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.
The document provides an overview of biometric security systems. It defines biometrics as measuring unique human characteristics and discusses various physiological and behavioral biometric traits used for identification, including fingerprints, facial recognition, voice recognition, hand geometry, retina and iris scanning. It covers classification of biometric traits, factors for determining their effectiveness, functions of biometric systems, and concerns regarding privacy, standardization and overreliance. The document concludes by discussing potential future applications of biometric technologies in hospitals, forensics and membership programs.
Biometricstechnology in iot and machine learningAnkit Gupta
Ravi Kumar presented on biometrics technology. The presentation discussed what biometrics is, the importance of biometrics for security and convenience, and the history of biometrics. It described various physical and behavioral biometric characteristics like fingerprints, face recognition, iris scans, and voice recognition. Applications of biometrics technology discussed included access control, time and attendance tracking, and use at airports and ATMs. Both advantages like uniqueness and accountability and disadvantages like costs and potential for false readings were covered. Emerging biometric technologies of the future may include ear shape, body odor, and DNA identification.
Biometrics uses measurements of physical and behavioral characteristics to authenticate identity. During enrollment, a biometric sample is taken and stored in a database. When authenticating, a new sample is taken and matched against stored data. If the samples match within a set threshold, access is granted. Common biometric traits include fingerprints, iris scans, facial recognition, voice recognition, and hand geometry. While effective, biometrics raise privacy and security concerns if biometric data is stolen or shared without consent. Implementation also faces challenges of user acceptance, high costs, and accuracy limitations. Overall, biometrics can reliably verify identities but organizations must consider implications and mitigate risks to privacy.
Using (Bio)Metrics To Predict Code Quality Onlines-mueller
Finding and fixing code quality concerns, such as defects or poor understandability of code, decreases software development and evolution costs. A common industrial practice to identify code quality concerns early on are code reviews. While code reviews help to identify problems early on, they also impose costs on development and only take place after a code change is already completed. The goal of our research is to automatically identify code quality concerns while a developer is making a change to the code. By using biometrics, such as heart rate variability, we aim to determine the difficulty a developer experiences working on a part of the code as well as identify and help to fix code quality concerns before they are even committed to the repository. In a field study with ten professional developers over a two-week period we investigated the use of biometrics to determine code quality concerns. Our results show that biometrics are indeed able to predict quality concerns of parts of the code while a developer is working on, improving upon a naive classifier by more than 26% and outperforming classifiers based on more traditional metrics. In a second study with five professional developers from a different country and company, we found evidence that some of our findings from our initial study can be replicated. Overall, the results from the presented studies suggest that biometrics have the potential to predict code quality concerns online and thus lower development and evolution costs.
Biometric security uses physical attributes such as fingerprints, palm veins, eyes, face, and voice to uniquely identify individuals, often for security purposes. Main biometric security systems include fingerprint readers, palm vein scanners, eye/retinal scanners, and facial and vocal recognition software. Fingerprint reading and palm vein scanning systems are compared based on factors like cost, accuracy, and difficulty to forge. Biometric security has applications in physical security, computer login, work access control, file access, ID verification, data encryption, and potential future uses like biometric digital wallets.
The document discusses various topics related to biometrics including:
1. Biometrics can be used for physical access control, ATM access, and authenticating transactions over the telephone or from home computers. Fingerprints, iris scans, and facial recognition are some common biometric technologies used.
2. Early biometrics systems from the 1880s involved precise body measurements and physical descriptions but failed by 1903. Modern biometrics use automated methods to recognize individuals based on physiological or behavioral characteristics.
3. Biometrics are part of identity management and can help with security, national security threats, accountability, and optimizing resources. However, biometrics also have limitations like environmental factors affecting performance.
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.
The document provides an overview of biometric security systems. It defines biometrics as measuring unique human characteristics and discusses various physiological and behavioral biometric traits used for identification, including fingerprints, facial recognition, voice recognition, hand geometry, retina and iris scanning. It covers classification of biometric traits, factors for determining their effectiveness, functions of biometric systems, and concerns regarding privacy, standardization and overreliance. The document concludes by discussing potential future applications of biometric technologies in hospitals, forensics and membership programs.
Biometricstechnology in iot and machine learningAnkit Gupta
Ravi Kumar presented on biometrics technology. The presentation discussed what biometrics is, the importance of biometrics for security and convenience, and the history of biometrics. It described various physical and behavioral biometric characteristics like fingerprints, face recognition, iris scans, and voice recognition. Applications of biometrics technology discussed included access control, time and attendance tracking, and use at airports and ATMs. Both advantages like uniqueness and accountability and disadvantages like costs and potential for false readings were covered. Emerging biometric technologies of the future may include ear shape, body odor, and DNA identification.
Biometrics uses measurements of physical and behavioral characteristics to authenticate identity. During enrollment, a biometric sample is taken and stored in a database. When authenticating, a new sample is taken and matched against stored data. If the samples match within a set threshold, access is granted. Common biometric traits include fingerprints, iris scans, facial recognition, voice recognition, and hand geometry. While effective, biometrics raise privacy and security concerns if biometric data is stolen or shared without consent. Implementation also faces challenges of user acceptance, high costs, and accuracy limitations. Overall, biometrics can reliably verify identities but organizations must consider implications and mitigate risks to privacy.
Using (Bio)Metrics To Predict Code Quality Onlines-mueller
Finding and fixing code quality concerns, such as defects or poor understandability of code, decreases software development and evolution costs. A common industrial practice to identify code quality concerns early on are code reviews. While code reviews help to identify problems early on, they also impose costs on development and only take place after a code change is already completed. The goal of our research is to automatically identify code quality concerns while a developer is making a change to the code. By using biometrics, such as heart rate variability, we aim to determine the difficulty a developer experiences working on a part of the code as well as identify and help to fix code quality concerns before they are even committed to the repository. In a field study with ten professional developers over a two-week period we investigated the use of biometrics to determine code quality concerns. Our results show that biometrics are indeed able to predict quality concerns of parts of the code while a developer is working on, improving upon a naive classifier by more than 26% and outperforming classifiers based on more traditional metrics. In a second study with five professional developers from a different country and company, we found evidence that some of our findings from our initial study can be replicated. Overall, the results from the presented studies suggest that biometrics have the potential to predict code quality concerns online and thus lower development and evolution costs.
