Predictive biometrics: A review and analysis of predicting personal characteristics from biometric data

Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, `higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future

Digital Transformation - IoT is a Metaphor

Digital Transformation is a convergence of multiple tools, technologies and ideas. A few of these elements are discussed in "IoT is a Metaphor" (PDF).Digital Economics is approaching and the "new economy" will need new rules, new changes and new thinking. Digital Transformation is a step toward Digital Economy. In this article, we haven't even scratched the surface of the imminent digital tsunami. Infrastructure and innovation must converge with tools and technologies, where systems must connect and communicate to meet the customer at the point of consumption. This will be an immense change which will turn paradoxes to paradigms. Please scroll down to download the pdf "IoT is a Metaphor

Developing resilient cyber-physical systems: A review of state-of-the-art malware detection approaches, gaps, and future directions

Cyber-physical systems (CPSes) are rapidly evolving in critical infrastructure (CI) domains such as smart grid, healthcare, the military, and telecommunication. These systems are continually threatened by malicious software (malware) attacks by adversaries due to their improvised tactics and attack methods. A minor configuration change in a CPS through malware has devastating effects, which the world has seen in Stuxnet, BlackEnergy, Industroyer, and Triton. This paper is a comprehensive review of malware analysis practices currently being used and their limitations and efficacy in securing CPSes. Using well-known real-world incidents, we have covered the significant impacts when a CPS is compromised. In particular, we have prepared exhaustive hypothetical scenarios to discuss the implications of false positives on CPSes. To improve the security of critical systems, we believe that nature-inspired metaheuristic algorithms can effectively counter the overwhelming malware threats geared toward CPSes. However, our detailed review shows that these algorithms have not been adapted to their full potential to counter malicious software. Finally, the gaps identified through this research have led us to propose future research directions using nature-inspired algorithms that would help in bringing optimization by reducing false positives, thereby increasing the security of such systems

Pengecaman peristiwa jatuh secara tiba-tiba menggunakan fitur gerakan dan pengelas ilhaman biologi sistem penglihatan

Kajian tentang pengecaman peristiwa yang berlaku secara tiba-tiba untuk sistem video pengawasan dikenal pasti boleh menyumbang ke arah pengurangan kos pembangunan teknologi sistem peranti pengesan bolehpakai dan juga ketidakselesaan pemakainya. Adalah dijangkakan, populasi penduduk dunia akan bertambah pada masa akan datang ekoran peningkatan jangka hayat manusia yang menyebabkan peningkatan bilangan penduduk dunia berumur 60 tahun ke atas. Oleh itu, sistem penjagaan keselamatan penghuni dalam rumah tak invasif yang boleh berfungsi untuk mengawas dan mengesan sebarang kejadian kemalangan yang tidak diingini seperti rebah, pengsan dan lain-lain akan menjadi penting dan berguna untuk warga tua khususnya untuk mereka yang tinggal bersendirian. Perkembangan dalam sistem pengecaman peristiwa yang berlaku secara tiba-tiba dijangkakan dapat menyediakan kemudahan kepada warga tua yang tinggal bersendirian di samping berupaya menjaga keselamatan mereka di rumah. Ini akan dapat mengurangkan kos perbelanjaan di pusat jagaan warga tua. Justeru, objektif utama kajian adalah untuk membangunkan satu kaedah mengesan gerakan dan mengecam peristiwa yang berlaku secara tiba-tiba dan memerlukan tindakan serta perhatian segera. Perlaksanaan pembangunan kaedah pengecaman kejadian melibatkan tiga langkah penting iaitu, pemprosesan awal, penyarian fitur dan pengelasan. Pemprosesan awal menggunakan teknik penolakan latar belakang (PLB) dan teknik pelicinan, (penuras kebarangkalian ruang, SPF dan sokongan data kejiranan, NDS) untuk mengurangkan hingar imej bebayang objek. Sifat gerakan telah dikenalpasti sebagai salah satu sifat yang penting dan relevan bagi mengesan perubahan mendadak pada orientasi, arah dan penampilan objek dalam sesebuah jujukan video. Terdapat tiga kaedah sarian fitur gerakan yang berasaskan ruang-masa iaitu templat, aliran vektor gerakan (AVG) dan ilhaman biologi sistem penglihatan manusia telah dilaksanakan. Seterusnya, keberkesanan fitur gerakan diuji dengan menggunakan tiga pengelas sedia ada iaitu k-kejiranan terdekat (k-NN), mesin vektor sokongan (SVM) dan rangkaian neural inspirasi biologi suap hadapan (BFFNN-P). Potensi pengelas BFFNN-P untuk mengelas peristiwa jatuh berbanding dengan aktiviti harian yang lain ditingkatkan melalui kaedah kawalan ralat berkadar (P), kamiran (I) dan terbitan (D). Hasil kajian yang diperolehi menunjukkan teknik SPF telah memberikan keputusan yang baik dalam mengurangkan hingar dan melicinkan imej bebayang objek. Fitur gerakan GaussH yang berasaskan inspirasi sistem penglihatan manusia telah memberikan keputusan yang lebih baik berbanding templat dan AVG dengan menggunakan pengelas BFFNN-PD. Prestasi kejituan, kepekaan dan kepekaan bagi fitur gerakan GaussH dengan pengelas BFFNN-PD adalah 98.6%, 98.2% dan 99.5%. Kesimpulannya, penyelidikan ini telah berjaya menghasilkan kaedah pengelasan melalui pendekatan inspirasi biologi yang mampu mengesan peristiwa yang berlaku secara tiba-tiba