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Face recognition has greatly matured since the earliest forms, but still improvements must be made before it can be applied in high security or large scale applications. We conducted an experiment in order to estimate percentage of Norwegian people having one or more look-alikes in Norwegian population. The results indicate that the face recognition technology may not be adequate for identity verification in large scale applications. To survey the additional value of a human supervisor, we conducted an experiment where we investigated whether a human guard would detect false acceptances made by a computerized system, and the role of hair in human recognition of faces. The study showed that, on average, the human guard was able to detect almost 80 % of the errors made by the computerized system. More over, the study showed that the ability of human guard to recognize a human face is a function of hair: false acceptance rate was significantly higher for the images where the hair was removed compared to where it was present.

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In this paper, we describe the content and rationale of a comprehensive information security program encompassing degree options at the B.Sc., M.Sc., and Ph.D. levels established at Gjøvik University College, Norway. While the individual programs are open for students meeting certain formal prerequisites at each level, the sequence of degree programs is also designed in such a way as to allow students to progress from B.Sc. to Ph.D. levels without undue overlap or repetition. This is accomplished by placing different emphases on the teaching and learning tools and techniques used, moving on to higher levels in Bloom's hierarchy in the process. At the same time, the different degrees also take into account the career progression and concomitant changes in the needs of students. We describe these considerations along with a brief description of courses offered at each level, along with a description of the learning environments at each level.

The diversity of computing and communication systems used as well as the sheer volume of data processed in all aspects of personal, government, and commercial activities poses considerable challenges to law enforcement and particularly compliance officers. While commercial tools exist for a number of common problems, this is, however, not always sufficient in many more complex cases. Moreover, investigators only familiar with such tools may not be aware of limits in scope and accuracy, potentially resulting in missing evidence or placing unwarranted confidence in it. Moreover, not only is it critical to have an in-depth understanding of the underlying operating principles of the systems that are analyzed, there will also at times be a need to go beyond capabilities of existing tool sets, the enabling knowledge, concepts, and analytical skills for which we argue is currently not offered in a concise higher education context but rather tends to be acquired in an ad-hoc manner. We therefore propose elements of a curriculum for the M.Sc. and particularly the Ph.D. level which provide the necessary rigorous theoretical foundations and perspectives in mathematics, computer science, and engineering combined with a background in forensic sciences which enable both a sound appreciation of existing techniques and the development of new forensic evidence collection and analysis methods. We argue that these abilities are crucial in developing a more rigorous discipline of digital forensics which will both be able to address new challenges posed by evolving information systems and also to satisfy the stringency expected from it given its increasing importance in a broad range of application areas.