Biometric security uses physical attributes such as fingerprints, palm veins, eyes, face, and voice to uniquely identify individuals, often for security purposes. Main biometric security systems include fingerprint readers, palm vein scanners, eye/retinal scanners, and facial and vocal recognition software. Fingerprint reading and palm vein scanning systems are compared based on factors like cost, accuracy, and difficulty to forge. Biometric security has applications in physical security, computer login, work access control, file access, ID verification, data encryption, and potential future uses like biometric digital wallets.
The document discusses various topics related to biometrics including:
1. Biometrics can be used for physical access control, ATM access, and authenticating transactions over the telephone or from home computers. Fingerprints, iris scans, and facial recognition are some common biometric technologies used.
2. Early biometrics systems from the 1880s involved precise body measurements and physical descriptions but failed by 1903. Modern biometrics use automated methods to recognize individuals based on physiological or behavioral characteristics.
3. Biometrics are part of identity management and can help with security, national security threats, accountability, and optimizing resources. However, biometrics also have limitations like environmental factors affecting performance.
This document summarizes a presentation on biometric systems. It begins by defining biometric systems as automated methods of identifying individuals based on physiological or behavioral characteristics. It then outlines the objectives of exploring biometric applications in management. It discusses types of biometrics like fingerprints and facial recognition. It explains how biometric systems work by enrolling reference templates and comparing them to new samples. It also covers benefits of biometric systems like security, convenience and accountability. Risks are discussed along with recommendations to ensure security of biometric data. The document concludes by noting biometric systems require careful risk analysis and implementation based on the environment.
IRJET- Secure Vault System using Iris Biometrics and PIC MicrocontrollerIRJET Journal
This document describes a secure vault system using iris biometrics and a PIC microcontroller for authentication. The system works by capturing iris images, segmenting the iris region, extracting features from the iris, and matching features to stored templates to authenticate users. When a match is found, the locker number is sent via RF transmitter to a robot, which then opens the corresponding locker. The system aims to provide a more secure and convenient alternative to traditional locker systems.
This document discusses biometric devices and their use for security and identification. It describes that biometrics uses human characteristics like fingerprints, iris scans, etc. to identify individuals. There are two main types of biometrics - behavioral (signatures, keystrokes) and physical (fingerprints, iris scans). Biometric devices work by recording these characteristics, extracting identifying features, and comparing new samples to stored references. Examples of biometric devices are fingerprint, palm, face, and iris scanners. The document also describes one biometric device called Bio-Star 09 and its use for employee attendance tracking and access control.
The document discusses biometrics, which is the study of methods for uniquely recognizing humans based on physical and behavioral traits. Some examples of physiological biometrics are fingerprint, face recognition, DNA, hand and palm geometry, and iris recognition. Behavioral biometrics include typing rhythm, gait, and voice. The document then explains the process of biometric systems which involves capturing biometric data, creating a template, storing it in a database, and comparing new captures against stored templates to authenticate users. It discusses some challenges with biometric technologies including privacy issues, discrimination concerns, and the permanence of biometrics.
The document discusses biometrics, which uses measurable physiological or behavioral characteristics to identify or verify the identity of individuals. It defines biometrics and explains how they work by capturing a biometric trait, converting it to a digital template, and storing it in a database for future matching. Common biometric traits include fingerprints, iris scans, voice recognition, and facial recognition. While biometrics provide stronger authentication than passwords, they also pose privacy and performance issues if an individual's biometric template is compromised or their traits change over time.
The document discusses biometrics, which uses physical or behavioral characteristics to identify individuals. It describes various biometric modalities like fingerprints, facial recognition, iris scans, and voice recognition. These are increasingly used for security applications like building access, computer login, and banking. Biometrics provides stronger authentication than passwords or ID cards, but has concerns around privacy and implementation costs. Overall, the document argues that multi-modal biometric systems offer greater security and are likely to see continued growth and adoption.
This document discusses key considerations for protecting critical infrastructure from cybersecurity threats involving biometrics. It notes that while biometrics can strengthen security, biometric systems themselves must be secured against attacks. The document outlines vulnerabilities across different stages of biometric systems and recommends countermeasures like multi-factor authentication, flexible technology, and ongoing analysis to adapt to evolving threats. The overall message is that cybersecurity requires a holistic defense-in-depth approach when using biometrics to authenticate identity.
The document discusses biometric systems for security. It defines biometrics as measuring biological traits to identify individuals. It then discusses the history of biometrics using fingerprinting in China in the 14th century. It describes the main types of biometric devices as behavioral (e.g. voice, signature) or physical (e.g. fingerprint, face) and lists their common uses including banking, attendance tracking, and data security. Finally, it compares biometric security to other methods and outlines some limitations such as noise in data and variations over time.
This document provides an overview of fingerprint identification systems, including their history, components, and applications. It discusses the types of fingerprints and how they are sensed and matched using algorithms. Fingerprint identification has been used for centuries for transactions and is now widely used in government and commercial applications, with systems integrated onto chips. Challenges include handling poor quality images and certain medical conditions, while companies produce sensors, algorithms, and full biometric solutions.
This document discusses finger vein authentication technology. It begins with an introduction and overview of biometrics and finger vein authentication. It then describes the four components of finger vein detection and authentication: image acquisition, pre-processing, extraction, and matching. It highlights benefits of finger vein authentication such as accuracy, speed, security, compact size, and difficulty to forge. It concludes with examples of applications for finger vein authentication such as PC login, identity management, time/attendance tracking, cashless catering, banking, and access control for secure areas.
