Citizen-centric privacy requirements engineering framework / Nor Asiakin Hasbullah

The transformation government (t-government) or Government 2.0 was initiated by the UK in 2006 to enhance and restructure the flaws in e-government with three characteristic themes of citizen-centric in (i) service delivery; (ii) shared services culture and (iii) professionalism. The aim of t-government is to transform public services for the benefit of citizens, businesses, taxpayers and frontline staff. The tgovernment requires a citizen centric perspective that takes into account of the citizens’ needs and concern contrary to the traditional approach where systems designers view the citizens’ needs from the perspective of the government and ignoring the citizens’ perspectives due to constraints of cost. One concern of citizen centricity revolves around the issue of trust in e-government in upholding citizen’s privacy. The effectiveness of t-government that uphold citizens’ rights to privacy is enshrined in the delivery process, and that citizens’ views and perceptions of privacy contribute to informing that process. Currently, the citizencentric perspective of privacy requirement is not well understood. To fill this gap, this research undertook a study with the objectives of (i) To investigate the availability and the content of privacy policy in e-government websites (ii) To investigate citizen’s privacy perception through their privacy concern and willingness to participate in public opinion platform (iii) To investigate citizen’s privacy requirement’s and need through their privacy preferences (iv) To propose citizencentric privacy requirements engineering framework by facilitating citizen engagement in fulfilling citizen privacy requirements. A multistakeholder perspective inquiry of citizens’ privacy concern though survey on citizens’ perception of personal and sensitive information among the common citizens and a focus group interview with a group of participatory citizens from the professionals was conducted. From the data analysis, two important results were obtained. The first is the citizen-centric preference set based on the information classification of personal and sensitive information and the second is the sensitivity scale of privacy related information. These two results are configured into a reference table and sensitivity classification tools respectively and integrated in a citizen-centric privacy requirements engineering framework which was verified by a group of experts. The framework can be applied to determine citizen centric privacy preference in the requirements of t-government engineering process and the tool could be use as classifying method to classify sensitive and personal information for system design

Investigating the Privacy Policy Adoption among Malaysia E-Government Websites: Towards Conceptualizing the E-Privacy Assessment Framework

Malaysia E-government had improved the government services and overcome barriers faced by the public in the offline environment. The government initiatives to safeguard the interest of the public had transcended to include privacy protection. The Personal Data Protection Act 2009 is considered as  one of the initiatives that had been  successfully  passed by  the  Malaysia Government  by April 2010. However, the implementation and governance of the Act is still subjected to minister’s  decision. This study  aims in parallel with the government initiatives by investigating the  adoption of  privacy policy  among the  Malaysia's  egovernment  websites. This study is importance towards examining the  current  level of awareness for the importance for privacy protection being provided for the  public,  before the full  enforcement of the  Act. Samples of 154 websites were selected by using convenient sampling from Malaysia government portal (http://www.malaysia.gov.my), which comprises  of federal and state governments. The evaluation process was done by using personal observation through an adopted indicators of privacy policies from Jamal Maier and Sunder in 2002 by observing the links provided for 'privacy policy statements', 'privacy policy notice' and 'privacy policy'. The study revealed several issues pertaining privacy policy adoption among Malaysia e-government site and highlights few recommendations and future works towards conceptualization of e-privacy assessment framework in Malaysia e-government context

Initial Investigation on Privacy Preferences: A Preliminary Study on User Priority, Concern, Perception and Expectation

This paper reports on the findings of an initial study on the user’s preference towards their own privacy. The study is important in having user’s opinion especially when dealing with security of their privacy. It is vital to know what the most important priorities are when dealing with privacy as this could lead to the requirements that the user expected when using a website. In addition, this study tried to gather information of user perceptions on privacy and the expectations that they have when dealing with organizations through a survey by using questionnaires. Results showed that Malaysians does have privacy concerns when dealing with organizations. Therefore, this study has achieved the objective s of gathering data on user perceptions and expectations towards privacy

Aggressive movement detection using optical flow features base on digital & thermal camera

