Department of Computer Science

Permanent URI for this communityhttps://repository.cuilahore.edu.pk/handle/123456789/16

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Author: search.filters.author.Dr. Adnan AhmadSubject: search.filters.subject.Computer Science

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Now showing 1 - 6 of 6
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    Semantic-Based Summarization Using Ontology and Machine Learning Algorithms
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Tayyaba Amber; CIIT/SP24-RCS-011/LHR; Dr. Adnan Ahmad; LHR TP 10037
    In natural language processing, the task of text summarization is a challenging and intriguing problem. A summary of a long document enables the reader to easily grasp the key informa- tion without having to read the entire text. The existing methods struggle with generating fluency and coherent summaries, often missing important sentences in a document. This the- sis aims to automate text summarization by using two approaches: extractive and abstractive. In the extractive text summarization, we introduce two layers of sentence scoring. First, we identify different features of the sentences based on a story document and assign weights to them. Second, we readjust the scoring by applying various rules. The top-N sentences are selected as our extractive text summary, where all the sentences have a high score. In an abstractive text summary, we utilize a predefined T5 model, comparing it with Bert2Bert, PEAGAUS, BART, and GPT2 models. The summary of the document is created based on the level of importance of the sentences in the document. The results obtained using the T5 on the feature-extraction with rules refinement scoring dataset are competitive with state-of-the-art. For the FER model, the performance has been improved, among which the most significant improvements are: BERTScoring 0.88, 0.80, 0.83, for the three selected story documents. After these utilization we also create a FER ontology their each sentences is work as instance and their score are work as its data properties. By using this technique we make our model to query-based user intension summary generator. This ontology give the same result as we pass a query that calculate all the feature and give the high score sentences as an output. By using this technique user also get the summary as their need.
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    Real Vs Fake: Detecting Deep Fake Videos Based ON Temporal changes in the Optical Flow between Frames
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Javaria Rasool; CIIT/SP22-RCS-016/LHR; Dr. Adnan Ahmad; LHR TP 9993
    This research analyses different methods to detect deepfakes and proposes a method that is novel and computationally competent. Main methods examined range through deep learning-based methods that use CNNs and GAN analysis, machine learning, and statistical methods. It also talks about the important issue of fairness in deepfake detection, with the goal of reducing biases across different demographic groups i.e. the proposed method is independent of features that may render it racist. This study introduces novel features designed to yield results comparable to complex and computationally intensive existing methodologies. The choice of new features was based on the idea that the way facial movements change over time will be different in deepfakes than in the original video. The frequency spectrum of temporal variations makes the difference clear. It also talks about the important issue of fairness in deepfake detection, with the goal of reducing biases across different demographic groups. It also looks at how detection methods can be used in media forensics workflows, even testing the usefulness of hand-crafted features alongside learnt representations. The need for robust and efficient detection in the face of evolving deepfake technologies and the importance of interpretable and fair solutions is felt more than ever before.
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    A Framework for the Development of Cybersecurity Legislation using a Decision Support System
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2023) Naseer Ahmad; FA21-RCS-017; LHR TP 8679; Dr. Adnan Ahmad
    The dependence on technology is increasing and its influence is felt in practically every aspect of life. Its trend is expected to remain in the future. Unfortunately, its advancement has led to an increase in cybercrime and it is causing growing concern around the world, specifically for developing nations. Developed countries have implemented strong cybersecurity legislation to address this issue. It is imperative that all nations implement robust and uniform cybersecurity legislation to combat cybercrime, similar to that of advanced nations. For this purpose, A framework is essential to assist in creating an effective and robust cybersecurity legislation, which is necessary to combat the negative impacts of cybercrimes. For fulfilling this need, this research has proposed a framework for the development of cyber law using a knowledge-based decision support system.
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    Online Trust in Teen Communities
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2017) Alia Samreen; FA15-RCS-015; LHR TP 6833; Dr. Adnan Ahmad
