Detecting Advanced Drone Smuggling Techniques

𝗧𝗵𝗲 𝗧𝗵𝗿𝗲𝗮𝘁 𝗼𝗳 𝗛𝗼𝘀𝘁𝗶𝗹𝗲 𝗥𝗲𝗰𝗼𝗻𝗻𝗮𝗶𝘀𝘀𝗮𝗻𝗰𝗲: 𝗗𝗿𝗼𝗻𝗲𝘀 𝗮𝗻𝗱 𝗖𝗼𝘃𝗲𝗿𝘁 𝗧𝗼𝗼𝗹𝘀 Recent revelations from a BBC report (https://lnkd.in/esj8k_5S) uncovered a vast arsenal of surveillance tools, including 11 drones, IMSI grabbers, and over 500 SIM cards, used for hostile reconnaissance. This raises urgent questions: How much activity has already gone undetected, or continues to go unnoticed, and why are authorities not acting on reported concerns? Drones are increasingly exploited for silent surveillance, bypassing physical security and collecting critical data with high-definition cameras and advanced sensors. Combined with tools like IMSI grabbers, attackers can exploit many vulnerabilities to gather sensitive intelligence with minimal risk. 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 Despite advancements in Counter-Uncrewed Aircraft Systems (CUAS), many organisations still lack effective measures to understand, detect and mitigate drone activity. Our own detection systems have uncovered highly concerning activities resembling reconnaissance, which have been reported to authorities. Yet, the unquestionable lack of decisive action or investigation leaves critical and commercial infrastructure vulnerable. 𝗦𝘁𝗿𝗲𝗻𝗴𝘁𝗵𝗲𝗻𝗶𝗻𝗴 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗠𝗶𝘁𝗶𝗴𝗮𝘁𝗶𝗼𝗻 To address this evolving threat, organisations must adopt a multi-layered approach: 1. 𝗧𝗵𝗿𝗲𝗮𝘁 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀: Understanding the intent and behaviour of potential adversaries is critical. Regular vulnerability assessments, including "red team" exercises, can simulate drone-based reconnaissance and uncover weak points. 2. 𝗘𝗮𝗿𝗹𝘆 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻: Implementing CUAS solutions capable of detecting, tracking, and identifying drones is essential. These systems must also integrate with broader surveillance tools to provide a complete security and common operating picture. 3. 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗔𝘄𝗮𝗿𝗲𝗻𝗲𝘀𝘀: Staff training on identifying and responding to drone activity is vital. Often, early detection by personnel can mitigate potential risks. 𝗧𝗵𝗲 𝗦𝘁𝗮𝗸𝗲𝘀 𝗔𝗿𝗲 𝗛𝗶𝗴𝗵 The tools identified in the BBC report highlight how advanced technology is being misused for hostile purposes. The growing sophistication of these devices, combined with their easy accessibility, means that security professionals cannot afford to overlook the risks. As security practitioners, policymakers, and technology providers, we must work together to close the detection gap and build resilience against drone-based threats. By investing in advanced CUAS technology and fostering a culture of proactive security, we can protect against future incidents of hostile reconnaissance. Have you reviewed your organisation’s readiness to detect and counter drones? Let’s start a conversation on how we can collectively address this critical issue.

Stealthy detection of UAS via passive RF sensing. What if you could detect drones using RF passive sensing without relying on radar, ISAC or similar methods? No RF illuminator needed. Using ELF signatures emitted from spinning rare-earth magnets in the UAS motors we can not only detect, but also identify the type of drone via neurosymbolic AI methods. See our latest paper in IEEE Sensors. This work is in collaboration with the University of Ruhuna, and the Brookhaven Nation Labs NY. Coauthors include Chatura Wickrema Seneviratne Soumyajit Mandal Nimasha Hiruni Silva Supun Ganegoda Sudeepa Ranasinghe Dilshara Herath Early accepted paper is attached.

Finding drones using intercepted telemetry Telemetry is often the most direct and informative source of positional truth about a remotely piloted aircraft. It originates from the platform itself and typically contains precise latitude, longitude, altitude, attitude, speed and system state. These reports can be transmitted unencrypted over conventional radio links, SATCOM, commercial cellular networks (LTE/5G), or airborne relays, and may be intercepted or analysed wherever they traverse a network. Even when operating in GNSS-denied environments, many UAVs continue to generate accurate position information. By fusing inertial navigation with GNSS, they maintain consistent coordinates long after satellite signals are degraded or unavailable. Each telemetry transmission can be correlated to reconstruct the aircraft’s movement and intent. Intercepted telemetry should be regarded as a valued source of information for determining a drone’s location and movement. It represents the aircraft’s own internal assessment of where it is, and—until proven otherwise—provides a reliable basis for situational understanding and operational decision-making. Melrose Networks melrosenetworks.com #counterUAS #telemetry #airspacedefence #signalsintelligence #dronedetection #airsecurity

Saturday Sound detection From social media: : Ukraine Reportedly Develops Acoustic Detector for FPV Drones — Ukrainian company Zvook has introduced a new tactical acoustic sensor, the Zvook NW0, designed to detect enemy FPV drones by analyzing the sound of their flight. The system reportedly focuses on fiber-optic FPV drones, which cannot be detected by conventional electronic reconnaissance or jamming systems. According to the developer, the sensor uses artificial intelligence to continuously analyze the surrounding acoustic environment. It reportedly provides a detection range of 150 to 450 meters with 360-degree coverage. Once a drone is identified, it can activate an audible warning and reportedly transmit detection data to the ZVOOK user interface, displaying targets on an interactive real-time map. To operate, the sensor reportedly requires a constant power supply and data link. Depending on configuration, connectivity is reportedly possible via fiber optics, twisted-pair cables, LTE, or LoRa, while power consumption is reportedly 15–20 watts. ZVOOK states that such sensors allow building a dense, networked early warning system to protect frontline positions, cities near the contact line, and key logistics routes. For reliable coverage, sensors are reportedly recommended every 400–600 meters, creating overlapping detection zones. The company is best known for its broader Zvook acoustic detection system, praised by Western militaries. This system reportedly uses a network of microphones to record ambient sounds, which software analyzes to isolate signatures of drones, helicopters, aircraft, and cruise missiles. According to The Times, it is capable of detecting drones up to 5 km and cruise missiles up to 7 km. While these ranges are lower than radar, the sensors are reportedly cheaper and hard to detect. Each station reportedly costs around $500, enabling wide deployment. The microphones are reportedly powered by rechargeable batteries and solar panels, with data reportedly transmitted via satellite communications. Source: Militarnyi / Photos: ZVOOK