This document proposes a new security system called Captcha as Graphical Passwords (CaRP) that combines captcha technology with graphical passwords. CaRP aims to address security issues like online guessing attacks, relay attacks, and shoulder surfing. It leverages hard AI problems to make passwords difficult for computers to guess automatically, while still being usable for humans. The system would use captcha-like puzzles as passwords that are hard for AI but easy for people. This approach could help protect against dictionary attacks and relay attacks on online services.
At Softroniics we provide job oriented training for freshers in IT sector. We are providing IEEE project guidance and Final year project guidance. We are Pioneers in all leading technologies like Android, Java, .NET, PHP, Python, Embedded Systems, Matlab, NS2, VLSI, Modelsim, Tanner, Xilinx etc. We are specializiling in technologies like Big Data, Cloud Computing, Internet Of Things (iOT), Data Mining, Networking, Information Security, Image Processing and many other. We are providing long term and short term internship also. We are also providing IEEE project support at Calicut, Thrissur and Palakkad. For more details contact 9037291113, 7907435072
Talha Obaid, Email Security, Symantec at MLconf ATL 2017MLconf
A Machine Learning approach for detecting a Malware:
The project is to improve the way we detect script based malware using Machine Learning. Malware has become one of the most active channel to deliver threats like Banking Trojans and Ransomware. The talk is aimed at finding a new and effective way to detect the malware. We started with acquiring both malicious and clean samples. Later we performed feature identification, while building on top of existing knowledge base of malware. Then we performed automated feature extraction. After certain feature set is obtained, we teased-out feature which are categorical, interdependent or composite. We applied varying machine learning models, producing both binary and categorical outcomes. We cross validated our results and re-tuned our feature set and our model, until we obtained satisfying results, with least false-positives. We concluded that not all the extracted features are significant, in fact some features are detrimental on the model performance. Once such features are factored-out, it results not only in better match, but also provides a significant gain in performance.
Efficient Securing System Using Graphical CaptchaSankar Anand
The document proposes a new security system called CaRP (Captcha as graphical passwords) that integrates captcha technology into a graphical password scheme. CaRP allows users to set passwords by clicking on images in a captcha challenge. This addresses weaknesses in existing systems like vulnerability to brute force and dictionary attacks. The proposed system offers stronger security against online attacks while being easy for users. It is recommended for domains like banking that require enhanced security.
DevSecCon London 2019 - Achieve AI-Powered API Privacy Using Open SourceGianluca Brigandi
This presentation, part talk and part practical demonstration, introduces Privacy-by-Design (PbD) onto a typical software application as part of a Secure Development Lifecycle, with a live demo showcasing how artificial intelligence (AI) can contribute to the process.
Ashrith Barthur, Security Scientist, H2o.ai, at MLconf 2017MLconf
This document discusses using machine learning to identify network attack behavior. It describes classifying different types of attacks, such as DDoS, ransomware, and phishing. Short-term attacks are aimed at overwhelming services, while long-term attacks involve reconnaissance, infrastructure vulnerabilities, and data exfiltration over long periods. Current solutions are limited as they are rule-based and stateless. The document proposes using features and machine learning models to better connect events over time and identify long-term attacks. Examples of useful features for the models include connection lengths and domain name statistics. Both manual and assisted labeling approaches are described to generate training data for the models.
This document proposes a new security system called Captcha as Graphical Passwords (CaRP) that combines captcha technology with graphical passwords. CaRP aims to address security issues like online guessing attacks, relay attacks, and shoulder surfing. It leverages hard AI problems to make passwords difficult for computers to guess automatically, while still being usable for humans. The system would use captcha-like puzzles as passwords that are hard for AI but easy for people. This approach could help protect against dictionary attacks and relay attacks on online services.
