Organizational Misconduct: Beyond the Principal-Agent Model

This article demonstrates that, at least since the adoption of the Organizational Sentencing Guidelines in 1991, the United States legal regime has been moving away from a system of strict vicarious liability toward a system of duty-based organizational liability. Under this system, organizational liability for agent misconduct is dependant on whether or not the organization has exercised due care to avoid the harm in question, rather than under traditional agency principles of respondeat superior. Courts and agencies typically evaluate the level of care exercised by the organization by inquiring whether the organization had in place internal compliance structures ostensibly designed to detect and discourage such conduct. I argue, however, that any internal compliance-based organizational liability regime is likely to fail because courts and agencies lack sufficient information about the effectiveness of such structures. As a result, an internal compliance-based liability system encourages the implementation of largely cosmetic internal compliance structures that reduce legal liability without reducing the incidence of organizational misconduct. Furthermore, a review of the empirical literature on the effectiveness of internal compliance structures suggests that many organizations have adopted precisely this cosmetic approach to internal compliance. This leads to two potential problems: first, an underdeterrence of organizational misconduct and, second, a proliferation of costly but ineffective internal compliance structures

EXFI: a low cost Fault Injection System for embedded Microprocessor-based Boards

Evaluating the faulty behavior of low-cost embedded microprocessor-based boards is an increasingly important issue, due to their adoption in many safety critical systems. The architecture of a complete Fault Injection environment is proposed, integrating a module for generating a collapsed list of faults, and another for performing their injection and gathering the results. To address this issue, the paper describes a software-implemented Fault Injection approach based on the Trace Exception Mode available in most microprocessors. The authors describe EXFI, a prototypical system implementing the approach, and provide data about some sample benchmark applications. The main advantages of EXFI are the low cost, the good portability, and the high efficienc

Privacy Violation and Detection Using Pattern Mining Techniques

Privacy, its violations and techniques to bypass privacy violation have grabbed the centre-stage of both academia and industry in recent months. Corporations worldwide have become conscious of the implications of privacy violation and its impact on them and to other stakeholders. Moreover, nations across the world are coming out with privacy protecting legislations to prevent data privacy violations. Such legislations however expose organizations to the issues of intentional or unintentional violation of privacy data. A violation by either malicious external hackers or by internal employees can expose the organizations to costly litigations. In this paper, we propose PRIVDAM; a data mining based intelligent architecture of a Privacy Violation Detection and Monitoring system whose purpose is to detect possible privacy violations and to prevent them in the future. Experimental evaluations show that our approach is scalable and robust and that it can detect privacy violations or chances of violations quite accurately. Please contact the author for full text at [email protected]