It covers several topics related to biometrics including a brief history, current applications, and the future potential of various biometric technologies such as fingerprints, iris recognition, and voice recognition. The document also discusses how biometric systems work and compares the features and accuracy of different biometric parameters.
Personal authentication using 3 d finger geometry (synopsis)Mumbai Academisc
The document proposes a 3D finger geometry authentication system as an improvement over existing hand geometry authentication methods. It captures 3D information using a low-cost depth sensor to limit constraints on hand placement. It extracts 3D geometry points from the finger and uses those as features for authentication, achieving similar accuracy to other methods but with greater convenience. It segments the finger, finds boundary points, enlarges the image, and extracts geometry points along circles projected inward from the boundary to generate the feature vector for matching. Preliminary results found the proposed system comparable to state-of-the-art hand geometry recognition.
I am Adoitya Kaila .a student of management.here I am presnting a presentation on biometric technology which is considered the most reliable source of security in todays time.i have tried to make it simple for each and everyone .
This document is a seminar report on biometrics technology submitted by Pavan Kumar M.T. to fulfill requirements for a Bachelor of Engineering degree. The report provides an introduction to biometrics, which uses human physiological or behavioral characteristics to identify individuals. It discusses the history of biometrics and provides a block diagram of typical biometrics systems. It also classifies and describes various biometric techniques including fingerprints, face recognition, hand geometry, iris recognition, speaker recognition, signature recognition, and gesture recognition.
An in-depth review on Contactless Fingerprint Identification using Deep LearningIRJET Journal
This document provides an overview of contactless fingerprint identification using deep learning. It discusses previous works that have used 3D fingerprint detection and projection, as well as recurrent convolutional networks to improve compatibility between contactless and contact-based fingerprint systems. The document also outlines the methodology of gathering requirements, designing the system, and implementing necessary modules to effectively identify fingerprints without physical contact.
The Pedanandipadu College Of Arts & Science. Biometrics ABSTRACT: In networking environment, security is a crucial factor. It is not easy to maintain security to confidential matters using Password security mechanism all the time.
This document summarizes biometrics for secure e-transactions using mobile phones. It proposes a multi-biometric model that integrates voice, fingerprint, and facial scanning embedded in a mobile phone to make e-transactions more secure. It discusses how each biometric like facial recognition, fingerprint scanning, and voice recognition works and their practical challenges. Integrating multiple biometrics improves security but also has issues like some populations like the elderly having unreadable biometrics.
Biometric System and Recognition Authentication and Security Issuesijtsrd
This document summarizes a research paper on biometric systems for authentication and security issues. The paper provides an overview of biometric systems and how they are used for authentication. It discusses some of the main types of biometrics like fingerprints, facial recognition, voice recognition, and others. It also covers authentication processes, including enrollment and verification. The paper analyzes security issues like spoofing attacks and discusses liveness detection techniques to help prevent spoofing. It evaluates biometric systems based on authentication accuracy and security. In conclusion, the paper argues that biometrics can provide secure authentication but that future research should focus on improving accuracy under non-ideal conditions and enhancing security against spoofing attacks.
The document discusses biometric devices, including what they are, common types of biometric devices, and how they work. It provides examples of biometric identifiers like fingerprints, DNA, and voice patterns. It also discusses how biometric devices are used for identification and access control in places like educational institutions, hospitals, offices, shopping malls, and housing societies. The document outlines some of the benefits of biometric devices, but also notes potential privacy and security concerns with storing individuals' biometric data.
This document discusses biometrics and biometric encryption. It begins with an introduction to biometrics and biometric principles and standards. It then discusses different methods to securely store cryptographic keys using biometrics, including biometric encryption. The document compares userID-based keys to biometric-based keys. It also covers advantages and threats of biometric systems, as well applications of biometric systems. In conclusion, the document provides an overview of biometrics and biometric encryption.