At Softroniics we provide job oriented training for freshers in IT sector. We are providing IEEE project guidance and Final year project guidance. We are Pioneers in all leading technologies like Android, Java, .NET, PHP, Python, Embedded Systems, Matlab, NS2, VLSI, Modelsim, Tanner, Xilinx etc. We are specializiling in technologies like Big Data, Cloud Computing, Internet Of Things (iOT), Data Mining, Networking, Information Security, Image Processing and many other. We are providing long term and short term internship also. We are also providing IEEE project support at Calicut, Thrissur and Palakkad. For more details contact 9037291113, 7907435072
Talha Obaid, Email Security, Symantec at MLconf ATL 2017MLconf
A Machine Learning approach for detecting a Malware:
The project is to improve the way we detect script based malware using Machine Learning. Malware has become one of the most active channel to deliver threats like Banking Trojans and Ransomware. The talk is aimed at finding a new and effective way to detect the malware. We started with acquiring both malicious and clean samples. Later we performed feature identification, while building on top of existing knowledge base of malware. Then we performed automated feature extraction. After certain feature set is obtained, we teased-out feature which are categorical, interdependent or composite. We applied varying machine learning models, producing both binary and categorical outcomes. We cross validated our results and re-tuned our feature set and our model, until we obtained satisfying results, with least false-positives. We concluded that not all the extracted features are significant, in fact some features are detrimental on the model performance. Once such features are factored-out, it results not only in better match, but also provides a significant gain in performance.
Efficient Securing System Using Graphical CaptchaSankar Anand
The document proposes a new security system called CaRP (Captcha as graphical passwords) that integrates captcha technology into a graphical password scheme. CaRP allows users to set passwords by clicking on images in a captcha challenge. This addresses weaknesses in existing systems like vulnerability to brute force and dictionary attacks. The proposed system offers stronger security against online attacks while being easy for users. It is recommended for domains like banking that require enhanced security.
DevSecCon London 2019 - Achieve AI-Powered API Privacy Using Open SourceGianluca Brigandi
This presentation, part talk and part practical demonstration, introduces Privacy-by-Design (PbD) onto a typical software application as part of a Secure Development Lifecycle, with a live demo showcasing how artificial intelligence (AI) can contribute to the process.
Ashrith Barthur, Security Scientist, H2o.ai, at MLconf 2017MLconf
This document discusses using machine learning to identify network attack behavior. It describes classifying different types of attacks, such as DDoS, ransomware, and phishing. Short-term attacks are aimed at overwhelming services, while long-term attacks involve reconnaissance, infrastructure vulnerabilities, and data exfiltration over long periods. Current solutions are limited as they are rule-based and stateless. The document proposes using features and machine learning models to better connect events over time and identify long-term attacks. Examples of useful features for the models include connection lengths and domain name statistics. Both manual and assisted labeling approaches are described to generate training data for the models.
Understand How Machine Learning Defends Against Zero-Day ThreatsRahul Mohandas
Detection Challenges
Machine Learning Approaches
Modeling Machine Learning classifiers
Attacks on Machine Learning Defenses
Real Protect
Deep Learning in Sandbox
Product security by Blockchain, AI and Security CertsLabSharegroup
Three themes You need to think about Product Security — and some tips for How to Do It
I have been working with software security laboratories and IT security firms for years. I have talked with clients, read and watched dozens of articles/videos and talked with several experts about product security themes, future, technologies.
The three themes are:
Is the blockchain the new technology of trust?
Blockchain has the potential to transform industries. However, some security experts raised questions: If blockchain is broadly used in technology solutions will security standards be adopted? How to protect the cryptographic keys that allow access to the blockchain applications? Although it is true that the potential is huge such as securing IoT nodes, edge devices with authentication, improved confidentiality and data integrity, disrupting current PKI systems, reducing DDoS attacks etc.
AI (Machine Learning, Deep Learning, Reinforcement Learning algorithm) potential in Product Security
Machine learning can help in creating products that analyse threats and respond to attacks and security incidents. There are several repositories on GitHub or open-source codes by IBM available for developers. Deep learning networks are rapidly growing due to cheap cloud GPU services and after Reinforcement learning algorithm’s last success nobody knows the upper limit.
Product Security by International security standards and practices
The present, future, and developmental orientations of independent third party certificates Industry. How can the international standards answer the rapid growth of new technologies and maintain secure applications in IoT, Blockchain or AI-driven industries?
Are IT products reliable, secure and will they stay that way?
I would like to explain Product Security in a simple way. My goal is the introduction of product security for Tech startups, fast-growing Tech firms. Furthermore, I would like to emphasize the benefits of product security certification.
(Workshop) Reverse Engineering - Protecting and Breaking the SoftwareSatria Ady Pradana
The document discusses reverse engineering principles and techniques. It introduces reverse engineering as breaking down an existing system to understand its construction and components. The three fundamental principles are comprehension, decomposition, and reconstruction. Common reverse engineering practices are described like resource modification, control flow bypass, and code caving. Hands-on examples are provided using a CrackMe program in C# to demonstrate reverse engineering a .NET binary, including modifying strings, bypassing checks, changing function targets, and injecting custom code.
