The extensive research in the field of multimodal biometrics by the research community and the advent of modern technology has compelled the use of multimodal biometrics in real life applications. Biometric systems that are based on a single modality have many constraints like noise, less universality, intra class variations and spoof attacks. On the other hand, multimodal biometric systems are gaining greater attention because of their high accuracy, increased reliability and enhanced security. This research paper proposes and develops a Convolutional Neural Network (CNN) based model for the feature level fusion of fingerprint and online signature. Two types of feature level fusion schemes for the fingerprint and online signature have been implemented in this paper. The first scheme named early fusion combines the features of fingerprints and online signatures before the fully connected layers, while the second fusion scheme named late fusion combines the features after fully connected layers. To train and test the proposed model, a new multimodal dataset consisting of 1400 samples of fingerprints and 1400 samples of online signatures from 280 subjects was collected. To train the proposed model more effectively, the size of the training data was further increased using augmentation techniques. The experimental results show an accuracy of 99.10% achieved with early feature fusion scheme, while 98.35% was achieved with late feature fusion scheme.

At present, voice biometrics are commonly used for identification and authentication of users through their voice. Voice based services such as mobile banking, access to personal devices, and logging into social networks are the common examples of authenticating users through voice biometrics. In Pakistan, voice-based services are very common in banking and mobile/cellular sector, however, these services do not use voice features to recognize customers. Therefore, the chance to use these services with false identity is always high. It is essential to design a voice-based recognition system to minimize the risk of false identity. In this paper, we developed regional voice datasets for voice biometrics, by collecting voice data in different local accents of Pakistan. Although, there is a global need for voice biometrics especially when voice-based services are common, however, this paper uses Pakistan as a use case to show how to build regional voice dataset for voice biometrics. To build voice dataset, voice samples were recorded from 180 male and female speakers with two languages English and Urdu in form of five regional accents. Mel Frequency Cepstral Coefficient (MFCC) features were extracted from the collected voice samples to train Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF) and K-nearest neighbor (KNN) classifiers. The results indicate that ANN outperformed SVM, RF and KNN by achieving 88.53% and 86.58% recognition accuracy on both datasets respectively.

This paper reports the development in fingerprint sensor technologies with respect to strengths and weaknesses of each. Related issues on technology, underlying physics, liveness detection, resolution, performance assessment, limitations and standardization are discussed. Finally, the future directions of fingerprint sensors and systems development are explored.

Vehicular Ad hoc Networks (VANETs) is a developing technology now a days. It is being developed in order to provide a safer and smoother experience of travelling. It is classified into two categories one being Vehicle to Vehicle (V2V) Communication and the other is Vehicle to Infrastructure (V2I) Communication. In this project, we have developed a system that is based on V2V and V2I technologies, which creates communication architecture to automatic management of traffic by helping emergency vehicles such as ambulance and fire brigade to select the route with less congestion based on the data sent by the sensors. During any type of difficulty, traffic jam or complication, the developed system will respond and forward the necessary information about traffic congestion, sending the route status updates to the vehicle display for driver. Moreover, the system also responds and generates an emergency message at the central node if the emergency vehicle meets an accident.

In this modern age, as time passes new emerging technologies, cyber services have been introduced. In this regard, most of the developing countries have deployed and implemented these technologies and services Such as: e Banking, eCommerce and eBusiness in their countries. Pakistan is also one of these developing countries, who has implemented and currently using for the citizen, users, businessmen and also offers these services as government offers user-oriented services. This type of services save the users time and also provides efficient services as well as enhance the economical and social reputation in the market. But, these services may raise a crucial challenge about their security. At this time cyber criminals are active to breach the security measures. Pakistan is also facing the security problem because of limited resources, technical personals and lack of standardized policies. Moreover, this paper highlights the cyber threats and attacks, cyber laws as well as some eGovernment service challenges and recommends cyber protection policies for policy makers. This paper also helps the policy makers and service oriented organizations to design new security policies and strategies for citizens of Pakistan.