Artificial Intelligence-Aided Digital Forensics Examination

调查网络犯罪的人需要筛选的数据池越来越大，越来越复杂，从加密通信和社交媒体互动到存储在物联网设备上的数据。目前用于搜索和分析数字证据的密集和人工方法无法处理日益复杂的数字取证。网络犯罪调查人员必须在相对较短的时间内对大量复杂的数据进行推理和发现。虽然人工智能（AI）可以为数字取证界提供很多东西，但人工智能在数字取证中的应用仍处于非常早期的阶段。

People who investigate cybercrimes have an increasingly large and complex pool of data to sift through, from encrypted communication and social media interactions to data stored on internet of things devices. The current intensive and manual approaches for searching and analyzing digital evidence are not capable of dealing with the increased complexity of digital forensics. Cybercrimes investigators must reason and discover over a large amount of sophisticated data in a relatively short time frame. While artificial intelligence (AI) has a lot to offer to the digital forensics community, AI utilization in digital forensics is still at a very early stage. The long-term goal of my research program is to build an autonomous AI-based system to detect artefacts of interest from all sources of data and analyze them as required. Given the current state of AI-based digital investigation systems, the near-term goal of this program is to build a representation of information into a “smart system” to record, reason about, and exchange information of investigation cases and to detect artefacts of forensics value from complex and uncertain data. The near-term objectives that are pursued in this program are: 1) building a representation of properties of digital evidence suitable for recording, reasoning about, and exchanging information of investigation cases; 2) using AI to automate components of an investigation process such as looking for a particular file, event or log over complex and uncertain datasets; and 3) building AI-based decision-making support systems that suggest the best courses of action in collaborative and mission critical investigation tasks. The research will contribute to the field in the following ways: 1) it will provide a formal and structured representation of knowledge in the digital forensics domain, which is currently limiting information and evidence exchange activities in the field; 2) it will result in creation of fuzzy deep learning AI agents capable of discovering relevant evidence from complex and encrypted data in a timely manner, overcoming limitations of current technology; and 3) it will result in an intuitive multi-criteria fuzzy decision-making support system that is capable of guiding investigators with variety of goals and priorities to take best courses of action. The proposed research will help Canada to establish its leadership in AI and digital forensics and trains at least 8 HQPs who help meet Canada's demand for digital investigators and AI experts. We will create large and re-usable repositories of digital investigation cases which provide a reusable collection of background knowledge for both human and AI agents. Moreover, as most of digital examination cases are collaborative and mission critical tasks, the ability to reason about evidence discovery and analysis process and knowing the best follow-up activities, would assist investigators to make rapid and informed decisions.