The document summarizes key aspects of cloud security based on a lecture given by Dr. Rajesh P Barnwal. It discusses the evolution of cloud models from bare metal to serverless computing. It highlights some major security challenges in cloud computing like multi-tenancy, loss of control, and third party handling of data. The document then covers modern cloud security measures like identity and access management, secure access service edge, firewall as a service, cloud access security brokers, and zero trust network access. It also discusses new paradigms like serverless computing and their advantages for security.
This document contains the resume of Manjesh N, who is seeking a position as a Network Security Engineer. It outlines his skills and experience in networking, security, and various certifications. His experience includes over 8 years providing technical support for networking and security products from Arbor, SonicWALL, and Dell. He has extensive hands-on experience with firewalls, routers, switches, and other networking devices.
Modern Security Operations & Common Roles/Competencies Harry McLaren
This document provides an overview of modern security operations technologies and frameworks from the perspective of Harry McLaren, a cybersecurity professional with 14 years of experience. It discusses the evolution of security operations functions from basic monitoring to advanced detection, analysis, and response. Key components of a security operations center are described, including threat modeling, detection configuration, and the MITRE ATT&CK framework for mapping threats, techniques, and countermeasures. Implementing a DevOps approach and config-as-code is advocated to improve effectiveness, faster adaptation, and increased scalability. Common security analyst roles and competencies such as technical skills, behaviors, and emotional intelligence are also covered.
This lightning talk is a brief discussion around how PepsiCo is managing their ‘detection catalog’ and how it maps and is enhanced by the MITRE ATT&CK framework.
Applying a Security Kernel Framework to Smart Meter GatewaysMarcel Winandy
The document discusses applying a security kernel framework to smart meter gateways. It notes privacy and security are critical issues for smart metering given data from homes is communicated over the internet. The EU has directives requiring smart meters be installed in most homes by 2020 and specifying security and privacy protections. The talk describes security requirements for smart meter gateways set by German standards, and issues with existing approaches not meeting them. It then introduces the TURAYA security kernel framework as a way to address these issues and simplify developing secure smart meter gateways.
I will talk about innovation in the area of cyber security analytics - developing machine learning methods to detect and block cyber attacks (e.g. detecting ransomware within 4 seconds of execution and killing the underlying processes). Rather than just focusing on this as a 'black box', I'll pull it apart and talk about how we can use these methods to enable security practitioners (SOC/CIRT etc) to ask and answer questions about 'what' and 'why' these methods are flagging attacks. I'll also talk about resilience of machine learning methods to manipulation and adversarial attacks - how stable these approaches are to diversity and evolution of malware for example.
Using MITRE PRE-ATTACK and ATTACK in Cybercrime Education and ResearchMITRE - ATT&CKcon
From MITRE ATT&CKcon Power Hour October 2020
By:
Aunshul Rege, Associate Professor, Temple University, @prof_rege
Rachel Bleiman, PhD Student/NSF Graduate Research Assistant, Temple University, @rab1928
This presentation from the MITRE ATT&CKcon Power Hour session on October 9, 2020, explores the application of the MITRE ATT&CK® and PRE-ATT&CK matrices in cybercrime education and research. Specifically, Rege and Bleiman demonstrate the mapping of the PRE-ATT&CK matrix to social engineering case studies as an experiential learning project in an upper-level cybercrime liberal arts course. It thus allows students to understand the alignment process of threat intelligence to the PRE-ATT&CK framework and also learn about its usefulness/limitations. The talk also discusses the mapping of the ATT&CK matrix, tactics, techniques, software, and groups for two cybercrime datasets created by collating publicly disclosed incidents: (i) critical infrastructure ransomware (CIRW) incidents, and (ii) social engineering (SE) incidents. For the CIRW dataset, 39% of the strains mapped onto the ATT&CK software. For the SE dataset, 49% of the groups and 65% of the techniques map on to the MITRE framework. This helps the researchers identify the framework's usefulness/limitations and also helps our datasets connect to richer information that may not otherwise be available in the publicly disclosed incidents.
