Public Safety and Trust Based Systems

该项目将以新颖和有效的方式应用计算机科学和数据科学来解决萨斯喀彻温省惩教、治安和公共安全部(“该部”)管理的公共安全问题。该部的核心活动是监督萨斯喀彻温省的惩教系统和设施，并向萨斯喀彻温省的市政警察部门提供指导和支持。具体地说，该项目的目标是(A)通过提高记录囚犯电话的速度和降低成本来改善对囚犯电话系统(“Telmate”)的监测，(B)通过检测异常使用模式来改善对同一系统的监测，以及(C)评估计算机化代理人的可信性。除了研究结果本身，潜在的结果是该部的新政策和程序。例如：(A)更方便的电话记录可能允许安全情报官员通过分配更多时间分析而不是更少时间来改变他们分析安全威胁的程序，(B)对电话呼叫日志数据的详细分析可能导致影响囚犯呼叫的允许频率、持续时间和次数的政策，以及(C)对自动化系统信任的更好理解可能有助于未来制定针对自动化车辆的新政策。主要的好处将是在与萨斯喀彻温省公共安全有关的几项倡议中协助该部。该项目旨在通过检测非法行为、促进对机密数据的分析以及减少自动化系统的错误来提高公共和囚犯的安全。它还将为计算机科学、数据科学、软件设计、数据挖掘、数据库访问、语音识别、基于信任的协议、机器学习、深度学习、时间序列和处理私人信息方面的高素质人员提供培训。

This project will apply computer science and data science in novel and effective ways to address public safety problems managed by the Saskatchewan Ministry of Corrections, Policing, and Public Safety ("the Ministry"). The core activity of the Ministry is to oversee Saskatchewan's correctional system and facilities, and to provide guidance and support to Saskatchewan's municipal police services. Specifically, the goals of this project are to (A) improve monitoring of the inmate telephone system ("Telmate") by increasing the speed and decreasing the cost of transcribing inmate calls, (B) improve the monitoring of the same system by detecting anomalous patterns of usage, and (C) estimating the trustworthiness of computerized agents. The potential outcomes, besides the research results themselves, are new policies and procedures for the Ministry. As examples: (A) more convenient transcription of telephone calls may allow security intelligence officers to change their procedures for analyzing security threats by allocating more time to analysis and less to listening, (B) detailed analysis of telephone call log data may lead to policies affecting the permissible frequency, duration, and times of inmate calls, and (C) improved understanding of trust in automated systems may contribute to the future formulation of new policies for automated vehicles. The primary benefit will be to aid the Ministry in several initiatives related to public safety in Saskatchewan. The project is intended to increase public and inmate safety by detecting illegal behaviours, facilitating the analysis of confidential data, and reducing the errors made by automated systems. It will also provide training for highly qualified personnel in computer science, data science, software design, data mining, database access, speech recognition, trust-based protocols, machine learning, deep learning, time series, and handling private information.