Detection and tracking of people in digital images has been subject to extensive research in the past decades.Following the growing availability of thermal cameras and the distinctive thermal signature of humans, research effort has been focusing on developing people detection and tracking methodologies applicable to this sensing modality.Thermal imaging technology can be used to detect aggressive levels in humans based on the radiated heat from their face and body. Previous research proposed an approach to figure out human aggressive features using Horn-Schunck optical flow algorithm in order to find the flow vector for all video frames using digital camera only. However, still not strong enough to confirm and verify the existence of an aggressive movement. Then, we propose another approach using thermal videos to detect aggressive features in human aggressive movement.Video frames are collected using thermal camera and then extracted into thermal images. This research also guides and discovers the patterns of body distracted movement.Result below will show the comparison between both cameras digital and thermal camera

A Study on Implementing Physiology-Based Approach and Optical Flow Algorithm to Thermal Screening System for Flu Detection

Viral outbreaks such as SARS, H5N1, and H1N1 have led the need of temperature monitoring in areas where crowds are expected such as in hospitals and airports. Infrared (IR) thermal screening, hitherto, has been found as powerful, quick and non-invasive method to detect the elevated temperature of febrile individuals when the temperature of the face is above 36°. Past research has proved that the most excellent area that represents the core body temperature is the medial canthal areas of the face as it is less dependent on the effects of ambient temperature. In realistic situation, the moving subjects are random and the angles of the skin surface and distances change dynamically and misdetection of canthal area could also be due to any other unwanted objects that have the same temperature. The normal approach is to ask a single person to stand still for 2 seconds to capture the temperature. However this approach is ineffective and this will lead to long queue in public. To solve this issue, we have proposed a combination of physiology-based and optical flow algorithm to extract vascular network from the face. The thermal camera is provided with colour and audible alarming, hence when the camera detect an abnormal temperature from a person, automatic febrile individual tracking alarm wil

Factors Influencing Users’ Satisfaction Towards Image Use in Social Media: A PLS-SEM Analysis

Images for social media are an essential component of any blog or social media post. As we now live in the age of the 'camera in everyone's pocket', a new dynamic era of image creation and content has emerged. However, people use media due to specific motives or gratifications that lead to their satisfaction of social media use. This research study utilized uses and gratification theory (UGT), a sociology theory related to the motives of people using the media. The UGT factors include enjoyment, entertainment, social influence, social interaction, and information sharing. There were 441 data that were collected and analysed. IBM SPSS Statistics 20 and Smart PLS 3.3.3 were used for the data analysis. Result showed that information sharing was the most influencing factors on users’ satisfaction to use image in social media. Therefore, the factors identified in these studies could be used as a guideline and references in future study related to social media awareness and implications

Implementing low level features for human aggressive movement detection

In this real world, being able to identify the signs of imminent abnormal behaviors such as aggression or violence and also fights, is of extreme importance in keeping safe those in harm’s way. This research propose an approach to figure out human aggressive movements using Horn-Schunck optical flow algorithm in order to find the flow vector for all video frames. The video frames are collected using digital camera. This research guides and discovers the patterns of body distracted movement so that suspect of aggression can be investigated without body contact. Using the vector of this method, the abnormal and normal video frames are then classified and utilized to define the aggressiveness of humans. Preliminary experiment result showed that the low level of feature extraction can classify human aggressive and non-aggressive movements

Political Security Threat Prediction Framework Using Hybrid Lexicon-Based Approach and Machine Learning Technique

The internet offers a powerful medium for expressing opinions, emotions and ideas, using online platforms supported by smartphone usage and high internet penetration. Most internet posts are textual based and can include people’s emotional feelings for a particular moment or sentiment. Monitoring online sentiments or opinions is important for detecting any excessive emotions triggered by citizens which can lead to unintended consequences and threats to national security. Riots and civil war, for instance, must be addressed due to the risk of jeopardizing social stability and political security, which are crucial elements of national security. Mining opinions according to the national security domain is a relevant research topic that must be enhanced. Mechanisms and techniques that can mine opinions in the aspect of political security require significant improvements to obtain optimum results. Researchers have noted that there is a strong relationship between emotion, sentiment and political security threats. This study proposes a new theoretical framework for predicting political security threats using a hybrid technique: the combination of lexicon-based approach and machine learning in cyberspace. In the proposed framework, Decision Tree, Naive Bayes, and Support Vector Machine have been deployed as threat classifiers. To validate our proposed framework, an experimental analysis is accomplished. The performance of each technique used in the experiments is reported. In this study, our proposed framework reveals that the hybrid Lexicon-based approach with the Decision Tree classifier recorded the highest performance score for predicting political security threats. These findings offer valuable insight to ongoing research on opinion mining in predicting threats based on the political security domain