This document proposes a new security system called Captcha as Graphical Passwords (CaRP) that combines captcha and graphical passwords to address online security issues. CaRP uses hard AI problems from captcha tests to create password entry challenges that are difficult for computers to solve but easy for humans. This allows CaRP to protect against online guessing attacks and relay attacks on passwords. The system offers reasonable security and usability to improve online security for applications.
Captcha as graphical passwords a new security primitive based on hard ai prob...IGEEKS TECHNOLOGIES
The document proposes a new security primitive called Captcha as Graphical Passwords (CaRP) that uses hard AI problems from Captcha technology to create a novel graphical password system. CaRP aims to address security issues like online guessing attacks, relay attacks, and shoulder surfing. It can probabilistically thwart automated online guessing even if the password is in the search set. CaRP also aims to solve the "image hotspot" problem in other graphical password systems. The document outlines examples of how CaRP could work and argues that it offers reasonable security and usability for improving online security.
This document presents a project on a novel graphical password system called Captcha as Graphical Passwords (CaRP) that uses CAPTCHA technology. CaRP addresses security issues like online guessing attacks, relay attacks, and shoulder surfing. It offers protection against dictionary attacks and relay attacks while being reasonably secure and usable. The document describes the existing CAPTCHA system, disadvantages of the current approach, the proposed CaRP system and its advantages, software and hardware requirements, UML diagrams, sample registration and login pages, and test cases.
Security for Hard AI Problems Using CaRP Authenticationpaperpublications3
Abstract: Using hard AI problems for security is emerging as an exciting new paradigm, but has been underexplored. This approach present a new security primitive based on hard AI problems, namely, a novel family of graphical password systems built on top of Captcha technology, which is called Captcha as graphical passwords (CaRP). CaRP is both a Captcha and a graphical password scheme. CaRP addresses a number of security problems altogether, such as online guessing attacks, relay attacks, and, if combined with dual-view technologies, shoulder-surfing attacks. Notably, a CaRP password can be found only probabilistically by automatic online guessing attacks even if the password is in the search set.
This document proposes a new type of graphical password system called CAPTCHA As Graphical Passwords (CaRP) that integrates CAPTCHAs with password authentication. CaRP schemes require users to click on a sequence of visual objects like characters, animals or grid cells in an image to enter their password. This combines the tasks of recognizing CAPTCHA objects and recalling a click-sequence password. CaRP aims to thwart automatic guessing attacks by generating new images for each login attempt. Recognition-based CaRP examples include Click Text and Click Animal, while Animal Grid combines recognition and cued recall. CaRP is resistant to relay attacks and provides stronger security than other graphical passwords by leveraging hard AI problems in CAPT
Many security primitives are supported hard
mathematical problems. Passwords remain the foremost
widely used authentication method despite their well-known
security weaknesses. CAPTCHA authentication is clearly a
practical problem.
— A CAPTCHA means "Completely Automated
Public Turing test to tell Computers and Humans Apart". It is a
type of challenge-response test used in computing to determine
whether or not the user is human. CaRP is both a Captcha and a
graphical password scheme. CaRP addresses a number of
security problems altogether, such as online guessing attacks,
relay attacks, and, if combined with dual-view technologies,
shoulder-surfing attacks. Particularly, a CaRP password can be
found only probabilistically by automatic online guessing attacks,
even if the password is in the search set. CaRP also offers an
approach to address the well-known image hotspot problem in
popular graphical password systems, such as PassPoints, which
often leads to weak password choices. Thus, a variant to the
login/password scheme, using graphical scheme was introduced.
But it also suffered due to shoulder-surfing and screen dump
attacks. Thus it introduces a framework to proposed (IPAS)
Implicit Password Authentication System, which is protected to
the common attacks suffered by other authentication schemes.
IRJET- Carp a Graphical Password: Enhancing Security using AIIRJET Journal
This document proposes a new security method called CaRP (Captcha as a Graphical Password) that combines Captcha and graphical passwords to enhance online security. CaRP addresses security issues like guessing attacks, relay attacks, and shoulder surfing. It works by generating a new image-based challenge for each login attempt. Since the images change, automated programs cannot learn or guess the password between attempts like they can with text passwords. CaRP draws on the gap in abilities between humans and machines to recognize visual patterns. The document outlines the basic CaRP authentication process and different types of CaRP schemes that could be used. It argues that CaRP provides a more secure authentication method than traditional passwords or Captchas alone.
