Artificial intelligence (AI) and machine learning play an important role in helping law enforcement deal with increasing threats, but the need then for access to data is likely to further drive concerns about privacy.
Closer collaboration between the private and public sectors as well as citizens also would be essential, according to delegates at Interpol World 2017 in Singapore this week.
The rise of urbanisation, globalisation, and online connectivity had unleashed tremendous amount of data that was never before available, Anselm Lopez, director of strategic relations directorate, international cooperation and partnerships division at Singapore's Ministry of Home Affairs. He also is part of Interpol's Asia executive committee.
Lopez noted that data had become a critical element in decision making for law enforcement, as it had for enterprises, and these agencies would have to adapt or be rendered irrelevant.
He said the data could be used and analysed to combat crime and threats, including terrorism, incident response, and cybercrime. Failure to do so efficiently, especially amid the deluge of data available, could lead to law enforcement missing out on critical details and making decisions that were not supported by sound analysis, and possibly leading to loss of lives or losses.
Law enforcement agencies then would need to determine how they could integrate data acquisition and analytics on a daily basis to sharpen risk management, and do so in and around locations during large-scale crisis situations so their internal systems could support decision making.
Adding that there was no cookie-cutter approach, Lopez said systems and methodologies would need to extract data and be able to distinguish innocuous events from real and serious threats. "We must acquire the ability to distill the noise and sharpen our focus," he said.
This further emphasised the importance of partnership between the private sector and law enforcement, which would ensure the necessary capabilities were developed "to fight the new order of threats".
Speed and efficiency, for one, would be crucial. Within hours of the Boston bomb attacks in April 2013, for instance, law enforcement had to process more than 2,300 videos, 9,600 calls, and 5,500 tips from the public. In the more recent Manchester bombing incident, some 30,000 man-hours were spent scrutinising videos for information.
The large volumes of data output today placed an unacceptable level of burden on humans, including law enforcement agencies that had finite resources, said Michael Hershman, group CEO for International Centre for Sport Security (ICSS), who called for tools that could help ease the pressure.
A common thread in security incidents was the difficulties faced by law enforcement and security agencies in identifying acts ahead of time and preventing them, Hershman said. Investigations conducted after such incidents sometimes revealed that information available prior to the event would have at least prompted a closer look at the instigators, but failed to trigger alerts due to the inability to process data in a timely fashion.
While it would be impossible to prevent all acts of violence, he said technology could make a profound impact in helping to prevent a significant number.
ICSS was developing a "data fusion system (DFS)" that aimed to provide a predictive analysis platform to collect, integrate, and analyse data. This would be used to help emergency services and law enforcement agencies predict potential threats and facilitate higher security at events, such as the 2022 Fifa World Cup to be held in Qatar.
The platform, for instance, would be able to use behavioural analytics to assess social media narratives and identify individuals who were being radicalised. Such data could then support operational command centres at event sites and matched against persons identified on-site.
