The Experts below are selected from a list of 3363 Experts worldwide ranked by ideXlab platform

Erich Heintzelman - One of the best experts on this subject based on the ideXlab platform.

Priyadarsi Nanda - One of the best experts on this subject based on the ideXlab platform.

  • sandfox secure sandboxed and isolated environment for Firefox Browser
    Security of Information and Networks, 2015
    Co-Authors: Anil Saini, Manoj Singh Gaur, Vijay Laxmi, Priyadarsi Nanda
    Abstract:

    Browser functionalities can be widely extended by Browser extensions. One of the key features that makes Browser extensions so powerful is that they run with "high" privileges. As a consequence, a vulnerable or malicious extension might expose Browser, and operating system (OS) resources to possible attacks such as privilege escalation, information stealing, and session hijacking. The resources are referred as Browser as well as OS components accessed through Browser extension such as accessing information on the web application, executing arbitrary processes, and even access files from a host file system. This paper presents sandFOX (secure sandbox and iso- lated environment), a client-side Browser policies for constructing sandbox environment. sandFOX allows the Browser extension to express fine-grained OS specific security policies that are enforced at runtime. In particular, our proposed policies provide the protection to OS resources (e.g., host file system, network and processes) from the Browser attacks. We use Security-Enhanced Linux (SELinux) to tune OS and build a sandbox that helps in reducing potential damage from attacks on the OS resources. To show the practicality of sandFOX in a range of settings, we compute the effectiveness of sandFOX for various Browser attacks on OS resources. We also show that sandFOX enabled Browser experiences low overhead on loading pages and utilizes negligible memory when running with sandbox environment.

  • SIN - sandFOX: secure sandboxed and isolated environment for Firefox Browser
    Proceedings of the 8th International Conference on Security of Information and Networks - SIN '15, 2015
    Co-Authors: Anil Saini, Manoj Singh Gaur, Vijay Laxmi, Priyadarsi Nanda
    Abstract:

    Browser functionalities can be widely extended by Browser extensions. One of the key features that makes Browser extensions so powerful is that they run with "high" privileges. As a consequence, a vulnerable or malicious extension might expose Browser, and operating system (OS) resources to possible attacks such as privilege escalation, information stealing, and session hijacking. The resources are referred as Browser as well as OS components accessed through Browser extension such as accessing information on the web application, executing arbitrary processes, and even access files from a host file system. This paper presents sandFOX (secure sandbox and iso- lated environment), a client-side Browser policies for constructing sandbox environment. sandFOX allows the Browser extension to express fine-grained OS specific security policies that are enforced at runtime. In particular, our proposed policies provide the protection to OS resources (e.g., host file system, network and processes) from the Browser attacks. We use Security-Enhanced Linux (SELinux) to tune OS and build a sandbox that helps in reducing potential damage from attacks on the OS resources. To show the practicality of sandFOX in a range of settings, we compute the effectiveness of sandFOX for various Browser attacks on OS resources. We also show that sandFOX enabled Browser experiences low overhead on loading pages and utilizes negligible memory when running with sandbox environment.

Lisa Bartle - One of the best experts on this subject based on the ideXlab platform.

Anil Saini - One of the best experts on this subject based on the ideXlab platform.

  • sandfox secure sandboxed and isolated environment for Firefox Browser
    Security of Information and Networks, 2015
    Co-Authors: Anil Saini, Manoj Singh Gaur, Vijay Laxmi, Priyadarsi Nanda
    Abstract:

    Browser functionalities can be widely extended by Browser extensions. One of the key features that makes Browser extensions so powerful is that they run with "high" privileges. As a consequence, a vulnerable or malicious extension might expose Browser, and operating system (OS) resources to possible attacks such as privilege escalation, information stealing, and session hijacking. The resources are referred as Browser as well as OS components accessed through Browser extension such as accessing information on the web application, executing arbitrary processes, and even access files from a host file system. This paper presents sandFOX (secure sandbox and iso- lated environment), a client-side Browser policies for constructing sandbox environment. sandFOX allows the Browser extension to express fine-grained OS specific security policies that are enforced at runtime. In particular, our proposed policies provide the protection to OS resources (e.g., host file system, network and processes) from the Browser attacks. We use Security-Enhanced Linux (SELinux) to tune OS and build a sandbox that helps in reducing potential damage from attacks on the OS resources. To show the practicality of sandFOX in a range of settings, we compute the effectiveness of sandFOX for various Browser attacks on OS resources. We also show that sandFOX enabled Browser experiences low overhead on loading pages and utilizes negligible memory when running with sandbox environment.

