SirenPod - AI-powered Honeypot for IoT Devices

In the UK the estimate for the economic cost of cyber crime to the Government is £2.2bn per annum. We took information from the National Fraud Authority Annual Fraud Indicator, which estimates the total cost of tax and benefits fraud, local government and central government fraud, NHS fraud and pension fraud. The total cost was combined with an estimate from the NFA on the proportion of fraud that is attributable to 'criminal attacks'. Moreover the economic cost of cyber crime to UK businesses is £21bn per annum.

Within an organization's comprehensive cybersecurity strategy aimed at safeguarding critical assets within their network and facilities, honeypots represent a novel tool for detecting cyberattacks. They prove invaluable in addressing the formidable challenge of identifying zero-day and advanced attacks targeting crucial infrastructure and systems, bolstering other intrusion detection systems in this endeavour. Furthermore, honeypots have the capacity to divert cyber attackers' attention and entice them as a decoy, thus thwarting potential assaults on the genuine network infrastructure.

In this project, we propose the development of the next-generation honeypots, aptly named SirenPod, designed to mimic the behaviour of IoT devices known for their susceptibility to cyberattacks. Consequently, the SirenPod not only possess the capability to detect and analyse such attacks but can also function as a diversion, drawing potential attackers away from high-value energy or medical devices. This proposed advancement incorporates Artificial Intelligence to enhance both the current efficacy of deception during interactions with attackers and the fidelity of system emulation. SirenPod are poised to comprehensively meet the requirements of existing industrial and healthcare IoT equipment, while their adaptable and extensible designs position them for future expansion and capability enhancement.