A comparative study of biometric authentication based on handwritten signatureseSAT Journals
Abstract With the increasing concerns for security, automated systems for authorization and authentication have become enormously important in every sector today. There are many methods for personal identification such as smart cards, PIN (personal Identification Number), passwords, etc. Regardless of the efficiency and accuracy of these systems, these systems can be always be stolen, lost, forgotten, cracked, hacked, etc. And it is for this reason biometric based authentication system have gained a lot of importance worldwide. A biometric system is essentially a pattern-recognition system that recognizes a person based on a feature vector derived from a specific physiological (face, iris, retina, voice, palm prints, hand geometry) or behavioral characteristic (signature, voice, keystroke pattern) that the person possesses. This system is more accurate as these characteristics are unique for a particular person and vary almost negligibly over time. In this paper we have presented a comparative study of recent advances in biometric authentication based on mainly offline Hand-written signatures. Keywords:- Biometrics, online and offline signature verification, authentication, feature extraction, region of interest (ROI), Artificial Neural Network.
This document presents a comparative study of biometric authentication based on handwritten signatures. It discusses offline and online signature verification techniques. For offline verification, the key steps are data acquisition through scanning signatures, preprocessing like segmentation and noise removal, feature extraction such as height-width ratios and pixel densities, and matching signatures using classifiers like neural networks. The document reviews several related works on signature verification and compares their recognition rates. Recognition rates ranged from 61.45% to 99.03% depending on the specific techniques used for preprocessing, feature extraction, and matching.
This document outlines a presentation on biometric authentication. It discusses authentication and its types, biometrics and why they are used, the characteristics and modes of biometric systems, different biometric techniques including fingerprint, face, iris, hand geometry and voice recognition, a comparison of techniques, applications and limitations. The working process of a biometric system including enrollment, authentication, capturing, pre-processing, feature extraction and matching is also summarized.
This document discusses biometrics, which uses physiological or behavioral characteristics to identify individuals. It outlines the history of biometrics dating back to fingerprint use in China in the 14th century. Various biometric techniques are described like fingerprints, facial recognition, iris scans, and hand geometry. Biometrics works by recording and comparing these characteristics using biometric devices and databases. Applications of biometrics include access control systems, e-commerce, banking, and crime investigation. While biometrics provides security, issues around privacy, identity risks, and technology limitations require consideration.
Electrically small antennas: The art of miniaturizationEditor IJARCET
We are living in the technological era, were we preferred to have the portable devices rather than unmovable devices. We are isolating our self rom the wires and we are becoming the habitual of wireless world what makes the device portable? I guess physical dimensions (mechanical) of that particular device, but along with this the electrical dimension is of the device is also of great importance. Reducing the physical dimension of the antenna would result in the small antenna but not electrically small antenna. We have different definition for the electrically small antenna but the one which is most appropriate is, where k is the wave number and is equal to and a is the radius of the imaginary sphere circumscribing the maximum dimension of the antenna. As the present day electronic devices progress to diminish in size, technocrats have become increasingly concentrated on electrically small antenna (ESA) designs to reduce the size of the antenna in the overall electronics system. Researchers in many fields, including RF and Microwave, biomedical technology and national intelligence, can benefit from electrically small antennas as long as the performance of the designed ESA meets the system requirement.
This document provides a comparative study of two-way finite automata and Turing machines. Some key points:
- Two-way finite automata are similar to read-only Turing machines in that they have a finite tape that can be read in both directions, but cannot write to the tape.
- Turing machines have an infinite tape that can be read from and written to, allowing them to recognize recursively enumerable languages.
- Both models are examined in their ability to accept the regular language L={anbm|m,n>0}.
- The time complexity of a two-way finite automaton for this language is O(n2) due to making two passes over the
This document analyzes and compares the performance of the AODV and DSDV routing protocols in a vehicular ad hoc network (VANET) simulation. Simulations were conducted using NS-2, SUMO, and MOVE simulators for a grid map scenario with varying numbers of nodes. The results show that AODV performed better than DSDV in terms of throughput and packet delivery fraction, while DSDV had lower end-to-end delays. However, neither protocol was found to be fully suitable for the highly dynamic VANET environment. The document concludes that further work is needed to develop improved routing protocols optimized for VANETs.
This document discusses the digital circuit layout problem and approaches to solving it using graph partitioning techniques. It begins by introducing the digital circuit layout problem and how it has become more complex with increasing circuit sizes. It then discusses how the problem can be decomposed into subproblems using graph partitioning to assign geometric coordinates to circuit components. The document reviews several traditional approaches to solve the problem, such as the Kernighan-Lin algorithm, and discusses their limitations for larger circuit sizes. It also discusses more recent approaches using evolutionary algorithms and concludes by analyzing the contributions of various approaches.