CAPTCHA as Graphical Password: A Novel Approach to Enhance the Security in WWWIJLT EMAS
This research aims to study the existing password
scheme and to design and develop a new improved graphical
password scheme. A novel protection primitive is presented in
view of strong AI problems namely a new family of graphical
password scheme built up on top of captcha technology, which
we call Captcha as graphical password (CaRP). CaRP is both a
captcha and graphical password scheme. CaRP addresses
number of security issues altogether for example, online guessing
attacks, relay attacks and if combined with dual -view
technologies shoulder-surfing attacks. CaRP likewise offers a
novel way to deal with address the notable image hotspot
problem in well-known
A Survey of Comparative Analysis of Secure Passwords using CaRP by Different ...IRJET Journal
This document summarizes research on CAPTCHAs and graphical passwords. It discusses how CAPTCHAs are used to distinguish humans from bots but have usability issues. Graphical passwords were developed as an alternative but are vulnerable to attacks. The document reviews several techniques for CAPTCHAs and graphical passwords, including CaRP which uses images as passwords and is resistant to guessing attacks. It analyzes the security and usability of different schemes and automated attack methods against PassPoints passwords. In conclusion, image-based CAPTCHAs can reduce spam while advancing AI, and new forms may be more robust against attacks.
Pass byo bring your own picture for securing graphical passwordsLeMeniz Infotech
This document describes PassBYOP, a new graphical password scheme that uses live video of a physical token (such as a photo on a mobile phone) rather than static digital images. Three feasibility studies examine its reliability, usability, and security against observation attacks. Results found passwords based on image features to be viable, with task times and error rates comparable to prior schemes. Using a user-owned physical token increased security against observation without additional user burden, showing promise for more secure graphical passwords.
Understand How Machine Learning Defends Against Zero-Day ThreatsRahul Mohandas
Detection Challenges
Machine Learning Approaches
Modeling Machine Learning classifiers
Attacks on Machine Learning Defenses
Real Protect
Deep Learning in Sandbox
Product security by Blockchain, AI and Security CertsLabSharegroup
Three themes You need to think about Product Security — and some tips for How to Do It
I have been working with software security laboratories and IT security firms for years. I have talked with clients, read and watched dozens of articles/videos and talked with several experts about product security themes, future, technologies.
The three themes are:
Is the blockchain the new technology of trust?
Blockchain has the potential to transform industries. However, some security experts raised questions: If blockchain is broadly used in technology solutions will security standards be adopted? How to protect the cryptographic keys that allow access to the blockchain applications? Although it is true that the potential is huge such as securing IoT nodes, edge devices with authentication, improved confidentiality and data integrity, disrupting current PKI systems, reducing DDoS attacks etc.
AI (Machine Learning, Deep Learning, Reinforcement Learning algorithm) potential in Product Security
Machine learning can help in creating products that analyse threats and respond to attacks and security incidents. There are several repositories on GitHub or open-source codes by IBM available for developers. Deep learning networks are rapidly growing due to cheap cloud GPU services and after Reinforcement learning algorithm’s last success nobody knows the upper limit.
Product Security by International security standards and practices
The present, future, and developmental orientations of independent third party certificates Industry. How can the international standards answer the rapid growth of new technologies and maintain secure applications in IoT, Blockchain or AI-driven industries?
Are IT products reliable, secure and will they stay that way?
I would like to explain Product Security in a simple way. My goal is the introduction of product security for Tech startups, fast-growing Tech firms. Furthermore, I would like to emphasize the benefits of product security certification.
(Workshop) Reverse Engineering - Protecting and Breaking the SoftwareSatria Ady Pradana
The document discusses reverse engineering principles and techniques. It introduces reverse engineering as breaking down an existing system to understand its construction and components. The three fundamental principles are comprehension, decomposition, and reconstruction. Common reverse engineering practices are described like resource modification, control flow bypass, and code caving. Hands-on examples are provided using a CrackMe program in C# to demonstrate reverse engineering a .NET binary, including modifying strings, bypassing checks, changing function targets, and injecting custom code.
The document summarizes key aspects of cloud security based on a lecture given by Dr. Rajesh P Barnwal. It discusses the evolution of cloud models from bare metal to serverless computing. It highlights some major security challenges in cloud computing like multi-tenancy, loss of control, and third party handling of data. The document then covers modern cloud security measures like identity and access management, secure access service edge, firewall as a service, cloud access security brokers, and zero trust network access. It also discusses new paradigms like serverless computing and their advantages for security.