“Enhancing Iris Scanning Using Visual Cryptography”iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Introduction
The term “biometrics” is derived from the Greek words “bio” (life) and “metrics” (to measure). Automated biometric systems have only become available over the last few decades, due to significant advances in the field of computer processing. Many of these new automated techniques, however, are based on ideas that were originally conceived hundreds, even thousands of years ago.
One of the oldest and most basic examples of a characteristic that is used for recognition by humans is the face. Since the beginning of civilization, humans have used faces to identify known (familiar) and unknown (unfamiliar) individuals. This simple task became increasingly more challenging as populations increased and as more convenient methods of travel introduced many new individuals into- once small communities. The concept of human-to-human recognition is also seen in behavioral-predominant biometrics such as speaker and gait recognition. Individuals use these characteristics, somewhat unconsciously, to recognize known individuals on a day-to-day basis.
This document discusses various biometric techniques for user authentication. It begins by defining biometrics as the automated measurement of physiological and behavioral characteristics to determine or verify identity. The document then covers the requirements for an ideal biometric technique, describes different biometric methods like fingerprint scanning, facial recognition, retina scanning, and others. It also discusses factors for evaluating biometric techniques and compares the strengths and weaknesses of different methods. Fingerprint technology and potential threats are explained in detail.
In the age of Biometric Security taking over the traditional security features, this is a small intro to the Biometric features one can use to enhance the security. The various modalities have been explained.
IRIS Recognition Based Authentication System In ATMIJTET Journal
Security and Authentication of individuals is necessary for our daily lives especially in ATMs. It has been improved by using biometric verification techniques like face recognition, fingerprints, voice and other traits, comparing these existing traits, there is still need for considerable computer vision. Iris recognition is a particular type of biometric system that can be used to reliably identify a person uniquely by analyzing the patterns found in the iris. Initially Iris images are collected as datasets and maintained in agent memory. Then the Iris and pupil are detected from the image, removing noises. The features of the iris were encoded by convolving the normalized iris region with 2DGabor filter. The Hamming distance was chosen as a matching metric, which gave the measure of how many bits disagreed between the templates of the iris.
This presentation discusses biometric authentication methods for enhancing security. It covers phases of biometric systems including capture, extraction, comparison and match/no match. Fingerprint recognition is described as the oldest method dating back to 1896 and widely used for criminal identification. The presentation also discusses other biometric techniques like hand geometry recognition, facial recognition analyzing attributes like eye sockets and mouth, voice recognition using formants, iris recognition using unique iris patterns, and emerging biometrics like vein scans, facial thermography, gait recognition, blood pulse, ear shape recognition and odor sensing. Biometric technologies can achieve e-commerce and e-government promises through strong personal authentication and each technique's performance varies by usage and environment.
This document discusses various biometric security systems used for identification and verification. It describes physiological biometrics like fingerprint, iris, retina, and facial recognition that analyze unique physical characteristics. It also covers behavioral biometrics like signature, voice recognition, and hand geometry that analyze unique behavioral characteristics. For each biometric method, it explains how the technology works, its accuracy, advantages and limitations. It emphasizes that multimodal biometric systems integrating multiple technologies provide more secure authentication.
The document discusses the use of biometrics in Aadhar cards, PAN cards, and fingerprint lock apps in India. It provides background on each type of identification and how biometrics were integrated. For Aadhar cards, fingerprints and iris scans were added to uniquely identify individuals and prevent fraud. This increased security and convenience. PAN cards were also linked to Aadhar cards and now use biometrics like fingerprints to authenticate identity. Fingerprint lock apps use biometrics to securely lock phones based on unique fingerprints, improving privacy. Biometrics thus enhance security and authentication across many identification systems in India.
This document provides an introduction to biometric security systems. It discusses how biometrics has evolved from early manual criminal identification techniques to modern automated systems. It describes some of the first commercial biometric devices used over 25 years ago for timekeeping and access control. It then summarizes several common biometric modalities used in existing security systems, including fingerprint, face, signature, voice, and gait recognition.
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.
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.
This document discusses various biometric identification techniques including 3D facial recognition, iris recognition, and keystroke dynamics. It provides details on how each method works, advantages, limitations, and applications. 3D facial recognition involves capturing a facial image and transforming it into a unique face print using elastic graph matching algorithms to allow identification from several meters away. Iris recognition uses the colored iris surrounding the eye which is stable over a person's lifetime allowing identification with low error rates. Keystroke dynamics analyzes typing patterns such as keystroke duration and pressure to continuously authenticate computer users with minimal hardware requirements.
This document summarizes a presentation on biometric systems. It begins by defining biometric systems as automated methods of identifying individuals based on physiological or behavioral characteristics. It then outlines the objectives of exploring biometric applications in management. It discusses types of biometrics like fingerprints and facial recognition. It explains how biometric systems work by enrolling reference templates and comparing them to new samples. It also covers benefits of biometric systems like security, convenience and accountability. Risks are discussed along with recommendations to ensure security of biometric data. The document concludes by noting biometric systems require careful risk analysis and implementation based on the environment.
IRJET- Secure Vault System using Iris Biometrics and PIC MicrocontrollerIRJET Journal
This document describes a secure vault system using iris biometrics and a PIC microcontroller for authentication. The system works by capturing iris images, segmenting the iris region, extracting features from the iris, and matching features to stored templates to authenticate users. When a match is found, the locker number is sent via RF transmitter to a robot, which then opens the corresponding locker. The system aims to provide a more secure and convenient alternative to traditional locker systems.
This document discusses biometric devices and their use for security and identification. It describes that biometrics uses human characteristics like fingerprints, iris scans, etc. to identify individuals. There are two main types of biometrics - behavioral (signatures, keystrokes) and physical (fingerprints, iris scans). Biometric devices work by recording these characteristics, extracting identifying features, and comparing new samples to stored references. Examples of biometric devices are fingerprint, palm, face, and iris scanners. The document also describes one biometric device called Bio-Star 09 and its use for employee attendance tracking and access control.