This document summarizes various data mining techniques that have been used for intrusion detection systems. It first describes the architecture of a data mining-based IDS, including sensors to collect data, detectors to evaluate the data using detection models, a data warehouse for storage, and a model generator. It then discusses supervised and unsupervised learning approaches that have been applied, including neural networks, support vector machines, K-means clustering, and self-organizing maps. Finally, it reviews several related works applying these techniques and compares their results, finding that combinations of approaches can improve detection rates while reducing false alarms.
This document provides an overview of speech recognition systems and recent progress in the field. It discusses different types of speech recognition including isolated word, connected word, continuous speech, and spontaneous speech. Various techniques used in speech recognition are also summarized, such as simulated evolutionary computation, artificial neural networks, fuzzy logic, Kalman filters, and Hidden Markov Models. The document reviews several papers published between 2004-2012 that studied speech recognition methods including using dynamic spectral subband centroids, Kalman filters, biomimetic computing techniques, noise estimation, and modulation filtering. It concludes that Hidden Markov Models combined with MFCC features provide good recognition results for large vocabulary, speaker-independent, continuous speech recognition.
This document discusses integrating two assembly lines, Line A and Line B, based on lean line design concepts to reduce space and operators. It analyzes the current state of the lines using tools like takt time analysis and MTM/UAS studies. Improvements are identified to eliminate waste, including methods improvements, workplace rearrangement, ergonomic changes, and outsourcing. Paper kaizen is conducted and work elements are retimed. The goal is to integrate the lines to better utilize space and manpower while meeting manufacturing standards.
This document summarizes research on the exposure of microwaves from cellular networks. It describes how microwaves interact with biological systems and discusses measurement techniques and safety standards regarding microwave exposure. While some studies have alleged health hazards from microwaves, independent reviews by health organizations have found no evidence that exposure to microwaves below international safety limits causes harm. The document concludes that with precautions like limiting exposure time and using phones with lower SAR ratings, microwaves from cell phones pose minimal health risks.
This document summarizes a research paper that examines the effect of feature reduction in sentiment analysis of online reviews. It uses principle component analysis to reduce the number of features (product attributes) from a dataset of 500 camera reviews labeled as positive or negative. Two models are developed - one using the original set of 95 product attributes, and one using the reduced set. Support vector machines and naive Bayes classifiers are applied to both models and their performance is evaluated to determine if classification accuracy can be maintained while using fewer features. The results show it is possible to achieve similar accuracy levels with less features, improving computational efficiency.
This document provides a review of multispectral palm image fusion techniques. It begins with an introduction to biometrics and palm print identification. Different palm print images capture different spectral information about the palm. The document then reviews several pixel-level fusion methods for combining multispectral palm images, finding that Curvelet transform performs best at preserving discriminative patterns. It also discusses hardware for capturing multispectral palm images and the process of region of interest extraction and localization. Common fusion methods like wavelet transform and Curvelet transform are also summarized.
This document describes a vehicle theft detection system that uses radio frequency identification (RFID) technology. The system involves embedding an RFID chip in each vehicle that continuously transmits a unique identification signal. When a vehicle is stolen, the owner reports it to the police, who upload the vehicle's information to a central database. Police vehicles are equipped with RFID receivers. If a stolen vehicle passes within range of a receiver, the receiver detects the vehicle's ID signal and displays its details on a tablet. This allows police to quickly identify and recover stolen vehicles. The system aims to make it difficult for thieves to hide a vehicle's identity and allows vehicles to be tracked globally wherever the detection system is implemented.
This document discusses and compares two techniques for image denoising using wavelet transforms: Dual-Tree Complex DWT and Double-Density Dual-Tree Complex DWT. Both techniques decompose an image corrupted by noise using filter banks, apply thresholding to the wavelet coefficients, and reconstruct the image. The Double-Density Dual-Tree Complex DWT yields better denoising results than the Dual-Tree Complex DWT as it produces more directional wavelets and is less sensitive to shifts and noise variance. Experimental results on test images demonstrate that the Double-Density method achieves higher peak signal-to-noise ratios, especially at higher noise levels.
