M.Selvi, T.Manickam, C.N.Marimuthu"Gaussian Filter based Biometric System Security Enhancement", International Research Journal of Engineering and Technology (IRJET), Volume2,issue-01 April 2015.e-ISSN:2395-0056, p-ISSN:2395-0072. www.irjet.net
Abstract
A novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. To enhance the security of biometric recognition frameworks, by adding liveness assessment in a fast, user-friendly, and non-intrusive manner, through the use of image quality assessment.
The proposed approach presents a very low degree of complexity, which makes it suitable for real-time applications, using 25 general image quality features extracted from one image (i.e., the same acquired for authentication purposes) to distinguish between legitimate and impostor samples. Multi-biometric and Multi-attack protection method which targets to overcome part of these limitations through the use of Image Quality Assessment (IQA).
Moreover, being software-based, it presents the usual advantages of this type of approaches: fast, as it only needs one image (i.e., the same sample acquired for biometric recognition) to detect whether it is real or fake, non-intrusive; user-friendly (transparent to the user), cheap and easy to embed in already functional systems and no hardware is required).
The increasing use of distributed authentication architecture
has made interoperability of systems an important issue. Interoperabil ity of systems affects the maturity of the technology and also improves confidence of users in the technology. Biometric systems are not immune to the concerns of interoperability. Interoperability of fingerprint sensors and its effect on the overall performance of the recognition system is an area of interest with a considerable amount of work directed
towards it. This research analyzed effects of interoperability on error rates for fingerprint datasets captured from two optical sensors and a capacitive sensor when using a single commercially available fingerprint
matching algorithm. The main aim of this research was to emulate a
centralized storage and matching architecture with multiple acquisition
stations. Fingerprints were collected from 44 individuals on all three sensors and interoperable False Reject Rates of less than .31% were achieved using two different enrolment strategies.
Seminar report on Error Handling methods used in bio-cryptographykanchannawkar
Detail information about the real time errors in the biometrics devices and also how to secure encryption keys. To make authentication systems more secure. In this seminar report describe about the combination of the biometrics with the cryptography. and also describe the methods that are used to handle the real time error like fault accept and fault reject and also describe their their rates.i,e FRR and FAR by the biometrics systems.
IMAGE QUALITY ASSESSMENT FOR FAKE BIOMETRIC DETECTION: APPLICATION TO IRIS, F...ijiert bestjournal
In this Paper,the actual presence of a real legitimate trait in contrast to a fake self - manufactured synthetic or reconstructed sample is a significant problem in biometric authentication,which requires the development of new and efficient protection measures. In this paper,we present a novel software - based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. The obje ctive of the proposed system is to enhance the security of biometric recognition frameworks,by adding livens assessment in a fast,user - friendly,and non - intrusive manner,through the use of image quality assessment. The proposed approach presents a very low degree of complexity,which makes it suitable for real - time applications,using 25 general image quality features extracted from one image (i.e.,the same acquired for authentication purposes) to distinguish between legitimate and impostor samples. The experimental results,obtained on publicly available data sets of fingerprint,iris,and 2D face,show that the proposed method is highly competitive compared with other state - of - the - art approaches and that the analysis of the general image quality of rea l biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake traits.
7 multi biometric fake detection system using image quality based liveness de...INFOGAIN PUBLICATION
Biometric systems mostly popular in all over the world because of its user friendly and credible nature in security. In spite of this advantages, many attacks that done through synthetic , self manufactured, fake, reconstructed samples affected on the performance and accuracy of biometric system which becomes major problem in biometrics. Hence, new effective measures have to be taken to protect the biometric systems. In this paper, we propose novel software based multi-biometric fake detection system to detect various types of attacks. The main moto of this system is to enhance security level of biometric recognition systems through Image Quality Assessment (IQA) which is one of the liveness detection method.25 image quality measures calculated from test image which used to classify between real and fake trait using Linear Discriminative Analysis(LDA) classifier. The experimental results is done on the database of 2D face and fingerprint modalities, shows the proposed system is ease in implementation in real time application as complexities is very less because of one input image. Also this system is fast, user-friendly, non-intrusive which is more competitive with any other state of the art approaches, classifies between real and fake traits.
Abstract—Biometric systems are increasingly deployed in networked environment, and issues related to interoperability are bound to arise as single vendor, monolithic architectures become less desirable. Interoperability issues affect every subsystem of the biometric system, and a statistical framework to evaluate interoperability is proposed. The framework was applied to the acquisition subsystem for a fingerprint recognition system and the results were evaluated using the framework. Fingerprints were collected from 100 subjects on 6 fingerprint sensors. The results show that performance of interoperable fingerprint datasets is not easily predictable and the proposed framework can aid in removing unpredictability to some degree.
An SVM based Statistical Image Quality Assessment for Fake Biometric DetectionIJTET Journal
Abstract
A biometric system is a computer based system and is used to identify the person on their behavioral and logical characteristics such as (for example fingerprint, face, iris, keystroke, signature, voice, etc.).A typical biometric system consists of feature extraction and matching patterns. But nowadays biometric systems are attacked by using fake biometric samples. This paper described the fingerprint biometric techniques and also introduce the attack on that system and by using Image Quality Assessment for Liveness Detection to know how to protect the system from fake biometrics and also how the multi biometric system is more secure than uni-biometric system. Support Vector Machine (SVM) classification technique is used for training and testing the fingerprint images. The testing onput fingerprint image is resulted as real and fake fingerprint image by quality score matching with the training based real and fake fingerprint samples.
The vulnerabilities of biometric sensors have been
discussed extensively in the literature and popularized in films and
television shows. This research examines the image quality of an
artificial print as compared to a genuine finger, and examines the
characteristics of the two, including minutiae counts and image
quality, as repeated samples are taken.
