M.Phil / MS

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Cross Genre Author Profiling Using Semantic Tagger Based Approach
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2017) Humaira Muqdes; FA15-RCS-023; LHR TP 7000; Dr. Rao Muhammad Adeel Nawab
Author profiling is a task to predict one or more traits of an author (e.g. age, gender etc.), from his/her written text. The collaborative environments have significantly increased the chance of fake author profiles, particularly over the social media. The field of automatically detecting an author’s profile from written text has potential applications in marketing, forensics, security, detecting fake profiling and harassment cases. This research work aims to explore the problem of cross genre author profiling, in which training dataset is in one genre and test dataset is in another genre. We explored three different methods for cross-genre author profiling: (1) stylometry based approach, (2) content based approach, (3) semantic tags based approach and (4) combination of previous three approaches. As far as we are aware semantic tags based approach and combination of approaches has not been previously used for cross genre author profiling problem. Evaluation was carried out using four benchmark author profiling corpora: (1) PAN-AP-14 Social Media Corpus, (2) PAN-AP-14 Hotel Reviews corpus, (3) PAN-AP-14 Blogs Corpus and (4) PAN-AP-16 Twitter Corpus. Accuracy was used an evaluation measure. Above mentioned techniques were applied for both same and cross genre problems. For same genre, best results were obtained using content based technique on PAN-AP 14-Hotel Reviews Corpus (Accuracy =55.26) for Age (Accuracy= 66.59) for gender content based techniques for PAN-AP-Blogs Corpus (Accuracy = 67.57) for age, Semantic tagger based technique (Accuracy = 78.38) for gender. Content based technique on PAN-AP-14-social media Corpus (Accuracy =55.26) for Age (Accuracy= 78.95) for gender. Content based technique on PAN-AP-16-Twitter Corpus (Accuracy =54.76) for Age (Accuracy= 74.42) for gender. For Cross Genre Training Corpus PAN-14-Blogs and testing Corpus PAN-14-Hotel reviews for age (Accuracy = 56.96) for gender training Corpus is PAN-16-Twitter (Accuracy= 58.97). Content Based Technique for Training Corpus PAN-14-Hotel reviews and testing Corpus PAN-14-Blogs for age (Accuracy = 40.81) for gender Stylistic based for training Corpus is PAN-14-Blogs (Accuracy= 59.86). Content based technique for Training Corpus PAN-14-Social Media and testing Corpus PAN-14-Blogs for age (Accuracy = 40.81) for gender Content based technique training Corpus is PAN-14-Blogs (Accuracy= 59.86). Stylistic based technique for PAN-16- Twitter training corpus and testing corpus PAN-14-Blogs (Accuracy = 40.81) for age. Content based technique for gender where testing corpus is PAN-14-Blogs (61.22) for gender.
Semantics Of Delegation In Federated Cloud
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2017) Numan Ahmad; FA15-RCS-005; LHR TP 6915; Dr. Adnan Ahmad
In federated cloud different cloud service provider allow each other to use their unused resources at some cost when their own resources are not enough. Or they collaborate with each other by delegating different services which other CSP (cloud service providers) are not providing. Before delegating they need to get pre-approval from some administrative authority which is time consuming task and can create administrative bottleneck. There should be a mechanism in federated cloud that allow the user to delegate permissions without taking pre-approval i.e. Ad-hoc Delegation. In this thesis, we explored the semantic of decentralized ad-hoc delegation in federated cloud and proposed a framework that explains the essential characteristics for delegation in federated cloud. We also developed a model, based on framework, that explore the semantics of decentralized ah-hoc delegation in federated cloud. Moreover, the model is formulated through Colored Petri Net using CPN-tools to verify it’s working.
A Game Theory Based Trust Model for Internet of Things
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2020) Ghulam Mustafa; FA15-RCS-029; LHR TP 5970; Dr. Adnan Ahmed
Internet of Things is a paradigm shift in the advancement of wireless sensor networks. This has been realized with advanced techniques of service provision and exchange of data. The concept behind this technology is “anytime, anywhere, any media”. There is a huge potential in IoT for the development of a large number of application out of which very small part has been deployed in our lives. Devices connected through the internet of Things are equipped with smart objects and these objects are increasingly becoming part of our life. IoT devices are providing services in almost all walks of life like services in automated industry, medical field, chemical plants, inventory control and other areas of human life. IoT devices are light weight with low power and low memory. Therefore, these devices are resource constrained and data possessed by these devices is very sensitive. In this research work the author identified a number of trust factors for the differentiation of the trustworthy and suspicious devices in IoT environments. The suspicious devices some time behave abnormally due to number of facts like memory and battery constraints and low processing power. Due to their malfunctioning these devices compromise the overall trust profile of the IoT network. The author has proposed a framework through which he described the essential elements for the identification of malicious nodes. This framework helps in in identifying the suspicious behavior of giving false feedback as badmouthing against the trustworthy nodes. After framing the proposed frame work, a model has been designed in which game theory has been incorporated for the behavior correction of the malicious devices through carrot and stick policy. On the basis of the game strategy the Nash equilibrium has been achieved so that a device after choosing its strategy cannot deviate from its strategy unilaterally. The stated model has been formalized in Microsoft Azure IoT Central, a software as a service (SaaS) based cloud environment and simulation has been performed. In the simulation, the deployment of the IoT devices and their feedback values regarding the tasks and services have also been collected for the identification of badmouthing in these feedbacks. The trust value of the participating nodes has been calculated on the basis of the feedback values after passing through the proposed non cooperative game so that our proposed trust model become trustworthy and cooperation enforcing. Finally, a conclusion regarding the performance of proposed work has been drawn

M.Phil / MS

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