The security of online assessments is a major concern due to widespread cheating. One common form of cheating is impersonation, where students invite unauthorized persons to take assessments on their behalf. Several techniques exist to handle impersonation. Some researchers recommend use of integrity policy, but communicating the policy effectively to the students is a challenge. Others propose authentication methods like, password and fingerprint; they offer initial authentication but are vulnerable thereafter. Face recognition offers post-login authentication but necessitates additional hardware. Keystroke Dynamics (KD) has been used to provide post-login authentication without any additional hardware, but its use is limited to subjective assessment. In this work, we address impersonation in assessments with Multiple Choice Questions (MCQ). Our approach combines two key strategies: reinforcement of integrity policy for prevention, and keystroke-based random authentication for detection of impersonation. To the best of our knowledge, it is the first attempt to use keystroke dynamics for post-login authentication in the context of MCQ. We improve an online quiz tool for the data collection suited to our needs and use feature engineering to address the challenge of high-dimensional keystroke datasets. Using machine learning classifiers, we identify the best-performing model for authenticating the students. The results indicate that the highest accuracy (83%) is achieved by the Isolation Forest classifier. Furthermore, to validate the results, the approach is applied to Carnegie Mellon University (CMU) benchmark dataset, thereby achieving an improved accuracy of 94%. Though we also used mouse dynamics for authentication, but its subpar performance leads us to not consider it for our approach.
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Local Gabor features (jets) have been widely used in face recognition systems. Once the sets of jets have been extracted from the two faces to be compared, a proper measure of similarity (or distance) between corresponding features should be chosen. For instance, in the well known Elastic Bunch Graph Matching (EBGM) approach and other Gabor-based face recognition systems, the cosine distance was used as a measure. In this paper, we provide an empirical evaluation of seven distance measures for comparison, using a recently introduced face recognition system, based on Shape Driven Gabor Jets (SDGJ). Moreover we evaluate different normalization factors that are used to pre-process the jets. Experimental results on the BANCA database suggest that the concrete type of normalization applied to jets is a critical factor, and that some combinations of normalization + distance achieve better performance than the classical cosine measure for jet comparison.
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This paper proposes an epistemological transition based on Edgar Morin's complexity paradigm to analyse authenticity in a complex tourism environment, avoiding fragmentation, and integrating relevant actors and relationships. The results show that storytelling is an important element of these tourism experiences, legitimising and unifying the authenticity of the experience and relating objects, social environment and individual experiences. The size of the tour groups and the rigidity of the itinerary were important elements for constructing authenticity. Tourists, service providers and government bodies all directly or indirectly participate as co-creators, making the perception of authenticity a constant negotiation between the elements of the experience and the actors involved in it.
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The increasing complexity of digital networks on which society depends on renders these networks increasingly vulnerable to attacks. Focusing on physical layer security, we propose to develop single-spatial-mode optical Physical Unclonable Functions (PUFs) as an authentication solution for quantum and classical communication links. These novel PUFs are read out through standard optical fibers or free-space links. Several implementations of single-mode PUFs are proposed exploiting the time / frequency domain for the encoding challenge / response space. Together with the PUFs, we will develop tools to generate challenge-forming few-photon light pulses and to validate PUF responses at the few-photon level and take specific steps toward wide implementation.