The document discusses biometrics, which is the study of methods for uniquely recognizing humans based on physical and behavioral traits. Some examples of physiological biometrics are fingerprint, face recognition, DNA, hand and palm geometry, and iris recognition. Behavioral biometrics include typing rhythm, gait, and voice. The document then explains the process of biometric systems which involves capturing biometric data, creating a template, storing it in a database, and comparing new captures against stored templates to authenticate users. It discusses some challenges with biometric technologies including privacy issues, discrimination concerns, and the permanence of biometrics.
The document discusses biometrics, which uses measurable physiological or behavioral characteristics to identify or verify the identity of individuals. It defines biometrics and explains how they work by capturing a biometric trait, converting it to a digital template, and storing it in a database for future matching. Common biometric traits include fingerprints, iris scans, voice recognition, and facial recognition. While biometrics provide stronger authentication than passwords, they also pose privacy and performance issues if an individual's biometric template is compromised or their traits change over time.
The document discusses biometrics, which uses physical or behavioral characteristics to identify individuals. It describes various biometric modalities like fingerprints, facial recognition, iris scans, and voice recognition. These are increasingly used for security applications like building access, computer login, and banking. Biometrics provides stronger authentication than passwords or ID cards, but has concerns around privacy and implementation costs. Overall, the document argues that multi-modal biometric systems offer greater security and are likely to see continued growth and adoption.
This document discusses key considerations for protecting critical infrastructure from cybersecurity threats involving biometrics. It notes that while biometrics can strengthen security, biometric systems themselves must be secured against attacks. The document outlines vulnerabilities across different stages of biometric systems and recommends countermeasures like multi-factor authentication, flexible technology, and ongoing analysis to adapt to evolving threats. The overall message is that cybersecurity requires a holistic defense-in-depth approach when using biometrics to authenticate identity.
The document discusses biometric systems for security. It defines biometrics as measuring biological traits to identify individuals. It then discusses the history of biometrics using fingerprinting in China in the 14th century. It describes the main types of biometric devices as behavioral (e.g. voice, signature) or physical (e.g. fingerprint, face) and lists their common uses including banking, attendance tracking, and data security. Finally, it compares biometric security to other methods and outlines some limitations such as noise in data and variations over time.
This document provides an overview of fingerprint identification systems, including their history, components, and applications. It discusses the types of fingerprints and how they are sensed and matched using algorithms. Fingerprint identification has been used for centuries for transactions and is now widely used in government and commercial applications, with systems integrated onto chips. Challenges include handling poor quality images and certain medical conditions, while companies produce sensors, algorithms, and full biometric solutions.
This document discusses finger vein authentication technology. It begins with an introduction and overview of biometrics and finger vein authentication. It then describes the four components of finger vein detection and authentication: image acquisition, pre-processing, extraction, and matching. It highlights benefits of finger vein authentication such as accuracy, speed, security, compact size, and difficulty to forge. It concludes with examples of applications for finger vein authentication such as PC login, identity management, time/attendance tracking, cashless catering, banking, and access control for secure areas.
“Enhancing Iris Scanning Using Visual Cryptography”iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Introduction
The term “biometrics” is derived from the Greek words “bio” (life) and “metrics” (to measure). Automated biometric systems have only become available over the last few decades, due to significant advances in the field of computer processing. Many of these new automated techniques, however, are based on ideas that were originally conceived hundreds, even thousands of years ago.
One of the oldest and most basic examples of a characteristic that is used for recognition by humans is the face. Since the beginning of civilization, humans have used faces to identify known (familiar) and unknown (unfamiliar) individuals. This simple task became increasingly more challenging as populations increased and as more convenient methods of travel introduced many new individuals into- once small communities. The concept of human-to-human recognition is also seen in behavioral-predominant biometrics such as speaker and gait recognition. Individuals use these characteristics, somewhat unconsciously, to recognize known individuals on a day-to-day basis.
This document discusses various biometric techniques for user authentication. It begins by defining biometrics as the automated measurement of physiological and behavioral characteristics to determine or verify identity. The document then covers the requirements for an ideal biometric technique, describes different biometric methods like fingerprint scanning, facial recognition, retina scanning, and others. It also discusses factors for evaluating biometric techniques and compares the strengths and weaknesses of different methods. Fingerprint technology and potential threats are explained in detail.
In the age of Biometric Security taking over the traditional security features, this is a small intro to the Biometric features one can use to enhance the security. The various modalities have been explained.
IRIS Recognition Based Authentication System In ATMIJTET Journal
Security and Authentication of individuals is necessary for our daily lives especially in ATMs. It has been improved by using biometric verification techniques like face recognition, fingerprints, voice and other traits, comparing these existing traits, there is still need for considerable computer vision. Iris recognition is a particular type of biometric system that can be used to reliably identify a person uniquely by analyzing the patterns found in the iris. Initially Iris images are collected as datasets and maintained in agent memory. Then the Iris and pupil are detected from the image, removing noises. The features of the iris were encoded by convolving the normalized iris region with 2DGabor filter. The Hamming distance was chosen as a matching metric, which gave the measure of how many bits disagreed between the templates of the iris.
This presentation discusses biometric authentication methods for enhancing security. It covers phases of biometric systems including capture, extraction, comparison and match/no match. Fingerprint recognition is described as the oldest method dating back to 1896 and widely used for criminal identification. The presentation also discusses other biometric techniques like hand geometry recognition, facial recognition analyzing attributes like eye sockets and mouth, voice recognition using formants, iris recognition using unique iris patterns, and emerging biometrics like vein scans, facial thermography, gait recognition, blood pulse, ear shape recognition and odor sensing. Biometric technologies can achieve e-commerce and e-government promises through strong personal authentication and each technique's performance varies by usage and environment.
This document discusses various biometric security systems used for identification and verification. It describes physiological biometrics like fingerprint, iris, retina, and facial recognition that analyze unique physical characteristics. It also covers behavioral biometrics like signature, voice recognition, and hand geometry that analyze unique behavioral characteristics. For each biometric method, it explains how the technology works, its accuracy, advantages and limitations. It emphasizes that multimodal biometric systems integrating multiple technologies provide more secure authentication.
