The Experts below are selected from a list of 297 Experts worldwide ranked by ideXlab platform

John C. S. Lui - One of the best experts on this subject based on the ideXlab platform.

  • Exploiting non-uniform Program Execution Time to evade record/replay forensic analysis
    Computers & Security, 2020
    Co-Authors: Mingshen Sun, John C. S. Lui
    Abstract:

    Abstract Record/replay system is an essential and widely used module in forensic analysis, as it can help forensic analysts to reconstruct Programs’ behaviors. However, the security implication of record/replay systems (i.e., whether record/replay systems can faithfully reproduce all behaviors of a Program) has not been thoroughly studied. This paper is the first work which investigates and explores the security limitations of record/replay systems from the perspective of software forensics. In particular, we reveal a type of vulnerability in record/replay systems caused by non-uniform Program Execution Time. A Program can exploit this vulnerability to prevent its malicious behavior from being replayed. We conduct a series of experiments on three platforms (i.e., web browser, mobile operating system and virtualized sandbox) to illustrate the wide footprints of the vulnerability. Finally, we discuss possible methods to mitigate the vulnerability. The goal of this work is to study the inherent security limitations of record/replay systems, discover the vulnerability and explore potential mitigation methods, from which forensic analysts can be informed and cautious when applying record/replay systems to software forensics.

  • exploiting non uniform Program Execution Time to evade record replay forensic analysis
    Computers & Security, 2020
    Co-Authors: Mingshen Sun, John C. S. Lui
    Abstract:

    Abstract Record/replay system is an essential and widely used module in forensic analysis, as it can help forensic analysts to reconstruct Programs’ behaviors. However, the security implication of record/replay systems (i.e., whether record/replay systems can faithfully reproduce all behaviors of a Program) has not been thoroughly studied. This paper is the first work which investigates and explores the security limitations of record/replay systems from the perspective of software forensics. In particular, we reveal a type of vulnerability in record/replay systems caused by non-uniform Program Execution Time. A Program can exploit this vulnerability to prevent its malicious behavior from being replayed. We conduct a series of experiments on three platforms (i.e., web browser, mobile operating system and virtualized sandbox) to illustrate the wide footprints of the vulnerability. Finally, we discuss possible methods to mitigate the vulnerability. The goal of this work is to study the inherent security limitations of record/replay systems, discover the vulnerability and explore potential mitigation methods, from which forensic analysts can be informed and cautious when applying record/replay systems to software forensics.

Akond Rahman - One of the best experts on this subject based on the ideXlab platform.

  • synthesizing Program Execution Time discrepancies in julia used for scientific software
    International Conference on Software Maintenance, 2019
    Co-Authors: Effat Farhana, Nasif Imtiaz, Akond Rahman
    Abstract:

    Scientific software is defined as software that is used to analyze data to investigate unanswered research questions in the scientific community. Developers use Programming languages such as Julia to build scientific software. When Programming with Julia, developers experience Program Execution Time discrepancy i.e. not obtaining desired Program Execution Time, which hinders them to efficiently complete their tasks. The goal of this paper is to help developers in achieving desired Program Execution Time for Julia by identifying the causes of why Program Execution Time discrepancies happen with an empirical study of Stack Overflow posts. We conduct an empirical study with 263 Julia-related posts collected from Stack Overflow, and apply qualitative analysis on the collected 263 posts. We identify 9 categories of Program Execution Time discrepancies for Julia, which include discrepancies related to data structures usage such as, arrays and dictionaries. We also identify 10 causes that explain why the Program Execution Time discrepancies happen. For example, we identify Program Execution Time discrepancy to happen when developers unnecessarily allocate memory by using array comprehension.

  • ICSME - Synthesizing Program Execution Time Discrepancies in Julia Used for Scientific Software
    2019 IEEE International Conference on Software Maintenance and Evolution (ICSME), 2019
    Co-Authors: Effat Farhana, Nasif Imtiaz, Akond Rahman
    Abstract:

    Scientific software is defined as software that is used to analyze data to investigate unanswered research questions in the scientific community. Developers use Programming languages such as Julia to build scientific software. When Programming with Julia, developers experience Program Execution Time discrepancy i.e. not obtaining desired Program Execution Time, which hinders them to efficiently complete their tasks. The goal of this paper is to help developers in achieving desired Program Execution Time for Julia by identifying the causes of why Program Execution Time discrepancies happen with an empirical study of Stack Overflow posts. We conduct an empirical study with 263 Julia-related posts collected from Stack Overflow, and apply qualitative analysis on the collected 263 posts. We identify 9 categories of Program Execution Time discrepancies for Julia, which include discrepancies related to data structures usage such as, arrays and dictionaries. We also identify 10 causes that explain why the Program Execution Time discrepancies happen. For example, we identify Program Execution Time discrepancy to happen when developers unnecessarily allocate memory by using array comprehension.