  • SIN - sandFOX: secure sandboxed and isolated environment for Firefox Browser
    Proceedings of the 8th International Conference on Security of Information and Networks - SIN '15, 2015
    Co-Authors: Anil Saini, Manoj Singh Gaur, Vijay Laxmi, Priyadarsi Nanda
    Abstract:

    Browser functionalities can be widely extended by Browser extensions. One of the key features that makes Browser extensions so powerful is that they run with "high" privileges. As a consequence, a vulnerable or malicious extension might expose Browser, and operating system (OS) resources to possible attacks such as privilege escalation, information stealing, and session hijacking. The resources are referred as Browser as well as OS components accessed through Browser extension such as accessing information on the web application, executing arbitrary processes, and even access files from a host file system. This paper presents sandFOX (secure sandbox and iso- lated environment), a client-side Browser policies for constructing sandbox environment. sandFOX allows the Browser extension to express fine-grained OS specific security policies that are enforced at runtime. In particular, our proposed policies provide the protection to OS resources (e.g., host file system, network and processes) from the Browser attacks. We use Security-Enhanced Linux (SELinux) to tune OS and build a sandbox that helps in reducing potential damage from attacks on the OS resources. To show the practicality of sandFOX in a range of settings, we compute the effectiveness of sandFOX for various Browser attacks on OS resources. We also show that sandFOX enabled Browser experiences low overhead on loading pages and utilizes negligible memory when running with sandbox environment.

Mohammad Zulkernine - One of the best experts on this subject based on the ideXlab platform.

  • analysing vulnerability reproducibility for Firefox Browser
    Conference on Privacy Security and Trust, 2016
    Co-Authors: Maryam Davari, Mohammad Zulkernine
    Abstract:

    Fixing some security failures are difficult because they cannot be easily reproduced. To address Hardly Reproducible Vulnerabilities (HRVs), security experts spend a significant amount of time, effort, and budget. Sometimes they do not succeed in the reproduction step and ignore some security failures. The exploitation of a vulnerability due to its irreproducibility may cause severe consequences. An efficient solution is to explore the behaviour of both hardly and easily reproducible security issues at the code level. We use linear regression techniques to build models based on the classical software complexity metrics and a set of attributes related to the environment of the system. The results show that the considered metrics and the vulnerability types do not have significant linear correlations with each other. Also, predicting the HRV-prone parts of large systems is a great help for security experts to focus their effort on the top-ranked vulnerable files. After identifying the suitable indicators based on linear regression, different machine learning techniques such as Random Forest, Logistic Regression, C4.5 Decision Tree, and Naive Bayes are employed to build HRV prediction models. The Random Forest technique achieves the precision of 82% and recall of 84% to classify vulnerable files into HRV-prone or non HRV-prone files. We believe that the results encourage the use of software metrics for vulnerability prediction in some projects.

  • PST - Analysing vulnerability reproducibility for Firefox Browser
    2016 14th Annual Conference on Privacy Security and Trust (PST), 2016
    Co-Authors: Maryam Davari, Mohammad Zulkernine
    Abstract:

    Fixing some security failures are difficult because they cannot be easily reproduced. To address Hardly Reproducible Vulnerabilities (HRVs), security experts spend a significant amount of time, effort, and budget. Sometimes they do not succeed in the reproduction step and ignore some security failures. The exploitation of a vulnerability due to its irreproducibility may cause severe consequences. An efficient solution is to explore the behaviour of both hardly and easily reproducible security issues at the code level. We use linear regression techniques to build models based on the classical software complexity metrics and a set of attributes related to the environment of the system. The results show that the considered metrics and the vulnerability types do not have significant linear correlations with each other. Also, predicting the HRV-prone parts of large systems is a great help for security experts to focus their effort on the top-ranked vulnerable files. After identifying the suitable indicators based on linear regression, different machine learning techniques such as Random Forest, Logistic Regression, C4.5 Decision Tree, and Naive Bayes are employed to build HRV prediction models. The Random Forest technique achieves the precision of 82% and recall of 84% to classify vulnerable files into HRV-prone or non HRV-prone files. We believe that the results encourage the use of software metrics for vulnerability prediction in some projects.

  • ICECCS - Protecting Web Browser Extensions from JavaScript Injection Attacks
    2013 18th International Conference on Engineering of Complex Computer Systems, 2013
    Co-Authors: Anton Barua, Mohammad Zulkernine, Komminist Weldemariam
    Abstract:

    Vulnerable web Browser extensions can be used by an attacker to steal users' credentials and lure users into leaking sensitive information to unauthorized parties. Current Browser security models and existing JavaScript security solutions are inadequate for preventing JavaScript injection attacks that can exploit such vulnerable extensions. In this paper, we present a runtime protection mechanism based on a code randomization technique coupled with a static analysis technique to protect Browser extensions from JavaScript injection attacks. The protection is enforced at runtime by distinguishing malicious code from the randomized extension code. We implemented our protection mechanism for the Mozilla Firefox Browser and evaluated it on a set of vulnerable and non-vulnerable Firefox extensions. The evaluation results indicate that our approach can be a viable solution for preventing attacks on JavaScript-based Browser extensions. In designing and implementing our approach, we were also able to reduce false positives and achieve maximum backward compatibility with existing extensions.