Amr el Rahwan
Amr is experienced in supporting international organizations, border security, and police in solving issues related to physical security and public safety by studying the security gaps in the information systems, building capacities, applying standards & regulations and converting them into technologies, providing feasibility studies & roadmaps, and providing exceptional global solutions for preventing, detecting, and investigating terrorism & serious crime.
He has unique experience in domain-specific Artificial Intelligence and applying the new EU regulations & the "Universal Message Format" UMF standard to achieve interoperability between the Member States and EU information systems for law enforcement such as CIR, ECRIS-TCN, EES, ESP, ETIAS, EURODAC, MID, sBMS, SIS, & VIS, in the field of borders, visa, police and judicial cooperation, asylum, and migration. He is one of those particular and rare profiles capable of establishing links between the operational and technological side, the legal aspects, and a fine knowledge of the Forensic environment.
He holds two research papers about Artificial Intelligence and Interoperability selected and published by FRONTEX and CEPOL.
Amr is based in the Netherlands and studying MSc in Cybersecurity at the International Hellenic University. Affiliated Member of "Secure Identity Alliance" for Interoperability for Law Enforcement & Border Security, and was a former Police Officer Engineer in Egypt.
● Design and integration of Information Systems for Public Safety & Law Enforcement, Biographic Systems, Biometrics (Fingerprint, Facial Recognition, & Iris), Digital Identity Management (E-ID, E-Passport), Borders Security, including Passenger Information API & PNR Systems.
● OSINT “Open Source Intelligence” & Cybersecurity Lecturer at Egyptian Police Communications Institute, Egyptian Police Information Systems Institute, and Egyptian Police Forensics Science Institute.
● Regular Speaker as an International Expert at OSCE (Organization for Security & Co-operation in Europe) Conferences & Workshops to help countries establish Advance Passenger Information (API) Systems.
● Invited Speaker about using Artificial Intelligence and interoperability in the field of law enforcement and border security at CEPOL, eu-LISA, and FRONTEX conferences.
● CEPOL external expert for Interoperability, EES, ETIAS, PNR, OSINT, and AI “Artificial Intelligence”.
● FRONTEX selected his research paper on "ARTIFICIAL INTELLIGENCE AND UMF STANDARD FOR INTEROPERABILITY IN THE FIELD OF BORDERS AND POLICE".
● CEPOL selected his research paper on "ARTIFICIAL INTELLIGENCE AND INTEROPERABILITY FOR SOLVING CHALLENGES OF OSINT AND CROSS-BORDER INVESTIGATIONS".
Sessions
The major investigation challenges are summarized as multiple-identity, fraudulent actions, lack of interoperability, and absence of an effective technical solution for exchanging Cross-Border information.
The EU published Regulations (EU) 2019/817 and 2019/818 for establishing a framework for EU interoperability between information systems in the field of borders and visa information systems, police and judicial cooperation, asylum, and migration. Existing systems such as EURODAC, SIS / SISII, and VIS must share data, and new systems such as ECRIS-TCN, EES, and ETIAS also need to follow these guidelines. The EU interoperability components include the European Search Portal (ESP), in addition to Europol and Interpol data; the Shared Biometric Matching Service (sBMS); the Common Identity Repository (CIR), and the Multiple Identity Detector (MID). Although the eu-LISA will implement the interoperability framework in 2023, new challenges will emerge, such as investigating multiple-identity and identity frauds due to the different formats and structures of data, low quality of biographic and biometric data, and low accuracy of matching algorithms.
Furthermore, the recent global threats such as the increase of illegal immigration, the high risks of terrorism and serious crime, the COVID-19 pandemic, and the war between Russia and Ukraine created the essential need for exchanging Cross-Border information for preventing, detecting, and investigating terrorism and serious crime across Europe and the neighboring countries.
Finally, the Open Source Intelligence (OSINT) investigation process is not automated, consumes a lot of time, and is overwhelming. When the border security and the law enforcement officers use methods of OSINT to investigate terrorism and serious crime, it is very difficult to match and link the identity-related data and facial images of the suspects stored in the EU systems, Cross-Border systems, and open sources.
The paper argues different Artificial Intelligence (AI) methods and algorithms and interoperability could be the optimum solution for the challenges mentioned above. The paper highlights a Person-Centric approach using Artificial Intelligence and interoperability to solve the challenges that emerge during investigations, such as multiple-identity, identity frauds, the complexity of OSINT investigations, and exchanging Cross-Border information.