The proliferation of networked authentication
systems has put focus on the issue of interoperability.
Fingerprint sensors are based on a variety of different technologies that introduce inconsistent distortions and variations in the feature set of the captured image, which makes the goal of interoperability challenging. The motivation of this
research was to examine the effect of fingerprint sensor interoperability on the performance of a minutiae based matcher. A statistical analysis framework for testing
interoperability was formulated to test similarity of minutiae count, image quality and similarity of performance between
native and interoperable datasets. False non-match rate (FNMR) was used as the performance metric in this research.
Interoperability performance analysis was conducted on each sensor dataset and also by grouping datasets based on the
acquisition technology and interaction type of the acquisition sensor. The lowest interoperable FNMR observed was 0.12%.
The increasing use of distributed authentication architecture
has made interoperability of systems an important issue. Interoperabil ity of systems affects the maturity of the technology and also improves confidence of users in the technology. Biometric systems are not immune to the concerns of interoperability. Interoperability of fingerprint sensors and its effect on the overall performance of the recognition system is an area of interest with a considerable amount of work directed
towards it. This research analyzed effects of interoperability on error rates for fingerprint datasets captured from two optical sensors and a capacitive sensor when using a single commercially available fingerprint
matching algorithm. The main aim of this research was to emulate a
centralized storage and matching architecture with multiple acquisition
stations. Fingerprints were collected from 44 individuals on all three sensors and interoperable False Reject Rates of less than .31% were achieved using two different enrolment strategies.
Seminar report on Error Handling methods used in bio-cryptographykanchannawkar
Detail information about the real time errors in the biometrics devices and also how to secure encryption keys. To make authentication systems more secure. In this seminar report describe about the combination of the biometrics with the cryptography. and also describe the methods that are used to handle the real time error like fault accept and fault reject and also describe their their rates.i,e FRR and FAR by the biometrics systems.
IMAGE QUALITY ASSESSMENT FOR FAKE BIOMETRIC DETECTION: APPLICATION TO IRIS, F...ijiert bestjournal
In this Paper,the actual presence of a real legitimate trait in contrast to a fake self - manufactured synthetic or reconstructed sample is a significant problem in biometric authentication,which requires the development of new and efficient protection measures. In this paper,we present a novel software - based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. The obje ctive of the proposed system is to enhance the security of biometric recognition frameworks,by adding livens assessment in a fast,user - friendly,and non - intrusive manner,through the use of image quality assessment. The proposed approach presents a very low degree of complexity,which makes it suitable for real - time applications,using 25 general image quality features extracted from one image (i.e.,the same acquired for authentication purposes) to distinguish between legitimate and impostor samples. The experimental results,obtained on publicly available data sets of fingerprint,iris,and 2D face,show that the proposed method is highly competitive compared with other state - of - the - art approaches and that the analysis of the general image quality of rea l biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake traits.
7 multi biometric fake detection system using image quality based liveness de...INFOGAIN PUBLICATION
Biometric systems mostly popular in all over the world because of its user friendly and credible nature in security. In spite of this advantages, many attacks that done through synthetic , self manufactured, fake, reconstructed samples affected on the performance and accuracy of biometric system which becomes major problem in biometrics. Hence, new effective measures have to be taken to protect the biometric systems. In this paper, we propose novel software based multi-biometric fake detection system to detect various types of attacks. The main moto of this system is to enhance security level of biometric recognition systems through Image Quality Assessment (IQA) which is one of the liveness detection method.25 image quality measures calculated from test image which used to classify between real and fake trait using Linear Discriminative Analysis(LDA) classifier. The experimental results is done on the database of 2D face and fingerprint modalities, shows the proposed system is ease in implementation in real time application as complexities is very less because of one input image. Also this system is fast, user-friendly, non-intrusive which is more competitive with any other state of the art approaches, classifies between real and fake traits.
Abstract—Biometric systems are increasingly deployed in networked environment, and issues related to interoperability are bound to arise as single vendor, monolithic architectures become less desirable. Interoperability issues affect every subsystem of the biometric system, and a statistical framework to evaluate interoperability is proposed. The framework was applied to the acquisition subsystem for a fingerprint recognition system and the results were evaluated using the framework. Fingerprints were collected from 100 subjects on 6 fingerprint sensors. The results show that performance of interoperable fingerprint datasets is not easily predictable and the proposed framework can aid in removing unpredictability to some degree.
An SVM based Statistical Image Quality Assessment for Fake Biometric DetectionIJTET Journal
Abstract
A biometric system is a computer based system and is used to identify the person on their behavioral and logical characteristics such as (for example fingerprint, face, iris, keystroke, signature, voice, etc.).A typical biometric system consists of feature extraction and matching patterns. But nowadays biometric systems are attacked by using fake biometric samples. This paper described the fingerprint biometric techniques and also introduce the attack on that system and by using Image Quality Assessment for Liveness Detection to know how to protect the system from fake biometrics and also how the multi biometric system is more secure than uni-biometric system. Support Vector Machine (SVM) classification technique is used for training and testing the fingerprint images. The testing onput fingerprint image is resulted as real and fake fingerprint image by quality score matching with the training based real and fake fingerprint samples.
The vulnerabilities of biometric sensors have been
discussed extensively in the literature and popularized in films and
television shows. This research examines the image quality of an
artificial print as compared to a genuine finger, and examines the
characteristics of the two, including minutiae counts and image
quality, as repeated samples are taken.
The proliferation of networked authentication
systems has put focus on the issue of interoperability.
