Transnational serious and organised crime (TSOC) costs the Australian economy approximately AUD $60 billion, and cybercrime against children, such as child exploitation and child sexual abuse material (CSAM), is rapidly outpacing law enforcement's ability to address the problem. In a move towards combating these issues, cybercrime researchers at the University of Adelaide and San Jose State University, in collaboration with Oracle, have developed an innovative platform that aims to reprieve these criminal activities.

The world-first Biometric Analyser and Network Extractor (BANE) platform intends to aid law enforcement by automating and cataloguing digital evidence such as pictures, videos, digital communications, posts, and other content. BANE will facilitate the rapid identification of offenders and victims, along with the exploration of their connections. It will be hosted on the Oracle Autonomous Database, which provides scalability and security, enabling the BANE platform to process hundreds of thousands of files and alleviating investigators' workloads and mental strain.

Bryce Westlake, associate professor in the Department of Justice Studies at San Jose State University, rightly pointed out the pressure law enforcement agencies face due to the bolstering amount of data in their ambit. "If investigators seize a computer or a couple of iPads, some phones, and a dozen USB sticks, they may have 500,000 files or more that they need to analyse," he said. According to Westlake, BANE will equip law enforcement agencies to consolidate and automate data review, thereby expediting investigations compared to manual methods.

Traditional methods of seizing, cataloguing, analysing, and storing CSAM at scale have proven laborious, time-consuming, and psychologically detrimental to investigators. With the BANE platform, investigators can process thousands of hours of sensitive content in a few hours, allowing investigations to progress rapidly and efficiently while alleviating the mental load on investigators.

Russell Brewer, associate professor of Criminology at the University of Adelaide, further emphasised the positive impact of BANE on investigations. "This technology has the potential to prevent kids from harm by allowing police to do more and undertake investigations at scale, not only more rapidly but also more effectively," he said. Brewer added that the comprehensive gathering of data across jurisdictions globally would enable more effective identification of offenders and victims.

The Oracle Autonomous Database, known for its automated management and the scalability and performance of OCI, employs a data pipeline utilising AI and machine learning to scan digital evidence. This may include videos, emails, or bank transactions to extract and match similarities in data. The matched data then get stored in a database for subsequent review by investigators, enhancing the process of drawing new links between offenders and victims. This can substantially improve investigatory outcomes, such as safeguarding a child or arresting an offender more swiftly.

While BANE was designed primarily to assist in child exploitation and protection cases, the researchers aim to collect, catalogue, and analyse different forms of criminal data and evidence for predictive intelligence across law enforcement domains. This model can further extend its application to the private sector, including banking and finance or supply chain security. Through controlled testing with law enforcement agencies, the project has demonstrated how the Autonomous Database on OCI can optimise faster, cost-efficient workflows to combat cybercrime effectively.