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Ismail Shakra

dblp:21/449 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Biometric security · 77% Authentication and access control · 23%
Human-computer interaction and pervasive computing
1 paper
Haptics and multimodal interaction · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Haptics and multimodal interaction
haptic interaction
0.112005
Haptic: the new biometrics-embedded media to recognizing and quantifying human patterns · ACM Multimedia 2005
Biometric security
behavioral biometrics
0.112005
Haptic: the new biometrics-embedded media to recognizing and quantifying human patterns · ACM Multimedia 2005
Authentication and access control
user authentication
0.012005
Haptic: the new biometrics-embedded media to recognizing and quantifying human patterns · ACM Multimedia 2005

Methods — techniques the papers use, named apart from their topics

haptic-based behavioral pattern analysis · 0.1
YearPublicationVenuePosition
2005 Haptic: the new biometrics-embedded media to recognizing and quantifying human patterns
abstract
Authentication for the purposes of security has taken giant strides since the introduction of Biometrics to help identify people by their behavioral and physiological features. From organizations and corporations to educational institutes, electronic resources, and even crime scenes, Biometrics offers a wide application scope to detect fraud attempts. This paper proposes a research path to achieve the task of authenticating users that are working in a haptic-based environment. The field of Biometrics can be divided into two main classes of human features. Birth-given characteristics like fingerprints and facial features cannot be developed or altered by humans. Behavioral characteristics such as hand signature and voice fall into the second class [1]. The work presented in this paper pursues the latter class and specifically studies how a person reacts to using daily devices or tools. The fact that we can exploit people's habits in handling devices to detect identity was the hypothesis that motivated this work.
Mauricio Orozco Trujillo, Ismail Shakra, Abdulmotaleb El Saddik
ACM Multimedia2