Fingerprint sensors are based on a variety of different technologies that introduce inconsistent distortions and variations in the feature set of the captured image, which makes the goal of interoperability challenging. The motivation of this
research was to examine the effect of fingerprint sensor interoperability on the performance of a minutiae based matcher. A statistical analysis framework for testing
interoperability was formulated to test similarity of minutiae count, image quality and similarity of performance between
native and interoperable datasets. False non-match rate (FNMR) was used as the performance metric in this research.
Interoperability performance analysis was conducted on each sensor dataset and also by grouping datasets based on the
acquisition technology and interaction type of the acquisition sensor. The lowest interoperable FNMR observed was 0.12%.
An Investigation towards Effectiveness of Present State of Biometric-Based Au...RSIS International
The adoption of biometric-based authentication mechanism has been already initiated a decade back but still in real-life we get to see usage of only unimodal biometrics. Out of all the different forms of biometrics, we see usage of fingerprint as the dominant attribute in contrast to different other attributes e.g. teeth image, palm, facial geometry, retina network, iris, etc. Multimodal biometrics is believed to offered better security compared to unimodal. Although, there are some of the technical advancement in evolving up with new multimodal methodologies, but still commercial usage of such is yet to be seen. Therefore, this manuscripts aims to explore the level of effectiveness in existing approaches of biometric-based authentication system in order to further investigate the unaddressed solution towards this problem. This paper reviews the approaches used for addressing different problems associated with biometrics and discusses about their technical methodologies as well as their limitations.
Problems from the inside of an organization’s perimeters are a significant threat, since it is very difficult to
differentiate them from outside activity. In this dissertation, evaluate an insider threat detection motto on
its ability to detect different type of scenarios that have not previously been identify or contemplated by the
developers of the system. We show the ability to detect a large variety of insider threat scenario instances
We report results of an ensemble-based, unsupervised technique for detecting potential insider threat,
insider threat scenarios that robustly achieves results. We explore factors that contribute to the success of
the ensemble method, such as the number and variety of unsupervised detectors and the use of existing
knowledge encoded in scenario based detectors made for different known activity patterns. We report
results over the entire period of the ensemble approach and of ablation experiments that remove the
scenario-based detectors.
FEATURE EXTRACTION METHODS FOR IRIS RECOGNITION SYSTEM: A SURVEYijcsit
Protection has become one of the biggest fields of study for several years, however the demand for this is growing exponentially mostly with rise in sensitive data. The quality of the research can differ slightly from any workstation to cloud, and though protection must be incredibly important all over. Throughout the past two decades, sufficient focus has been given to substantiation along with validation in the technology model. Identifying a legal person is increasingly become the difficult activity with the progression of time. Some attempts are introduced in that same respect, in particular by utilizing human movements such as fingerprints, facial recognition, palm scanning, retinal identification, DNA checking, breathing, speech checker, and so on. A number of methods for effective iris detection have indeed been suggested and researched. A general overview of current and state-of-the-art approaches to iris recognition is presented in this paper. In addition, significant advances in techniques, algorithms, qualified classifiers, datasets and methodologies for the extraction of features are also discussed.
This study investigated the effect of force levels (3, 5, 7, 9 and 11N) on fingerprint
matching performance, image quality scores and minutiae count between optical and capacitance sensors. Three images were collected from the right index fingers of 75 participants for each sensing technology. Descriptive statistics analysis of variance and Kruskal-Wallis non-parametric
tests were conducted to assess significant differences in minutiae counts and image quality scores, by force level. The results reveal a significant difference in image quality score by force level and sensor technology in contrast to minutiae count for the capacitance sensor. The image quality score is one of the many factors that influence the system matching performance, yet the
removal of low quality images does not improve the system performance at each force level. Further research is needed to identify other manipulatable factors to improve the interaction between a user and device and the subsequent matching performance.
A Review of Machine Learning based Anomaly Detection TechniquesEditor IJCATR
Intrusion detection is so much popular since the last two decades where intrusion is attempted to break into or misuse
the system. It is mainly of two types based on the intrusions, first is Misuse or signature based detection and the other is Anomaly
detection. In this paper Machine learning based methods which are one of the types of Anomaly detection techniques is
discussed.
The use of fingerprints in a voting system for registration and authentication
application has its limitations. Among these limitations are mismatches caused by
disparity in fingerprint trait and templates of voters taken at the point of registration
and at the point of authentication (voter’s accreditation). Manual labour, aging,
variations in user interaction (i.e. pressure on the scanner), environmental changes
and injuries are a few of the factors that can cause these disparities. The iris is more
resistant to these factors that cause disparity in biometrics. In this designed model, the
iris was used in place of fingerprints as the biometric measure to register and
authenticate voters. An iris scanner obtains the voter’s iris image, segments and
digitizes it. The digitized iris image of the voter is used as a training data and stored
in the template. This template is stored together with the voter’s particulars in a
database. An algorithm design using the C# (C sharp) language issues a PIN for the
voter’s authentication. At the point of authentication, the PIN of the voter is keyed in.
The iris scanner obtains the voter’s iris image, generates a template of the iris and
with the aid of the system’s embedded algorithm, compares the details of the voter’s
pin and iris trait with the one in the database for a match. A match grants the voter
the pass to vote. A mismatch denies the voter access to the voting system. This
implemented Iris Recognition Technology drastically reduces the chances of
mismatches for genuine voters and denies imposters in the voting system due to its
reliability and robustness as revealed by the tests carried out on the designed model.
A Smart Receptionist Implementing Facial Recognition and Voice InteractionCSCJournals
The purpose of this research is to implement a smart receptionist system with facial recognition and voice interaction using deep learning. The facial recognition component is implemented using real time image processing techniques, and it can be used to learn new faces as well as detect and recognize existing faces. The first time a customer uses this system, it will take the person’s facial data to create a unique user facial model, and this model will be triggered if the person comes the second time. The recognition is done in real time and after which voice interaction will be applied. Voice interaction is used to provide a life-like human communication and improve user experience. Our proposed smart receptionist system could be integrated into the self check-in kiosks deployed in hospitals or smart buildings to streamline the user recognition process and provide customized user interactions. This system could also be used in smart home environment where smart cameras have been deployed and voice assistants are in place.