This document contains the resume of Manjesh N, who is seeking a position as a Network Security Engineer. It outlines his skills and experience in networking, security, and various certifications. His experience includes over 8 years providing technical support for networking and security products from Arbor, SonicWALL, and Dell. He has extensive hands-on experience with firewalls, routers, switches, and other networking devices.
Modern Security Operations & Common Roles/Competencies Harry McLaren
This document provides an overview of modern security operations technologies and frameworks from the perspective of Harry McLaren, a cybersecurity professional with 14 years of experience. It discusses the evolution of security operations functions from basic monitoring to advanced detection, analysis, and response. Key components of a security operations center are described, including threat modeling, detection configuration, and the MITRE ATT&CK framework for mapping threats, techniques, and countermeasures. Implementing a DevOps approach and config-as-code is advocated to improve effectiveness, faster adaptation, and increased scalability. Common security analyst roles and competencies such as technical skills, behaviors, and emotional intelligence are also covered.
This lightning talk is a brief discussion around how PepsiCo is managing their ‘detection catalog’ and how it maps and is enhanced by the MITRE ATT&CK framework.
Applying a Security Kernel Framework to Smart Meter GatewaysMarcel Winandy
The document discusses applying a security kernel framework to smart meter gateways. It notes privacy and security are critical issues for smart metering given data from homes is communicated over the internet. The EU has directives requiring smart meters be installed in most homes by 2020 and specifying security and privacy protections. The talk describes security requirements for smart meter gateways set by German standards, and issues with existing approaches not meeting them. It then introduces the TURAYA security kernel framework as a way to address these issues and simplify developing secure smart meter gateways.
I will talk about innovation in the area of cyber security analytics - developing machine learning methods to detect and block cyber attacks (e.g. detecting ransomware within 4 seconds of execution and killing the underlying processes). Rather than just focusing on this as a 'black box', I'll pull it apart and talk about how we can use these methods to enable security practitioners (SOC/CIRT etc) to ask and answer questions about 'what' and 'why' these methods are flagging attacks. I'll also talk about resilience of machine learning methods to manipulation and adversarial attacks - how stable these approaches are to diversity and evolution of malware for example.
Using MITRE PRE-ATTACK and ATTACK in Cybercrime Education and ResearchMITRE - ATT&CKcon
From MITRE ATT&CKcon Power Hour October 2020
By:
Aunshul Rege, Associate Professor, Temple University, @prof_rege
Rachel Bleiman, PhD Student/NSF Graduate Research Assistant, Temple University, @rab1928
This presentation from the MITRE ATT&CKcon Power Hour session on October 9, 2020, explores the application of the MITRE ATT&CK® and PRE-ATT&CK matrices in cybercrime education and research. Specifically, Rege and Bleiman demonstrate the mapping of the PRE-ATT&CK matrix to social engineering case studies as an experiential learning project in an upper-level cybercrime liberal arts course. It thus allows students to understand the alignment process of threat intelligence to the PRE-ATT&CK framework and also learn about its usefulness/limitations. The talk also discusses the mapping of the ATT&CK matrix, tactics, techniques, software, and groups for two cybercrime datasets created by collating publicly disclosed incidents: (i) critical infrastructure ransomware (CIRW) incidents, and (ii) social engineering (SE) incidents. For the CIRW dataset, 39% of the strains mapped onto the ATT&CK software. For the SE dataset, 49% of the groups and 65% of the techniques map on to the MITRE framework. This helps the researchers identify the framework's usefulness/limitations and also helps our datasets connect to richer information that may not otherwise be available in the publicly disclosed incidents.
This document proposes a new security system called Captcha as Graphical Passwords (CaRP) that combines captcha and graphical passwords to address online security issues. CaRP uses hard AI problems from captcha tests to create password entry challenges that are difficult for computers to solve but easy for humans. This allows CaRP to protect against online guessing attacks and relay attacks on passwords. The system offers reasonable security and usability to improve online security for applications.
Captcha as graphical passwords a new security primitive based on hard ai prob...IGEEKS TECHNOLOGIES
The document proposes a new security primitive called Captcha as Graphical Passwords (CaRP) that uses hard AI problems from Captcha technology to create a novel graphical password system. CaRP aims to address security issues like online guessing attacks, relay attacks, and shoulder surfing. It can probabilistically thwart automated online guessing even if the password is in the search set. CaRP also aims to solve the "image hotspot" problem in other graphical password systems. The document outlines examples of how CaRP could work and argues that it offers reasonable security and usability for improving online security.
