Advanced and rapid developments in the field of computer and wireless technologies makes easy and possible to be a direct part of electronic media. Social media is an attractive, informative, useful, and approachable way to get information. In last few years, there is an increase observed in the smartphone, smart tablet, and wireless broadband market in Pakistan. It is because of the popularity of social media, its access, and usage in most of citizens. It is a positive prospect for the country, however; there are many issues are rising with the usage of social networking sites. In this paper, the social media technologies were and reasons behind the increase in usage of social media Pakistani netizens (Internet users) is discussed. Moreover, the challenges regarding social media such as cyber-crimes, cyber blackmailing, ethics, security and identity protection in Pakistan is discussed in this Paper.
Nowadays, smart devices have become a part of ourlives, hold our data, and are used for sensitive transactions likeinternet banking, mobile banking, etc. Therefore, it is crucial tosecure the data in these smart devices from theft or misplacement.The majority of the devices are secured with password/PINbaseduser authentication methods, which are already proveda less secure or easily guessable user authentication method.An alternative technique for securing smart devices is keystrokedynamics. Keystroke dynamics (KSD) is behavioral biometrics,which uses a natural typing pattern unique in every individualand difficult to fake or replicates that pattern. This paperproposes a user authentication model based on KSD as an additionalsecurity method for increasing the smart devices’ securitylevel. In order to analyze the proposed model, an android-basedapplication has been implemented for collecting data from fakeand genuine users. Six machine learning algorithms have beentested on the collected data set to study their suitability for usein the keystroke dynamics-based authentication model.
Now-a-days, in the field of machine learning the data augmentation techniques are common in use, especially with deep neural networks, where a large amount of data is required to train the network. The effectiveness of the data augmentation technique has been analyzed for many applications; however, it has not been analyzed separately for the multimodal biometrics. This research analyzes the effects of data augmentation on single biometric data and multimodal biometric data. In this research, the features from two biometric modalities: fingerprint and signature, have been fused together at the feature level. The primary motivation for fusing biometric data at feature level is to secure the privacy of the user’s biometric data. The results that have been achieved by using data augmentation are presented in this research. The experimental results for the fingerprint recognition, signature recognition and the feature-level fusion of fingerprint with signature have been presented separately. The results show that the accuracy of the training classifier can be enhanced with data augmentation techniques when the size of real data samples is insufficient. This research study explores that how the effectiveness of data augmentation gradually increases with the number of templates for the fused biometric data by making the number of templates double each time until the classifier achieved the accuracy of 99%.
In this paper, an android based SAMS (Smart Activities Monitoring System) application for smart phone is proposed. This application is developed with the aim of increasing the national security in Pakistan. In last decade, various incidents including militant attacks and ransomdemands have been reported in which cell phones played a central role in communication between the culprits. The tracking of these criminals is very important and the government needs to adopt technologies to track mobile phones if they are being used for dangerous activities. In this paper, an android based application is presented which is designed and tested to track a suspect without his/her attention. This application tracks a smartphone by obtaining its current location and monitors a suspect remotely by retrieving information such as call logs, message logs etc. It also detects the face of the suspect and covertly captures the picture using cell phone camera and then sends it via multiple messages. Moreover, the monitoring user can also make calls to the phone which the culprit is using in stealth mode to hear the conversation happening in surroundings of the user without the knowledge of suspect.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.