APPLICATION OF SELF-ORGANIZING FEATURE MAPS AND MARKOV CHAINS TO RECOGNITION ...IAEME Publication
The number of studies in the field of behavior analysis is currently experiencing a
significant upsurge. This study presents two cancarantly approaches to identifying
anomalous activity within users’ behavior in cloud infrastructures, each of which
allows researchers to learn from the empirical data collected. The main purpose of
these approaches is the ongoing scoring of users’ actions in cloud infrastructures to
reveal anomalies in their activity. The first approach is based on the technique of
statistical hypothesis testing and uses Kohonen self-organizing maps to generate the
target statistics. The second approach is based on revealing strange activity in the
dynamics of user’s behavior and uses Markov chains to describe their typical actions
A Bring Your Own Device Risk Assessment ModelCSCJournals
Bring Your Own Device (BYOD), a technology where individuals or employees use their own devices on the organization’s network to perform tasks assigned to them by the organization has been widely embraced. The reasons for adoption are diverse in every organization. In spite of the security control strategies implemented by these organizations to safeguard their information resources, there has been an upsurge in information security breaches as a result of existing vulnerabilities in these systems and the legacy systems in use. Various approaches have been employed to deal with security challenges in BYOD, but according to literature, risk assessment has proved to be the first key step towards improving security of the BYOD environment in an enterprise. Risk assessment models have been proposed by various researchers, although, most are largely influenced by the degree of technological advancement and utilization as well as the working cultures within institutions. The existing models were largely developed in technologically advanced countries and thus do not fit well in developing countries. This study sought to develop flexible BYOD risk assessment model that can be adopted by varied institutions to secure their information resources. The study was carried out in Five (5) purposively selected state universities in Kenya. The research adopted a mixed research design approach with mixed sampling technique utilized to select the participants. Reliability and validity of data collection tools were evaluated and recommended by IT security and network experts. The qualitative and quantitative data was collected by interviewing experts and administering a questionnaire to sampled participants. The developed model was validated both statistically and by experts. The findings revealed that threats and vulnerabilities contributed to 39.9% and 69.2% respectively to the risk of the BYOD environment while Data Encryption (DE) and Software Updates (SU) came out strongly as intervening variables which have a major impact on the relationship between the dependent and independent variables.
Improving the accuracy of fingerprinting system using multibiometric approachIJERA Editor
Biometric technology is a science that used to verify or identify the individual based on physical and/or
behavioral traits. Although biometric systems are considered more secure than other traditional methods such as
password, or key, they also have many limitations such as noisy image, or spoof attack. One of the solutions to
overcome these limitations, is by applying a multibiometric system. Multibiometric system has a significant
effect in improving the performance of both security and accuracy of the system. It also can alleviate the spoof
attacks and reduce the fail to enroll error. A multi-sample is one implementations of the multibiometric systems.
In this study, a new algorithm is suggested to provide a second chance for the genuine user who is rejected, to
compare his/her provided finger with the other samples of the same finger. Multisampling fingerprint is used to
implement this new algorithm. The algorithm is activated when the match score of the user is not equal to a
threshold but close to it, then the system provides another chance to compare the finger with another sample of
the same trait. Using multi-sample biometric system improved the performance of the system by reducing the
False Reject Rate (FRR). Applying the original matching algorithm on the presented database produced 3
genuine users, and 5 imposters for the same fingerprint. While after implementing the suggested condition, the
system performance is enhanced by producing 6 genuine users, and 2 imposters for the same fingerprint. This
work was built and executed depending on a previous Matlab code presented by Zhi Li Wu. Thresholds and
Receiver Operating Characteristic (ROC) curves computed before and after implementing the suggested
multibiometric algorithm. Both ROC curves compared. A final decision and recommendations are provided
depending on the results obtained from this project
As we know the fingerprint is unique of every living objects. It is quite difficult to find out the prints.
Usually the Forensics use Fine powder and duct tapes to identify the prints of living object. As powder is
exceptionally muddled, so such molecule can cause loss of information after that examination the information is
coordinated with the system. The proposed system consists of an embedded device in which it consists of ultra
light to glow the fingerprints details. After that we can detect the fingerprint, analysis and it will checks on the
database, and it will return the output after matching. For matching and analysis of the Fingerprint, we will be
using the Algorithm for matching.
Performance Enhancement Of Multimodal Biometrics Using CryptosystemIJERA Editor
Multimodal biometrics means the unification of two or more uni modal biometrics so as to make the system more reliable and secure. Such systems promise better security. This study is a blend of iris and fingerprint recognition technique and their fusion at feature level. Our work comprises of two main sections: feature extraction of both modalities and fusing them before matching and finally application of an encryption technique to enhance the security of the fused template.
An Efficient Fingerprint Identification using Neural Network and BAT Algorithm IJECEIAES
The uniqueness, firmness, public recognition, and its minimum risk of intrusion made fingerprint is an expansively used personal authentication metrics. Fingerprint technology is a biometric technique used to distinguish persons based on their physical traits. Fingerprint based authentication schemes are becoming increasingly common and usage of these in fingerprint security schemes, made an objective to the attackers. The repute of the fingerprint image controls the sturdiness of a fingerprint authentication system. We intend for an effective method for fingerprint classification with the help of soft computing methods. The proposed classification scheme is classified into three phases. The first phase is preprocessing in which the fingerprint images are enhanced by employing median filters. After noise removal histogram equalization is achieved for augmenting the images. The second stage is the feature Extraction phase in which numerous image features such as Area, SURF, holo entropy, and SIFT features are extracted. The final phase is classification using hybrid Neural for classification of fingerprint as fake or original. The neural network is unified with BAT algorithm for optimizing the weight factor.