This document compares the k-means and grid density clustering algorithms. It summarizes that grid density clustering determines dense grids based on the densities of neighboring grids, and is able to handle different shaped clusters in multi-density environments. The grid density algorithm does not require distance computation and is not dependent on the number of clusters being known in advance like k-means. The document concludes that grid density clustering is better than k-means clustering as it can handle noise and outliers, find arbitrary shaped clusters, and has lower time complexity.
This document proposes a method for detecting, localizing, and extracting text from videos with complex backgrounds. It involves three main steps:
1. Text detection uses corner metric and Laplacian filtering techniques independently to detect text regions. Corner metric identifies regions with high curvature, while Laplacian filtering highlights intensity discontinuities. The results are combined through multiplication to reduce noise.
2. Text localization then determines the accurate boundaries of detected text strings.
3. Text binarization filters background pixels to extract text pixels for recognition. Thresholding techniques are used to convert localized text regions to binary images.
The method exploits different text properties to detect text using corner metric and Laplacian filtering. Combining the results improves
This document describes the design and implementation of a low power 16-bit arithmetic logic unit (ALU) using clock gating techniques. A variable block length carry skip adder is used in the arithmetic unit to reduce power consumption and improve performance. The ALU uses a clock gating circuit to selectively clock only the active arithmetic or logic unit, reducing dynamic power dissipation from unnecessary clock charging/discharging. The ALU was simulated in VHDL and synthesized for a Xilinx Spartan 3E FPGA, achieving a maximum frequency of 65.19MHz at 1.98mW power dissipation, demonstrating improved performance over a conventional ALU design.
This document describes using particle swarm optimization (PSO) and genetic algorithms (GA) to tune the parameters of a proportional-integral-derivative (PID) controller for an automatic voltage regulator (AVR) system. PSO and GA are used to minimize the objective function by adjusting the PID parameters to achieve optimal step response with minimal overshoot, settling time, and rise time. The results show that PSO provides high-quality solutions within a shorter calculation time than other stochastic methods.
This document discusses implementing trust negotiations in multisession transactions. It proposes a framework that supports voluntary and unexpected interruptions, allowing negotiating parties to complete negotiations despite temporary unavailability of resources. The Trust-x protocol addresses issues related to validity, temporary loss of data, and extended unavailability of one negotiator. It allows a peer to suspend an ongoing negotiation and resume it with another authenticated peer. Negotiation portions and intermediate states can be safely and privately passed among peers to guarantee stability for continued suspended negotiations. An ontology is also proposed to provide formal specification of concepts and relationships, which is essential in complex web service environments for sharing credential information needed to establish trust.
This document discusses and compares various nature-inspired optimization algorithms for resolving the mixed pixel problem in remote sensing imagery, including Biogeography-Based Optimization (BBO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). It provides an overview of each algorithm, explaining key concepts like migration and mutation in BBO. The document aims to prove that BBO is the best algorithm for resolving the mixed pixel problem by comparing it to other evolutionary algorithms. It also includes figures illustrating concepts like the species model and habitat in BBO.
This document discusses principal component analysis (PCA) for face recognition. It begins with an introduction to face recognition and PCA. PCA works by calculating eigenvectors from a set of face images, which represent the principal components that account for the most variance in the image data. These eigenvectors are called "eigenfaces" and can be used to reconstruct the face images. The document then discusses how the system is implemented, including preparing a face database, normalizing the training images, calculating the eigenfaces/principal components, projecting the face images into this reduced space, and recognizing faces by calculating distances between projected test images and training images.
This document summarizes research on using wireless sensor networks to detect mobile targets. It discusses two optimization problems: 1) maximizing the exposure of the least exposed path within a sensor budget, and 2) minimizing sensor installation costs while ensuring all paths have exposure above a threshold. It proposes using tabu search heuristics to provide near-optimal solutions. The research also addresses extending the models to consider wireless connectivity, heterogeneous sensors, and intrusion detection using a game theory approach. Experimental results show the proposed mobile replica detection scheme can rapidly detect replicas with no false positives or negatives.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/