192,766 research outputs found
HAND GESTURE IDENTIFICATION ON SAFETY BOX SECURITY SYSTEM USING FUZZY C-MEANS METHOD
Security system technology has been growing so rapidly.
Ranging from conventional to modern security systems such as
biometric identification systems already poluler in our society. One
more unique system and relatively new in the IT world is a system of
hand signs of identification. This system has been used and developed
for gaming purposes, but over time these systems will be increasingly
popular to control other electronic equipment such as electronic safing
box.
The method used in this thesis is the Fuzzy C-Means. FCM data
processing are integral to the projection of each pattern is determined
and produced new centroids as the identity of the pattern. FCM
processing using Matlab 7.1 software while the centroid proximity to
count FCM results in a pattern that caught our webcam using euclidean
distance.
Testing the system using a Celeron 550 processor, 2.0 GHz and
logitech webcam 5500. The system is able to work with accuracy rate of
more than 88.67% in a room with sufficient light intensity. Maximum
distance is achieved for the detection of skin color is 70 cm with an
average speed of detection is 15.159 fps.
Key words: skin detection, hand gesture, integral projections, fuzzy c-
means, euclidean distance, matlab 7.1, VB 6.0
Survey and Systematization of Secure Device Pairing
Secure Device Pairing (SDP) schemes have been developed to facilitate secure
communications among smart devices, both personal mobile devices and Internet
of Things (IoT) devices. Comparison and assessment of SDP schemes is
troublesome, because each scheme makes different assumptions about out-of-band
channels and adversary models, and are driven by their particular use-cases. A
conceptual model that facilitates meaningful comparison among SDP schemes is
missing. We provide such a model. In this article, we survey and analyze a wide
range of SDP schemes that are described in the literature, including a number
that have been adopted as standards. A system model and consistent terminology
for SDP schemes are built on the foundation of this survey, which are then used
to classify existing SDP schemes into a taxonomy that, for the first time,
enables their meaningful comparison and analysis.The existing SDP schemes are
analyzed using this model, revealing common systemic security weaknesses among
the surveyed SDP schemes that should become priority areas for future SDP
research, such as improving the integration of privacy requirements into the
design of SDP schemes. Our results allow SDP scheme designers to create schemes
that are more easily comparable with one another, and to assist the prevention
of persisting the weaknesses common to the current generation of SDP schemes.Comment: 34 pages, 5 figures, 3 tables, accepted at IEEE Communications
Surveys & Tutorials 2017 (Volume: PP, Issue: 99
Benefits of Location-Based Access Control:A Literature Study
Location-based access control (LBAC) has been suggested as a means to improve IT security. By 'grounding' users and systems to a particular location, \ud
attackers supposedly have more difficulty in compromising a system. However, the motivation behind LBAC and its potential benefits have not been investigated thoroughly. To this end, we perform a structured literature review, and examine the goals that LBAC can potentially fulfill, \ud
the specific LBAC systems that realize these goals and the context on which LBAC depends. Our paper has four main contributions:\ud
first we propose a theoretical framework for LBAC evaluation, based on goals, systems and context. Second, we formulate and apply criteria for evaluating the usefulness of an LBAC system. Third, we identify four usage scenarios for LBAC: open areas and systems, hospitals, enterprises, and finally data centers and military facilities. Fourth, we propose directions for future research:\ud
(i) assessing the tradeoffs between location-based, physical and logical access control, (ii) improving the transparency of LBAC decision making, and \ud
(iii) formulating design criteria for facilities and working environments for optimal LBAC usage
Towards automated visual surveillance using gait for identity recognition and tracking across multiple non-intersecting cameras
Despite the fact that personal privacy has become a major concern, surveillance technology is now becoming ubiquitous in modern society. This is mainly due to the increasing number of crimes as well as the essential necessity to provide secure and safer environment. Recent research studies have confirmed now the possibility of recognizing people by the way they walk i.e. gait. The aim of this research study is to investigate the use of gait for people detection as well as identification across different cameras. We present a new approach for people tracking and identification between different non-intersecting un-calibrated stationary cameras based on gait analysis. A vision-based markerless extraction method is being deployed for the derivation of gait kinematics as well as anthropometric measurements in order to produce a gait signature. The novelty of our approach is motivated by the recent research in biometrics and forensic analysis using gait. The experimental results affirmed the robustness of our approach to successfully detect walking people as well as its potency to extract gait features for different camera viewpoints achieving an identity recognition rate of 73.6 % processed for 2270 video sequences. Furthermore, experimental results confirmed the potential of the proposed method for identity tracking in real surveillance systems to recognize walking individuals across different views with an average recognition rate of 92.5 % for cross-camera matching for two different non-overlapping views.<br/
Potential mass surveillance and privacy violations in proximity-based social applications
Proximity-based social applications let users interact with people that are
currently close to them, by revealing some information about their preferences
and whereabouts. This information is acquired through passive geo-localisation
and used to build a sense of serendipitous discovery of people, places and
interests. Unfortunately, while this class of applications opens different
interactions possibilities for people in urban settings, obtaining access to
certain identity information could lead a possible privacy attacker to identify
and follow a user in their movements in a specific period of time. The same
information shared through the platform could also help an attacker to link the
victim's online profiles to physical identities. We analyse a set of popular
dating application that shares users relative distances within a certain radius
and show how, by using the information shared on these platforms, it is
possible to formalise a multilateration attack, able to identify the user
actual position. The same attack can also be used to follow a user in all their
movements within a certain period of time, therefore identifying their habits
and Points of Interest across the city. Furthermore we introduce a social
attack which uses common Facebook likes to profile a person and finally
identify their real identity
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