To ensure that the object presented in front of biometric device is real or reconstructed sample is a significant
problem in biometric authentication, which requires the development of new and efficient protection measures. This
paper, presents a software-based fake biometric detection method that can be used in multiple biometric systems to
detect different types of fraudulent access attempts. The objective of the proposed system is to enhance the security of
biometric recognition devices through the use of image quality assessment in a fast and user friendly manner. The
proposed approach presents a very low degree of complexity, which makes it suitable for real-time applications, using
25 general image quality features extracted from one image to distinguish between real and imposed samples. The
proposed method is highly competitive compared with other as the analysis of the general image quality of real
biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake
traits.
An Investigation towards Effectiveness of Present State of Biometric-Based Au...RSIS International
The adoption of biometric-based authentication mechanism has been already initiated a decade back but still in real-life we get to see usage of only unimodal biometrics. Out of all the different forms of biometrics, we see usage of fingerprint as the dominant attribute in contrast to different other attributes e.g. teeth image, palm, facial geometry, retina network, iris, etc. Multimodal biometrics is believed to offered better security compared to unimodal. Although, there are some of the technical advancement in evolving up with new multimodal methodologies, but still commercial usage of such is yet to be seen. Therefore, this manuscripts aims to explore the level of effectiveness in existing approaches of biometric-based authentication system in order to further investigate the unaddressed solution towards this problem. This paper reviews the approaches used for addressing different problems associated with biometrics and discusses about their technical methodologies as well as their limitations.
Problems from the inside of an organization’s perimeters are a significant threat, since it is very difficult to
differentiate them from outside activity. In this dissertation, evaluate an insider threat detection motto on
its ability to detect different type of scenarios that have not previously been identify or contemplated by the
developers of the system. We show the ability to detect a large variety of insider threat scenario instances
We report results of an ensemble-based, unsupervised technique for detecting potential insider threat,
insider threat scenarios that robustly achieves results. We explore factors that contribute to the success of
the ensemble method, such as the number and variety of unsupervised detectors and the use of existing
knowledge encoded in scenario based detectors made for different known activity patterns. We report
results over the entire period of the ensemble approach and of ablation experiments that remove the
scenario-based detectors.
FEATURE EXTRACTION METHODS FOR IRIS RECOGNITION SYSTEM: A SURVEYijcsit
Protection has become one of the biggest fields of study for several years, however the demand for this is growing exponentially mostly with rise in sensitive data. The quality of the research can differ slightly from any workstation to cloud, and though protection must be incredibly important all over. Throughout the past two decades, sufficient focus has been given to substantiation along with validation in the technology model. Identifying a legal person is increasingly become the difficult activity with the progression of time. Some attempts are introduced in that same respect, in particular by utilizing human movements such as fingerprints, facial recognition, palm scanning, retinal identification, DNA checking, breathing, speech checker, and so on. A number of methods for effective iris detection have indeed been suggested and researched. A general overview of current and state-of-the-art approaches to iris recognition is presented in this paper. In addition, significant advances in techniques, algorithms, qualified classifiers, datasets and methodologies for the extraction of features are also discussed.
This study investigated the effect of force levels (3, 5, 7, 9 and 11N) on fingerprint
matching performance, image quality scores and minutiae count between optical and capacitance sensors. Three images were collected from the right index fingers of 75 participants for each sensing technology. Descriptive statistics analysis of variance and Kruskal-Wallis non-parametric
tests were conducted to assess significant differences in minutiae counts and image quality scores, by force level. The results reveal a significant difference in image quality score by force level and sensor technology in contrast to minutiae count for the capacitance sensor. The image quality score is one of the many factors that influence the system matching performance, yet the
removal of low quality images does not improve the system performance at each force level. Further research is needed to identify other manipulatable factors to improve the interaction between a user and device and the subsequent matching performance.
A Review of Machine Learning based Anomaly Detection TechniquesEditor IJCATR
Intrusion detection is so much popular since the last two decades where intrusion is attempted to break into or misuse
the system. It is mainly of two types based on the intrusions, first is Misuse or signature based detection and the other is Anomaly
detection. In this paper Machine learning based methods which are one of the types of Anomaly detection techniques is
discussed.
The use of fingerprints in a voting system for registration and authentication
application has its limitations. Among these limitations are mismatches caused by
disparity in fingerprint trait and templates of voters taken at the point of registration
and at the point of authentication (voter’s accreditation). Manual labour, aging,
variations in user interaction (i.e. pressure on the scanner), environmental changes
and injuries are a few of the factors that can cause these disparities. The iris is more
resistant to these factors that cause disparity in biometrics. In this designed model, the
iris was used in place of fingerprints as the biometric measure to register and
authenticate voters. An iris scanner obtains the voter’s iris image, segments and
digitizes it. The digitized iris image of the voter is used as a training data and stored
in the template. This template is stored together with the voter’s particulars in a
database. An algorithm design using the C# (C sharp) language issues a PIN for the
voter’s authentication. At the point of authentication, the PIN of the voter is keyed in.
The iris scanner obtains the voter’s iris image, generates a template of the iris and
with the aid of the system’s embedded algorithm, compares the details of the voter’s
pin and iris trait with the one in the database for a match. A match grants the voter
the pass to vote. A mismatch denies the voter access to the voting system. This
implemented Iris Recognition Technology drastically reduces the chances of
mismatches for genuine voters and denies imposters in the voting system due to its
reliability and robustness as revealed by the tests carried out on the designed model.