The document discusses the use of biometrics in Aadhar cards, PAN cards, and fingerprint lock apps in India. It provides background on each type of identification and how biometrics were integrated. For Aadhar cards, fingerprints and iris scans were added to uniquely identify individuals and prevent fraud. This increased security and convenience. PAN cards were also linked to Aadhar cards and now use biometrics like fingerprints to authenticate identity. Fingerprint lock apps use biometrics to securely lock phones based on unique fingerprints, improving privacy. Biometrics thus enhance security and authentication across many identification systems in India.
This document provides an introduction to biometric security systems. It discusses how biometrics has evolved from early manual criminal identification techniques to modern automated systems. It describes some of the first commercial biometric devices used over 25 years ago for timekeeping and access control. It then summarizes several common biometric modalities used in existing security systems, including fingerprint, face, signature, voice, and gait recognition.
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.
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.
This document discusses various biometric identification techniques including 3D facial recognition, iris recognition, and keystroke dynamics. It provides details on how each method works, advantages, limitations, and applications. 3D facial recognition involves capturing a facial image and transforming it into a unique face print using elastic graph matching algorithms to allow identification from several meters away. Iris recognition uses the colored iris surrounding the eye which is stable over a person's lifetime allowing identification with low error rates. Keystroke dynamics analyzes typing patterns such as keystroke duration and pressure to continuously authenticate computer users with minimal hardware requirements.
BIOMETRICS AUTHENTICATION TECHNIQUE FOR INTRUSION DETECTION SYSTEMS USING FIN...IJCSEIT Journal
Identifying attackers is a major apprehension to both organizations and governments. Recently, the most
used applications for prevention or detection of attacks are intrusion detection systems. Biometrics
technology is simply the measurement and use of the unique characteristics of living humans to distinguish
them from one another and it is more useful as compare to passwords and tokens as they can be lost or
stolen so we have choose the technique biometric authentication. The biometric authentication provides the
ability to require more instances of authentication in such a quick and easy manner that users are not
bothered by the additional requirements. In this paper, we have given a brief introduction about
biometrics. Then we have given the information regarding the intrusion detection system and finally we
have proposed a method which is based on fingerprint recognition which would allow us to detect more
efficiently any abuse of the computer system that is running.
Biometric Security advantages and disadvantagesPrabh Jeet
Biometrics refers to authentication techniques that rely on measurable physiological and individual characteristics to automatically verify identity. A biometric system uses behavioral or biological traits like fingerprints, iris scans, or voice to identify or verify individuals. Identification involves searching a biometric sample against a database of templates, while verification compares a sample to a single stored template. Biometrics are increasingly used for security applications like access control and transactions due to their convenience and effectiveness compared to traditional authentication methods.
This document discusses biometrics, which uses human body characteristics for authentication purposes. It describes biometric devices that scan and digitize characteristics like fingerprints, irises, and facial patterns. Biometrics can be physiological (fingerprints, iris scans) or behavioral (signatures, voice). To work, characteristics must be universal, unique, and permanent for each individual. Biometric systems enroll users by storing their data, and then verify identities by matching live scans to enrolled data. Examples of biometric technologies discussed include fingerprint recognition, face recognition using facial features, voice recognition, iris recognition using iris patterns, and signature verification.
The document discusses biometrics, which is the automated identification or verification of human identity through physiological and behavioral traits. It covers the history of biometrics, different biometric categories like fingerprints, iris scans, and voice recognition. It also discusses identification versus authentication modes, accuracy metrics, applications in various sectors, advantages, disadvantages and limitations of biometrics. The conclusion is that while biometrics provide strong authentication, a balance between security and privacy needs to be achieved as technologies advance.
This document summarizes the process of iris recognition for biometric authentication. It begins with image acquisition of the iris using a camera. Next, iris localization is performed to isolate the iris region from the rest of the eye image. Finally, pattern matching is done by converting the iris image into a numeric iris code template using Gabor wavelets to extract distinguishing features of the iris texture and patterns. This iris code provides a highly accurate means of identifying individuals due to the richness of distinguishing details in the iris structure.
This document discusses the implementation of biometric voting systems through computer networks using fingerprints. It begins by introducing biometrics and how fingerprints are commonly used for identification. It then examines how a biometric voting system would work, including voters registering their fingerprint templates in a database, logging into a voting website, selecting a candidate, and having their fingerprint scanned to cast their vote. The document evaluates different biometric methods and argues that fingerprints are most efficient and accurate. It also discusses challenges with biometric systems, such as false acceptance and rejection rates.
This document discusses various biometric technologies including fingerprint recognition, iris scanning, retina scanning, voice recognition, signature verification, face recognition, and hand geometry recognition. It describes how each type of biometric works, including capturing biometric data, extracting distinguishing features, enrollment, verification, and matching against stored templates. Biometrics are increasingly used for identification and access control because they cannot be lost, stolen, or forgotten like ID cards or passwords. However, biometric systems must also account for changes in biometrics over time.
This document discusses biometrics, which uses human body characteristics to authenticate identity. It describes how biometric devices work by scanning a trait, converting it to digital form, and comparing it to stored data. There are two main classes of biometrics: physiological (face, fingerprints, iris) and behavioral (signature, voice). Biometrics has advantages like accuracy but also disadvantages like cost and the possibility that some traits may change over time.
This document discusses biometrics, which uses human body characteristics to authenticate identity. It describes biometric devices that scan and digitize characteristics like fingerprints, irises, voice patterns. Biometrics can be physiological (face, fingerprints) or behavioral (signature, voice). To be used for identification, characteristics must be universal, unique, permanent, collectible, and difficult to circumvent. The document outlines various biometric modalities like fingerprint recognition, face recognition, voice recognition, and iris recognition. It also discusses advantages like accuracy but notes disadvantages like cost and changing characteristics with age, disease, or environment.
The document discusses different types of biometrics used to identify individuals, including fingerprints, handprints, iris scans, and signatures. It describes how biometrics systems work by automatically identifying people based on biological or behavioral characteristics. Some advantages of biometrics are that they cannot be lost, stolen, or forgotten like passwords. However, biometrics also have limitations like environmental factors affecting accuracy. The document also examines design considerations for biometrics systems and provides examples of current and potential future applications.