This document presents a project on a novel graphical password system called Captcha as Graphical Passwords (CaRP) that uses CAPTCHA technology. CaRP addresses security issues like online guessing attacks, relay attacks, and shoulder surfing. It offers protection against dictionary attacks and relay attacks while being reasonably secure and usable. The document describes the existing CAPTCHA system, disadvantages of the current approach, the proposed CaRP system and its advantages, software and hardware requirements, UML diagrams, sample registration and login pages, and test cases.
Security for Hard AI Problems Using CaRP Authenticationpaperpublications3
Abstract: Using hard AI problems for security is emerging as an exciting new paradigm, but has been underexplored. This approach present a new security primitive based on hard AI problems, namely, a novel family of graphical password systems built on top of Captcha technology, which is called Captcha as graphical passwords (CaRP). CaRP is both a Captcha and a graphical password scheme. CaRP addresses a number of security problems altogether, such as online guessing attacks, relay attacks, and, if combined with dual-view technologies, shoulder-surfing attacks. Notably, a CaRP password can be found only probabilistically by automatic online guessing attacks even if the password is in the search set.
This document proposes a new type of graphical password system called CAPTCHA As Graphical Passwords (CaRP) that integrates CAPTCHAs with password authentication. CaRP schemes require users to click on a sequence of visual objects like characters, animals or grid cells in an image to enter their password. This combines the tasks of recognizing CAPTCHA objects and recalling a click-sequence password. CaRP aims to thwart automatic guessing attacks by generating new images for each login attempt. Recognition-based CaRP examples include Click Text and Click Animal, while Animal Grid combines recognition and cued recall. CaRP is resistant to relay attacks and provides stronger security than other graphical passwords by leveraging hard AI problems in CAPT
Many security primitives are supported hard
mathematical problems. Passwords remain the foremost
widely used authentication method despite their well-known
security weaknesses. CAPTCHA authentication is clearly a
practical problem.
— A CAPTCHA means "Completely Automated
Public Turing test to tell Computers and Humans Apart". It is a
type of challenge-response test used in computing to determine
whether or not the user is human. CaRP is both a Captcha and a
graphical password scheme. CaRP addresses a number of
security problems altogether, such as online guessing attacks,
relay attacks, and, if combined with dual-view technologies,
shoulder-surfing attacks. Particularly, a CaRP password can be
found only probabilistically by automatic online guessing attacks,
even if the password is in the search set. CaRP also offers an
approach to address the well-known image hotspot problem in
popular graphical password systems, such as PassPoints, which
often leads to weak password choices. Thus, a variant to the
login/password scheme, using graphical scheme was introduced.
But it also suffered due to shoulder-surfing and screen dump
attacks. Thus it introduces a framework to proposed (IPAS)
Implicit Password Authentication System, which is protected to
the common attacks suffered by other authentication schemes.
IRJET- Carp a Graphical Password: Enhancing Security using AIIRJET Journal
This document proposes a new security method called CaRP (Captcha as a Graphical Password) that combines Captcha and graphical passwords to enhance online security. CaRP addresses security issues like guessing attacks, relay attacks, and shoulder surfing. It works by generating a new image-based challenge for each login attempt. Since the images change, automated programs cannot learn or guess the password between attempts like they can with text passwords. CaRP draws on the gap in abilities between humans and machines to recognize visual patterns. The document outlines the basic CaRP authentication process and different types of CaRP schemes that could be used. It argues that CaRP provides a more secure authentication method than traditional passwords or Captchas alone.
CAPTCHA as Graphical Password: A Novel Approach to Enhance the Security in WWWIJLT EMAS
This research aims to study the existing password
scheme and to design and develop a new improved graphical
password scheme. A novel protection primitive is presented in
view of strong AI problems namely a new family of graphical
password scheme built up on top of captcha technology, which
we call Captcha as graphical password (CaRP). CaRP is both a
captcha and graphical password scheme. CaRP addresses
number of security issues altogether for example, online guessing
attacks, relay attacks and if combined with dual -view
technologies shoulder-surfing attacks. CaRP likewise offers a
novel way to deal with address the notable image hotspot
problem in well-known
A Survey of Comparative Analysis of Secure Passwords using CaRP by Different ...IRJET Journal
This document summarizes research on CAPTCHAs and graphical passwords. It discusses how CAPTCHAs are used to distinguish humans from bots but have usability issues. Graphical passwords were developed as an alternative but are vulnerable to attacks. The document reviews several techniques for CAPTCHAs and graphical passwords, including CaRP which uses images as passwords and is resistant to guessing attacks. It analyzes the security and usability of different schemes and automated attack methods against PassPoints passwords. In conclusion, image-based CAPTCHAs can reduce spam while advancing AI, and new forms may be more robust against attacks.