A Smart Receptionist Implementing Facial Recognition and Voice InteractionCSCJournals
The purpose of this research is to implement a smart receptionist system with facial recognition and voice interaction using deep learning. The facial recognition component is implemented using real time image processing techniques, and it can be used to learn new faces as well as detect and recognize existing faces. The first time a customer uses this system, it will take the person’s facial data to create a unique user facial model, and this model will be triggered if the person comes the second time. The recognition is done in real time and after which voice interaction will be applied. Voice interaction is used to provide a life-like human communication and improve user experience. Our proposed smart receptionist system could be integrated into the self check-in kiosks deployed in hospitals or smart buildings to streamline the user recognition process and provide customized user interactions. This system could also be used in smart home environment where smart cameras have been deployed and voice assistants are in place.
APPLICATION OF SELF-ORGANIZING FEATURE MAPS AND MARKOV CHAINS TO RECOGNITION ...IAEME Publication
The number of studies in the field of behavior analysis is currently experiencing a
significant upsurge. This study presents two cancarantly approaches to identifying
anomalous activity within users’ behavior in cloud infrastructures, each of which
allows researchers to learn from the empirical data collected. The main purpose of
these approaches is the ongoing scoring of users’ actions in cloud infrastructures to
reveal anomalies in their activity. The first approach is based on the technique of
statistical hypothesis testing and uses Kohonen self-organizing maps to generate the
target statistics. The second approach is based on revealing strange activity in the
dynamics of user’s behavior and uses Markov chains to describe their typical actions
A Bring Your Own Device Risk Assessment ModelCSCJournals
Bring Your Own Device (BYOD), a technology where individuals or employees use their own devices on the organization’s network to perform tasks assigned to them by the organization has been widely embraced. The reasons for adoption are diverse in every organization. In spite of the security control strategies implemented by these organizations to safeguard their information resources, there has been an upsurge in information security breaches as a result of existing vulnerabilities in these systems and the legacy systems in use. Various approaches have been employed to deal with security challenges in BYOD, but according to literature, risk assessment has proved to be the first key step towards improving security of the BYOD environment in an enterprise. Risk assessment models have been proposed by various researchers, although, most are largely influenced by the degree of technological advancement and utilization as well as the working cultures within institutions. The existing models were largely developed in technologically advanced countries and thus do not fit well in developing countries. This study sought to develop flexible BYOD risk assessment model that can be adopted by varied institutions to secure their information resources. The study was carried out in Five (5) purposively selected state universities in Kenya. The research adopted a mixed research design approach with mixed sampling technique utilized to select the participants. Reliability and validity of data collection tools were evaluated and recommended by IT security and network experts. The qualitative and quantitative data was collected by interviewing experts and administering a questionnaire to sampled participants. The developed model was validated both statistically and by experts. The findings revealed that threats and vulnerabilities contributed to 39.9% and 69.2% respectively to the risk of the BYOD environment while Data Encryption (DE) and Software Updates (SU) came out strongly as intervening variables which have a major impact on the relationship between the dependent and independent variables.
Improving the accuracy of fingerprinting system using multibiometric approachIJERA Editor
Biometric technology is a science that used to verify or identify the individual based on physical and/or
behavioral traits. Although biometric systems are considered more secure than other traditional methods such as
password, or key, they also have many limitations such as noisy image, or spoof attack. One of the solutions to
overcome these limitations, is by applying a multibiometric system. Multibiometric system has a significant
effect in improving the performance of both security and accuracy of the system. It also can alleviate the spoof
attacks and reduce the fail to enroll error. A multi-sample is one implementations of the multibiometric systems.
In this study, a new algorithm is suggested to provide a second chance for the genuine user who is rejected, to
compare his/her provided finger with the other samples of the same finger. Multisampling fingerprint is used to
implement this new algorithm. The algorithm is activated when the match score of the user is not equal to a
threshold but close to it, then the system provides another chance to compare the finger with another sample of
the same trait. Using multi-sample biometric system improved the performance of the system by reducing the
False Reject Rate (FRR). Applying the original matching algorithm on the presented database produced 3
genuine users, and 5 imposters for the same fingerprint. While after implementing the suggested condition, the
system performance is enhanced by producing 6 genuine users, and 2 imposters for the same fingerprint. This
work was built and executed depending on a previous Matlab code presented by Zhi Li Wu. Thresholds and
Receiver Operating Characteristic (ROC) curves computed before and after implementing the suggested
multibiometric algorithm. Both ROC curves compared. A final decision and recommendations are provided
depending on the results obtained from this project
As we know the fingerprint is unique of every living objects. It is quite difficult to find out the prints.
Usually the Forensics use Fine powder and duct tapes to identify the prints of living object. As powder is
exceptionally muddled, so such molecule can cause loss of information after that examination the information is
coordinated with the system. The proposed system consists of an embedded device in which it consists of ultra
light to glow the fingerprints details. After that we can detect the fingerprint, analysis and it will checks on the
database, and it will return the output after matching. For matching and analysis of the Fingerprint, we will be
using the Algorithm for matching.
Performance Enhancement Of Multimodal Biometrics Using CryptosystemIJERA Editor
Multimodal biometrics means the unification of two or more uni modal biometrics so as to make the system more reliable and secure. Such systems promise better security. This study is a blend of iris and fingerprint recognition technique and their fusion at feature level. Our work comprises of two main sections: feature extraction of both modalities and fusing them before matching and finally application of an encryption technique to enhance the security of the fused template.