Fingerprint Authentication Using Biometric And Aadhar Card FingerprintSonuSawant
The document provides information about fingerprint authentication. It discusses how fingerprint authentication works by verifying a match between a captured fingerprint and one stored in a database. The fingerprint authentication process involves fingerprint capture, pre-processing, feature extraction, and matching. It notes that fingerprint authentication is widely used for security access control and online transactions due to fingerprints being unique and unchanging throughout a person's lifetime.
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International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
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
This is a complete report on Bio-metrics, finger print detection. It include what finger print is, how to scan and refin finger print, how the mechanism of its detection work, applications, etc
Biometrics uses physiological or behavioral characteristics to identify individuals. There are two main types: physiological (e.g. fingerprints, facial recognition) and behavioral (e.g. signature, voice). Biometric systems can operate in verification or identification mode. Verification compares a captured biometric to one on file to verify an individual's identity. Identification performs one-to-many comparisons to determine who an individual is. Common biometric technologies analyzed in the document include fingerprints, facial recognition, hand geometry, retinal scans, voice recognition, and signature analysis. Each method has advantages and disadvantages for security, accuracy, and usability. Biometrics is an evolving field that aims to increase identity security and convenience through technologies like iris scanning
This document summarizes a research paper on implementing a fingerprint-based biometric authentication system for ATMs using a PIC microcontroller. It describes how fingerprint identification works by analyzing ridge and valley patterns. The system uses a PIC16F877A microcontroller to collect fingerprint data from a fingerprint sensor module and match it to an enrolled fingerprint template to authenticate users. If a match is found, the ATM cashbox opens, and if not, an alarm sounds. The document discusses the methodology, advantages, limitations and components of the system, including the fingerprint sensor, microcontroller, LCD display, motor driver, and buzzer.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
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Build applications with generative AI on Google CloudMárton Kodok
We will explore Vertex AI - Model Garden powered experiences, we are going to learn more about the integration of these generative AI APIs. We are going to see in action what the Gemini family of generative models are for developers to build and deploy AI-driven applications. Vertex AI includes a suite of foundation models, these are referred to as the PaLM and Gemini family of generative ai models, and they come in different versions. We are going to cover how to use via API to: - execute prompts in text and chat - cover multimodal use cases with image prompts. - finetune and distill to improve knowledge domains - run function calls with foundation models to optimize them for specific tasks. At the end of the session, developers will understand how to innovate with generative AI and develop apps using the generative ai industry trends.
1. 1
Contents
Abstract ........................................................................................................................................... 2
Access Control................................................................................................................................ 3
Common Practices for Access Control Methods ........................................................................ 3
Common Control Types for Access Control............................................................................... 3
Biometric Authentication................................................................................................................ 5
Biometric Behavior Associations and Behavior Measures ......................................................... 6
Biometric Controls & Psychological Analysis............................................................................ 6
Physiological Biometric Controls ................................................................................................... 7
i. Fingerprint Recognition....................................................................................................... 7
ii. Retinal Scan ......................................................................................................................... 7
iii. Iris Scan............................................................................................................................ 7
Keystroke & Control Dynamics Analysis................................................................................... 7
Risks of Biometric authentication................................................................................................... 8
Use of Tokens ................................................................................................................................. 9
One-Time Password (OTP) ..................................................................................................... 9
Importance................................................................................................................................... 9
Drawbacks of OTPs .................................................................................................................... 9
Time-Based One Time Password (TOTP)............................................................................. 10
OTP/TOTP Token Considerations............................................................................................ 10
Multi-Factor Authentication ......................................................................................................... 11
Importance................................................................................................................................. 11
MFA Authentication Considerations ........................................................................................ 12
Single Sign-On.............................................................................................................................. 13
Considerations for SSO............................................................................................................. 13
Potential Risks........................................................................................................................... 14
Public Key Infrastructure.............................................................................................................. 15
Risks of PKI .............................................................................................................................. 15
Strategic Planning ......................................................................................................................... 16
References..................................................................................................................................... 18
2. 2
Abstract
The digital age has seen a growing use of passwords everywhere, from social media
websites to accounts on personal computers, passwords are everywhere to protect our documents
and financial institutions. All this makes the growth and adaptation of security controls vital in
an organization’s ability to grow and adapt and to be effective. Organizations should adopt
suitable controls based on their needs and strategies as each control greatly impacts the
organization’s strategies, safety and security.
3. 3
Access Control
Access control includes identification, authentication, authorization, and accountability
(Kung et al., 2017) and is defined as the process that either denies or grants resources and
services to a user in a network.
Common Practices for Access Control Methods
Some of the best practices for access control over the years include the following:
Should be based on determined roles as well as responsibilities
The principle of least privilege should be followed
They should be reviewed at various intervals and audits should occur
Logging of information
Common Control Types for Access Control
These methods can broadly be divided into the three following categories:
Technical Controls:
These include the use of biometrics, access control cards, usernames and passwords,
protocols for remote access authentication, access control lists(ACL), account restrictions,
encryptions, policy enforcements etc. (Dimov & Tistarelli, 2015)
Administrative Controls:
These include security awareness trainings, procedures, supervisory structures, personnel
control and testing.
Physical Controls:
5. 5
Biometric Authentication
This method verifies users by identifying and measuring an individual’s unique
behavioral and physiological features (Dimov et al., 2015). Biometric authentication provides
stronger access control than pins and passwords as it cannot be forgotten, lost or shared.
Biometric measures maximize between-individual random variances while simultaneously
minimizing within-individual variability.