Pass byo bring your own picture for securing graphical passwordsLeMeniz Infotech
This document describes PassBYOP, a new graphical password scheme that uses live video of a physical token (such as a photo on a mobile phone) rather than static digital images. Three feasibility studies examine its reliability, usability, and security against observation attacks. Results found passwords based on image features to be viable, with task times and error rates comparable to prior schemes. Using a user-owned physical token increased security against observation without additional user burden, showing promise for more secure graphical passwords.
SHUFFLED INPUT GRAPHICAL PASSWORD AUTHENTICATION SCHEMES BUILT ON CAPTCHA TEC...ijiert bestjournal
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captcha as graphical passwords—a new security primitive based on hard ai problems
1. Captcha as Graphical Passwords—A New Security Primitive Based on Hard AI Problems
Captcha as Graphical Passwords—A New Security Primitive Based
on Hard AI Problems
Many security primitives are based on hard mathematical problems. Using hard AI problems for
security is emerging as an exciting new paradigm, but has been under-explored. In this paper, we
present a new security primitive based on hard AI problems, namely, a novel family of graphical
password systems built on top of Captcha technology, which we call Captcha as graphical
passwords (CaRP). CaRP is both a Captcha and a graphical password scheme. CaRP addresses a
number of security problems altogether, such as online guessing attacks, relay attacks, and, if
combined with dual- view technologies, shoulder-surfing attacks. Notably, a CaRP password can
be found only probabilistically by automatic online guessing attacks even if the password is in
the search set. CaRP also offers a novel approach to address the well-known image hotspot
problem in popular graphical password systems, such as PassPoints, that often leads to weak
password choices. CaRP is not a panacea, but it offers reasonable security and usability and
appears to fit well with some practical applications for improving online security.
The most notable primitive invented is Captcha, which distinguishes human users from
computers by presenting a challenge, i.e., a puzzle, beyond the capability of computers
but easy for humans. Captcha is now a standard Internet security technique to protect
online email and other services from being abused by bots.
DISADVANTAGES OF EXISTING SYSTEM:
This existing paradigm has achieved just a limited success as compared with the
cryptographic primitives based on hard math problems and their wide applications.
Contact: 9703109334, 9533694296
ABSTRACT:
EXISTING SYSTEM:
PROPOSED SYSTEM:
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in
2. Captcha as Graphical Passwords—A New Security Primitive Based on Hard AI Problems
In this paper, we present a new security primitive based on hard AI problems, namely, a
novel family of graphical password systems built on top of Captcha technology, which
we call Captcha as graphical passwords (CaRP).
CaRP is both a Captcha and a graphical password scheme. CaRP addresses a number of
security problems altogether, such as online guessing attacks, relay attacks, and, if
combined with dual-view technologies, shoulder-surfing attacks.
ADVANTAGES OF PROPOSED SYSTEM:
CaRP offers protection against online dictionary attacks on passwords, which have been
for long time a major security threat for various online services.
CaRP also offers protection against relay attacks, an increasing threat to bypass Captchas
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Floppy Drive : 1.44 Mb.
Monitor : 15 VGA Colour.
Mouse : Logitech.
Ram : 512 Mb.
SOFTWARE REQUIREMENTS:
Operating system : Windows XP/7.
Coding Language : JAVA/J2EE
IDE : Netbeans 7.4
Database : MYSQL
Contact: 9703109334, 9533694296
protection.
REFERENCE:
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in
3. Captcha as Graphical Passwords—A New Security Primitive Based on Hard AI Problems
Bin B. Zhu, Jeff Yan, Guanbo Bao, Maowei Yang, and N ing Xu ,“Captcha as Graphical
Passwords—A New Security Primitive Based on Hard AI Problems”, VOL. 9, NO. 6, JUNE
2014.
Contact: 9703109334, 9533694296
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in