An Efficient Fingerprint Identification using Neural Network and BAT Algorithm IJECEIAES
The uniqueness, firmness, public recognition, and its minimum risk of intrusion made fingerprint is an expansively used personal authentication metrics. Fingerprint technology is a biometric technique used to distinguish persons based on their physical traits. Fingerprint based authentication schemes are becoming increasingly common and usage of these in fingerprint security schemes, made an objective to the attackers. The repute of the fingerprint image controls the sturdiness of a fingerprint authentication system. We intend for an effective method for fingerprint classification with the help of soft computing methods. The proposed classification scheme is classified into three phases. The first phase is preprocessing in which the fingerprint images are enhanced by employing median filters. After noise removal histogram equalization is achieved for augmenting the images. The second stage is the feature Extraction phase in which numerous image features such as Area, SURF, holo entropy, and SIFT features are extracted. The final phase is classification using hybrid Neural for classification of fingerprint as fake or original. The neural network is unified with BAT algorithm for optimizing the weight factor.
To ensure that the object presented in front of biometric device is real or reconstructed sample is a significant
problem in biometric authentication, which requires the development of new and efficient protection measures. This
paper, presents a software-based fake biometric detection method that can be used in multiple biometric systems to
detect different types of fraudulent access attempts. The objective of the proposed system is to enhance the security of
biometric recognition devices through the use of image quality assessment in a fast and user friendly manner. The
proposed approach presents a very low degree of complexity, which makes it suitable for real-time applications, using
25 general image quality features extracted from one image to distinguish between real and imposed samples. The
proposed method is highly competitive compared with other as the analysis of the general image quality of real
biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake
traits.
Overlapped Fingerprint Separation for Fingerprint AuthenticationIJERA Editor
Overlapped fingerprints captured at the crime scene plays significant role as an evidence to capture the criminals. As latent fingerprints are the accidently left skin impressions, so these are found to be with broken ridge composition, overlapped patterns and spoiled minutiae information. The Graphical User Interface (GUI) system is developed by using MATLAB R2015a software. This project also includes the development of standalone program for this system. The main purpose of GUI development is to get the value of real end points and real-branch points of a overlapped fingerprint image. The value of this point is used in fingerprint image matching process to identify the owner of an overlapped fingerprint image. The image enhancement consists of several process such as histogram equalization process, enhancement by Fast Fourier Transform (FFT) factor, and image binarization while minutiae extraction consist of ridge thinning process, region of interest (ROI) extraction, and minutiae extraction process. All processes should be done one by one.
Novel framework for optimized digital forensic for mitigating complex image ...IJECEIAES
Digital Image Forensic is significantly becoming popular owing to the increasing usage of the images as a media of information propagation. However, owing to the presence of various image editing tools and software, there is also an increasing threat to image content security. Reviewing the existing approaches to identify the traces or artifacts states that there is a large scope of optimization to be implemented to enhance the processing further. Therefore, this paper presents a novel framework that performs cost-effective optimization of digital forensic technique with an idea of accurately localizing the area of tampering as well as offers a capability to mitigate the attacks of various forms. The study outcome shows that the proposed system offers better outcomes in contrast to the existing system to a significant scale to prove that minor novelty in design attributes could induce better improvement with respect to accuracy as well as resilience toward all potential image threats.
Intelligent multimodal identification system based on local feature fusion be...nooriasukmaningtyas
Biometric identification systems, which use physical features to check a person's identity, ensure much higher security than password and number systems. Biometric features such as the face or a fingerprint can be stored on a microchip in a credit card, for example. A single modal biometric identification system fails to extract enough features for identification. Another disadvantage of using only one feature is not always readable. In this article, a smart multimodal biometric verification model for identifying and verifying a person's identity is recommended based on artificial intelligence methods. The proposed model is identified the iris and finger vein unique patterns each individual to overcome many challenges such as identity fraud, poor image quality, noise, and instability of the surrounding environment. Several experiments were performed on a dataset containing 50 people by using many matching methods. The results of the proposed model were provided a higher accuracy of 98%, with FAR and FRR of 0.0015% and 0.025%, respectively.
Biometric system works on behavioral and physiological biometric parameters to spot a person. Every fingerprint contains distinctive options and its recognizing system primarily works on native ridge feature local ridge endings, minutiae, core point, delta, etc. However, fingerprint pictures have poor quality thanks to variations in skin and impression conditions. In personal identification, fingerprint recognition is taken into account the foremost outstanding and reliable technique for matching with keep fingerprints within the information. Minutiae extraction is additional essential step in fingerprint matching. This paper provides plan regarding numerous feature extraction and matching algorithms for fingerprint recognition systems and to seek out that technique is additional reliable and secure.
A new multimodel approach for human authentication sclera vein and finger ve...eSAT Journals
Abstract
The vein structure is stable over time and can be manipulated for identifying human. The sclera portion of the human eye has blood vessel pattern which is unique for each human being. So, the sclera vein pattern can be used for a useful biometric feature. A few research works has been done over finger vein pattern recognition. Finger vein is an important biometric technique for personal identification and authentication. The finger vein is a blood vessel network under the finger skin. The network pattern is distinct for each individual, unaffected by aging and it is internal i.e. inside human skin which can always guarantee more security authentication. Sclera vein pattern recognition can face a few challenges like: the vein structure moves as the eye moves, low image quality, multilayered structure of the sclera vein and thickness of the sclera vein changes with the excitement level of the human body. To overcome this limitation, the multimodel biometrics is proposed through which the user can be authenticated either sclera vein or finger vein recognition. Sclera vein recognition used Y-shape descriptor and finger vein recognition used repeated line tracking based feature extraction method to effectively eliminate the most unlikely matches respectively. According to the available work in literatures and commercial utilization experiences, sclera vein and finger vein multimodality ensures higher performance and spoofing resistance. Thus building the multimodel biometric system increases the population coverage and improves the accuracy of the human recognition.