The different types of biometric authentication include:
Face recognition
Fingerprint scanning
Iris/retinal scanning
Hand geometry
Vein infrared thermogram
Palm print and gait
Another authentication method is voice identification which is to be measured in an
ambient setting. Obstacles like auditory eavesdropping and/or manipulation has resulted in it not
being used for specific multi factor systems (Kung et al., 2017). But it has been of great use in
tending to the needs of the disabled. For example, visually impaired people have problems with
authentication processes like Captcha (Dimov et al., 2015) thus being unable to visualize and
input character sequences. Voice authentication can be used here to interact in an auditory
fashion. Good biometric systems have low false rejection and false acceptance. Failure to
comply with this results in bad user experience. Achieving 100% accuracy has been the biggest
barrier in the commercialization of this technology. (Kung et al., 2017).
6. 6
Biometric Behavior Associations and Behavior Measures
Biometric techniques have proved to be more complex and costly as compared to other
methods. They require uniqueness of eyes and fingers for validation. The accepted standards for
biometric authentication include a speed of not more than five seconds, an enrolment time of not
more than 2 minutes, and a throughput of 6 to 10 per min (Dimov et al., 2015).
Biometric Controls & Psychological Analysis
False Reject Rate (FRR) – Authorized individuals are erroneously denied access meaning there
is a possibility of the system denying access to an individual who has been matched to the
template.
False Accept Rate – Unauthorized individuals, without a match template are erroneously allowed
access.
Cross Error Rate – It allows users to compare cross systems and remains the most accurate
biometric system (Dimov et al., 2015).
7. 7
Physiological Biometric Controls
i. Fingerprint Recognition
This cheap, non-intrusive method is used to develop images of ridges, whorls and fingerprint
minutia. It can be both static and dynamic. (Kung et al., 2017). But it has the disadvantage of the
sensor wearing off, it is affected by swellings and injuries and is prone to deception. (Dimov et
al., 2015).
ii. Retinal Scan
This includes recording unique components in the blood vessels of the retina and identifying
patterns on the rear eyeball. But is has the disadvantages of damaging the eye ball due to the
laser and the retina patterns may change as a result of heart diseases or diabetes. The subject
must remain still and the scanning unit must be directly before the eyes. It has the advantage of
great accuracy.
iii. Iris Scan
Considered the most accurate among all biometric authentication as iris patterns remain
constant throughout adulthood and vary between two eyes on an individual (Kung et al., 2017).
Keystroke & Control Dynamics Analysis
This involves analyzing and recognizing an individual’s unique typing rhythm. It uses
flight time and dwell time.
Signature Dynamic systems:
These use user signatures for reference and recognition. They capture the way the pen is
held and the amount of pressure exerted and signing speed. They have the advantage of being
non-intrusive but speed wear and changing speed can be a barrier.
8. 8
Risks of Biometric authentication
Facial recognition accuracy can vary depending on camera sensitivity, lighting and angle.
Accessories like glasses or sunglasses can make the person look different. Temperature or any
problem with the finger can affect finger print scans. Apple’s impressive touch ID can been
bypassed by the use of latex and accurate sensors (Dimov et al., 2015).
Other systems use information like location. Problems with keystroke dynamics is that it may
take people different time in case of a keyboard with a different interface, also right-handed
people type slower with their left hands and vice versa. The index finger types faster due to its
consistent use and instinctive ability. (Dimov et al., 2015).
9. 9
Use of Tokens
One-Time Password (OTP)
This technology provides maximum security. Users are provided with a list of passwords
and use every password in a sequence. Hackers could sniff the passwords from the network, but
that technique is generally ineffective. Users authenticate themselves with a pin or token (Alfred,
2016). The users do not have to memorize or choose passwords, the token generates a onetime
unique password for each process allowing access to protected resources (Roebuck, 2017).
Importance
They have been designed to replace session IDs, reducing server load, rationalizing
permission management, and offering appropriate tools for supporting a cloud-based or
distributed infrastructure. Tokens are generated when the user authenticates themselves
(Roebuck, 2017). This process has the advantage of statelessness, the token generated by the
server need not be stored anywhere. All user meta data is encoded directly in the token thus any
user can be authenticated by nay machine and no sessions are required. This also has the
advantage of scalability (Alfred, 2016). Using tokens for mobile application authentication
allows users to easily control what APIs can access their devices. They are easier than cookies
when deployed on Android or iOS and require no extra effort from the development team.
Drawbacks of OTPs
SMS OTPs involve sending the OTP to a phone number configured to the website. This
has the disadvantage of trust, users will have to deal with the malware through the SMS as
encryption on cellular networks is weak (Alfred, 2016). OTP can be inconvenient as the user has
to copy the OTP from the device that received it to the login form (Roebuck, 2017). The copied
10. 10
OTP has to be short printable hindering flexibility and resulting in diminished security (Alfred,
2016).
Time-Based One Time Password (TOTP)
This method consistently generates new passwords in a given time interval. The tokens
and the server use this time to produce authentication numbers which are used by the user during
login. Similar algorithms are used at the user and server side. The server and tokens generate
OTP for a fixed time.
OTP/TOTP Token Considerations
The following should be considered when implementing OTP tokens:
Token are required for every user thus require more investment.
Users need to carry the token with them at all times as they won’t be allowed
to access the system otherwise.
Users cannot use the system for a long time without the token.
Connections can be vulnerable to sniffing as once the original connection is
authenticated all connectors are assumed to be authenticated (Alfred, 2016).
Users need to ensure the safety of their tokens.
Security tokens may not be compatible with all severs or applications.
11. 11
Multi-Factor Authentication
MFA also known as two step authentication is an authentication username, password, and
additional authentication such as personal information or a physical token. It guarantees that the
users are who they are (Stanislav, 2015). It requires that users identify themselves by presenting
a minimum of 2-pieces of evidence through three major categories. If one factor is affected by a
hacker it’s impact on other steps is minimal thus providing greater security (Sampson, 2015).
Users’ choice of weak passwords make it easier for hackers (Dasgupta, Roy & Nag, 2017). MFA
provides layers of protection to the user by preventing a ripple effect (Sampson, 2015). Some
recognized MFA methods include pop-up notification or verification via text from mobile phone,
inserting a card, and typing in unique codes created by a physical token (Stanislav, 2015). Some
companies employ a MFA for every user this along with SSO makes it very secure and
completely eliminates the need for passwords (Sampson, 2015).