Pierluigi Ritrovato - One of the best experts on this subject based on the ideXlab platform.

  • HMM : A static mapping algorithm to map parallel applications on grids
    Lecture Notes in Computer Science, 2006
    Co-Authors: Ranieri Baraglia, Renato Ferrini, Pierluigi Ritrovato
    Abstract:

    In this paper we present a static mapping heuristic, called Heterogeneous Multi-phase Mapping (HMM), which allows a suboptimal mapping of a parallel Program onto a metacomputer to minimize the Program Execution Time. HMM allocates parallel tasks by exploiting the information embedded in the parallelism forms used to implement an application. Moreover, it uses a local search technique together with the tabu search meta-heuristic. The experimental results show that the proposed approach performs well promising a significant potential to develop efficient mapping solutions for metacomputers.

  • PPAM - HMM: a static mapping algorithm to map parallel applications on grids
    Parallel Processing and Applied Mathematics, 2006
    Co-Authors: Ranieri Baraglia, Renato Ferrini, Pierluigi Ritrovato
    Abstract:

    In this paper we present a static mapping heuristic, called Heterogeneous Multi-phase Mapping (HMM), which allows a suboptimal mapping of a parallel Program onto a metacomputer to minimize the Program Execution Time. HMM allocates parallel tasks by exploiting the information embedded in the parallelism forms used to implement an application. Moreover, it uses a local search technique together with the tabu search meta-heuristic. The experimental results show that the proposed approach performs well promising a significant potential to develop efficient mapping solutions for metacomputers.

Jonathan S. Turner - One of the best experts on this subject based on the ideXlab platform.

  • IEEE Real-Time and Embedded Technology and Applications Symposium - Partial Program Admission
    2009 15th IEEE Real-Time and Embedded Technology and Applications Symposium, 2009
    Co-Authors: Michael Wilson, Ron K. Cytron, Jonathan S. Turner
    Abstract:

    Real-Time systems on non-preemptive platforms require a means of bounding the Execution Time of Programs for admission purposes. Worst-Case Execution Time (WCET) is most commonly used to bound Program Execution Time. While bounding a Program’s WCET statically is possible, computing its true WCET is difficult. We present a new technique we call partial Program admission, a means of statically enforcing an otherwise untrusted assertion of WCET without adding runTime overhead, by means of code duplication. We apply this technique to real Programs from the virtual networking arena and present the results.

Manuel V Hermenegildo - One of the best experts on this subject based on the ideXlab platform.

  • using combined static analysis and profiling for logic Program Execution Time estimation
    International Conference on Logic Programming, 2006
    Co-Authors: E Mera, Pedro Lopezgarcia, German Puebla, Manuel Carro, Manuel V Hermenegildo
    Abstract:

    Predicting statically the running Time of Programs has many applications ranging from task scheduling in parallel Execution to proving the ability of a Program to meet strict Time constraints. A starting point in order to attack this problem is to infer the computational complexity of such Programs (or fragments thereof). This is one of the reasons why the development of static analysis techniques for inferring cost-related properties of Programs (usually upper and/or lower bounds of actual costs) has received considerable attention.

  • ICLP - Using combined static analysis and profiling for logic Program Execution Time estimation
    Logic Programming, 2006
    Co-Authors: E Mera, German Puebla, Manuel Carro, Pedro López-garcía, Manuel V Hermenegildo
    Abstract:

    Predicting statically the running Time of Programs has many applications ranging from task scheduling in parallel Execution to proving the ability of a Program to meet strict Time constraints. A starting point in order to attack this problem is to infer the computational complexity of such Programs (or fragments thereof). This is one of the reasons why the development of static analysis techniques for inferring cost-related properties of Programs (usually upper and/or lower bounds of actual costs) has received considerable attention.