Keywords: Sclera Vein Recognition, Sclera Feature Matching, Sclera Matching, Sclera Segmentation, Feature Extraction, Finger Vein Recognition, Multimodel Biometrics
Role of fuzzy in multimodal biometrics systemKishor Singh
Person identification is possible through the biometrics using their physiological and behavioral characteristics such
as face, ear, thumb print, voice, signature and key stock. Unimodal biometric systems face a range of problems, including noisy
data, intra-class versions, small liberty, non-university, spoof assaults, and unsustainable error rates. Some of these drawbacks
can be overcome by multimodal biometric technologies, which incorporate data from various information sources. In this paper
we work on multimodal biometric using three modalities face, ear and foot to find the optimal results using fuzzy fusion
mechanism and produces final identification decision via a fuzzy rules that enhance the quality of multimodalities biometric
system.
METRICS FOR EVALUATING ALERTS IN INTRUSION DETECTION SYSTEMSIJNSA Journal
Network intrusions compromise the network’s confidentiality, integrity and availability of resources. Intrusion detection systems (IDSs) have been implemented to prevent the problem. Although IDS technologies are promising, their ability of detecting true alerts is far from being perfect. One problem is that of producing large numbers of false alerts, which are termed as malicious by the IDS. In this paper we propose a set of metrics for evaluating the IDS alerts. The metrics will identify false, low-level and redundant alerts by mapping alerts on a vulnerability database and calculating their impact. The metrics are calculated using a metric tool that we developed. We validated the metrics using Weyuker’s properties and Kaner’s framework. The metrics can be considered as mathematically valid since they satisfied seven of the nine Weyuker’s properties. In addition, they can be considered as workable since they satisfied all the evaluation questions from Kaner’s framework.
SMSECURITY: SECURITY SYSTEM AND SMS NOTIFICATION CUM FACE RECOGNITIONijcsit
This study used the Rapid Application Development (RAD) Methodology ensured that the phases in system
development are done in the software building process. A prototype was developed that is used in the pilot
implementation and a questionnaire has been distributed to the respondents to gather the information that
can be used to determine if the functions of the system can benefit the owner/user. The findings revealed t
that the system requires functional requirements such as; the user must be computer literate and
knowledgeable on how the security system works, the location must have a Telecommunication signal and
USB dongle must have loaded. Non-functional requirements such as; easy to use and high cost but can be
useful; Hardware and Software Requirements with the latest version of the software with the help of
computers that has higher specifications that the user/homeowner requires to have a user account to
access and operate the system the system has good technical performance as to functionality, reliability,
efficiency, and usability. Furthermore, the system entailed efficiency and was easy to use by the
respondents.
novel method of identifying fingerprint using minutiae matching in biometric ...INFOGAIN PUBLICATION
Fingerprint is one of the best apparatus to identify human because of its uniqueness, details information, hard to change and long-term indicators of human identity where there are several biometric feature that can be recycled to endorse the individuality. Identification of fingerprint is very important in forensic science, trace any part of human, collection of crime part and proof from a crime. This paper presents a new method of identifying fingerprint in biometrics security system. Fingerprint is one of the best example in biometric security because it can identify personal information and it is much secure than any other biometric identification system. The experimental result exhibits the performance of the proposed method.
A BAYESIAN CLASSIFICATION ON ASSET VULNERABILITY FOR REAL TIME REDUCTION OF F...IJNSA Journal
IT assets connected on internetwill encounter alien protocols and few parameters of protocol process are exposed as vulnerabilities. Intrusion Detection Systems (IDS) are installed to alerton suspicious traffic or activity. IDS issuesfalse positives alerts, if any behavior construe for partial attack pattern or the IDS lacks environment knowledge. Continuous monitoring of alerts to evolve whether, an alert is false positive or not is a major concern. In this paper we present design of an external module to IDS,to identify false positive alertsbased on anomaly based adaptive learning model. The novel feature of this design is that the system updates behavior profile of assets and environment with adaptive learning process.A mixture model is used for behavior modeling from reference data. The design of the detection and learning process are based on normal behavior and of environment. The anomaly alert identification algorithm isbuiltonSparse Markov Transducers (SMT) based probability.The total process is presented using real-time data. The Experimental results are validated and presentedwith reference to lab environment.
Broadcasting Forensics Using Machine Learning Approachesijtsrd
Broadcasting forensic is the practice of using scientific methods and techniques to analyse and authenticate Multimedia content. Over the past decade, consumer grade imaging sensors have become increasingly prevalent, generating vast quantities of images and videos that are used for various public and private communication purposes. Such applications include publicity, advocacy, disinformation, and deception, among others. This paper aims to develop tools that can extract knowledge from these visuals and comprehend their provenance. However, many images and videos undergo modification and manipulation before public release, which can misrepresent the facts and deceive viewers. To address this issue, we propose a set of forensics and counter forensic techniques that can help establish the authenticity and integrity of Multimedia content. Additionally, we suggest ways to modify the content intentionally to mislead potential adversaries. Our proposed tools are evaluated using publicly available datasets and independently organized challenges. Our results show that the forensics and counter forensic techniques can accurately identify manipulated content and can help restore the original image or video. Furthermore, in this paper demonstrate that the modified content can successfully deceive potential adversaries while remaining undetected by state of the art forensic methods. Amit Kapoor | Prof. Vinod Mahor "Broadcasting Forensics Using Machine Learning Approaches" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-3 , June 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd57545.pdf Paper URL: https://www.ijtsrd.com.com/engineering/computer-engineering/57545/broadcasting-forensics-using-machine-learning-approaches/amit-kapoor
Similar to IRJET-Gaussian Filter based Biometric System Security Enhancement (20)
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.