Importance
MFA offers good end user experience and robust security. For example, an organization
might need higher level of reassurance while accessing a human resource applications, banks
permit clients to log into their account with their password and username, but a second
authentication is required prior to any transactions, retailers can use MFA in case a vendor logs
into its portal from a new system to ensure it is not a hacker attempting to gain access with a
password that has been stolen (Stanislav, 2015). This type of MFA is referred to as contextual,
risk-based, or adaptive MFA. It has the advantage of increasing the system’s security when
needed (Dasgupta et al., 2017). Thus balancing convenience and security. Due to the magnitude
of loss in case of violation MFA requires additional proof. If contextual MFA is used security
maybe achieved without giving up usability (Sampson, 2015).
12. 12
MFA Authentication Considerations
Users are locked out of their accounts in case of a single mistake.
Though used to keep hackers away, hackers can create their own two step authentication
to keep users locked out.
13. 13
Single Sign-On
Users can identify themselves to servers only once through this method (Miller, 2015).
Users can login multiple times with a single password but compromise in a single authentication
can compromise all available resources.
Considerations for SSO
The following should be considered when implementing SSO.
Since one authentication regulates access to resources this process should be secure.
Smart cards and tokens maybe used to strengthen the authentication process.
Password policies need to be enforced implementing minimum password length,
complexity of password, minimum time for renewal, and maximum frequency of
attempts.
Encryption to protect against sniffing should be used. Logins should be used to detect
suspicious login attempts.
Authentication servers must be used.
SSO protocols often share session information, but a central domain exists, by which
authentication is executed, and sessions are shared with some domains in certain manners
(Dasgupta et al., 2017). For instance, a central domain can generate a signed JSON Web Token
that is encrypted with JWE. This token can be passed to the customer and applied by the
authentication domain. The token may be redirected and consists of all the data necessary to
authenticate the user. Since the tokens are signed, the client cannot modify it (Miller, 2015).
Users are redirected to the authentication domain every time authentication is required. Since the
14. 14
users have already logged in, they can instantly redirect to the original domain through the
authentication token.
Potential Risks
Authentication and privacy keys are a security concern.
If the SSO server is unavailable the users cannot access any site.
SSO is not suitable for multi-user computers if they remain logged at all times.
They lack back up and better authentication.
If the password is weak it is easy to identify and hack accounts, once hacked all accounts
will be compromised.
15. 15
Public Key Infrastructure
PKI is defined as a technology that uses mathematical processes and algorithms to
facilitate secure transactions using data integrity, data confidentiality, and authentication by Kim
(2016). PKI uses certificates, developed by a trusted certificate authority to prove an individual’s
identity. The user is authenticated by the certificate authority’s private key. This certificate can
be used for authentication to access many applications that check the identity through the digital
signature from the CA. (Schmeh, 2016). PKI is valuable to applications that require no pre-
registration like online transactions. Users only require a certificate from the certificate authority
(Kim, 2016).
Risks of PKI
There is no governing body to enforce the standards of PKI (Schmeh, 2016). CAs are
trusted third parties but limitations in security procedures over the years has resulted in less trust
in PKI as any compromise in CA can expose the entire PKI security to risks (Kim, 2016).
16. 16
Strategic Planning
Strategic operations define an organization’s strategy or direction and the decisions it
takes and the resources it allocates to pursue that strategy. Organizations need to keep in mind
the following:
What the organization is currently doing
Who they are doing it for
How will they excel going forward
Strategic decisions keep in view the next three to five years and consider any potential
mishaps. These mishaps may also include untapped opportunities. These decisions are affected
by factors that may be out of the organization’s control, e.g. wars, geopolitical shocks etc.
Organizations’ strategies should also address how they intend to sustain their operations and
provide quality products or services to their customers while including capabilities for future
innovations.
Strategic planning involves the following steps:
Clarifying mission and vision statements
This involves identifying and clarifying the company’s mission, vision, corporate
values, culture and most importantly why the company exits and what success looks like
to the company.
Identifying current and future market position
17. 17
This involves gathering data on internal strengths, weaknesses, external threat and
external opportunities so the organization can develop an understanding of all the critical
issues and deal with them accordingly.
Prioritizing
Creating priorities that need to be addressed and form strategies in dealing with
those issues.
It is the culmination of proper security controls, the understanding of the need for an
organization’s assets to remain secure, and various strategic decisions that allow for an
organization to properly plan for their long-term success. It is part of the constant struggle to
create balance between security, accessibility, and strategic vision. Each of these acts as the
driving force to enable the next, sparking creativity and hopefully, long-term success.
18. 18
References
Alfred, A. (2016). Node.js: Token-Based Authentication Part 3. Defining Routes and
Implementing Token-Based Authentication.
Dasgupta, D., Roy, A., & Nag, A. (January 01, 2017). Multi-Factor Authentication: More secure
approach towards authenticating individuals.
Dimov, D., & In Tistarelli, M. (2015). Biometric Authentication. Cham (Alemania: Springer.
Kim, D. (2016). Access control, authentication, and public key infrastructure: Laboratory
manual to accompany.
Kung, S. Y., Mak, M.-W., & Lin, S.-H. (2017). Biometric authentication: A machine learning
approach. Upper Saddle River: Prentice Hall.
Miller, W. (2015). Foundations of iOS Security: Working with Single Sign-on Authentication.
Roebuck, K. (2017). Security Tokens: High-impact Strategies - What You Need to Know:
Definitions, Adoptions, Impact, Benefits, Maturity, Vendors. Dayboro: Emereo Pub.
Schmeh, K. (2016). Cryptography and Public Key Infrastructure on the Internet. New York,
NY: John Wiley & Sons.
Sampson, A. (2015). Architecting Microsoft Azure Solutions: Multi-factor Authentication
Overview.
Stanislav, M. (2015). Two-factor authentication. Ely, Cambridgeshire, United Kingdom: It
Governance Publishing.