    Consistently, individuals from everywhere throughout the world connect, share and exchange data over Internet. We communicate online to share individual data, discover answers to inquiries, direct money related exchanges, play social recreations and keep up proficient and individual connections. “Online Social Network (OSN) is a set of personal contacts through which the people maintains their social identity and receive emotional support, material aid, services, information and new social contacts” [1] like Facebook, Orkut etc. Online Social Network gives a virtual situation where people can share their stories, pictures, recordings, and take part in chat rooms for online chatting with their friends and associates. In the last decade, Online Social Networks (OSN) have expanded ubiquitously. More people use OSN to share their interests and make associations, [1] likewise, OSN help people to overcome geographical impediments. Despite of its advantages OSN has also raised some privacy concerns for users. Many people have lost their jobs [86], lives [89], become bullied [4], hacked [4] etc. because of privacy issues of OSN. The situation is even worst for teens who get emotionally, socially and physically compromised due to interactions over online social networks. This is because of the fragile psychology of teens as they are more inclined to pulls of fascination [4,38], emotionally immature [3], more inclined to sensual offers [3,5] and easily grasped by fraudulent [3]. Thus, there is a need of an application that can evaluate, maintain and exhibit the community trust over acquaintances for teens. Trust is an essential part of connections in online social networks whether it is for security, deciding information access, or recommender systems [8]. In this thesis, the student has analyzed issues of teenagers and the factors that affect the formation of end user trust in online environments. After exploring the factors, the student has proposed a framework portraying various stages and their elements important to build trust among people. On the basis of framework, a reputation model is proposed, which xi ensures that a stranger or an acquaintance is trustworthy or not. Our proposed method basically judges people on the basis of their reputation, trustworthiness, honesty, benevolence, integrity, compatibility, confidence etc. The method is also implemented using dot net framework and SQL server. The student generates a new app on Facebook App. Then, the student gets Facebook App Key and App Secret Key. After that, in dot net framework the student gets built in Facebook Configuration Dll. Then, the student creates an instance of Facebook Dll Class and set its App Key and App Secret Key. Then, ask the User Current Session Token Context to be used by Facebook. Then, it will check for Permissions assigned to us by the User on FaceBook. The application was also tested and evaluated by teens on the basis of usefulness, ease of use, ease of learning, satisfaction, and system capabilities. The questionnaire was validated through inter-item and inter-variable correlation which appeared to be sufficiently significant. Moreover, Cronbach’s Alpha test was carried out for internal consistency which also appears to be statistically significant. The average users’ response over the variable and their items suggests that teens are satisfied with the proposed approach and it really helped them to identify trustworthy and well reputed friends
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    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.
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    An Approach to Identify Fake Profile in Online Social Networks Using Network Graph Analysis
    (Library Information Services COMSATS University Islamabad Lahore Campus, 2020-01-30) Fareeha Hafeez; SP17-RCS-002; Dr. Adnan Ahmad; LHR TP 6399
    In the present generation, Online Social Networks have become an essential part of internet users to perform different activities like sharing different information in the form of personal information, videos, pictures, discussions on different topics, product reviews, research and e-business. The popularity of these platforms such as Facebook and Twitter etc. attracted cyber criminals to violate and abuse the network services for illicit gain. These cyber criminals includes the fraudsters, imposters, scammers social bots, phishers and spammers etc. These attackers exploit the platform for personal gain particularly by using fake profiles. Fake profiles can be used for a variety of purpose but the primary purpose of such profiles include fake followers, spread mislead content and scamming. The online social network’s overall reputation is affected by fake profiles. A spam account is a type of fake account that can be human generated or bot generated. The primary purpose of spammers is to distribute misleading information, malicious content, posting malicious users and send spontaneous messages to a large group of audience. A lot of existing research is available to detect fake profiles in online social networks but there is no feasible method available to overcome this problem. A model is much needed that can identify fake profiles in online social network.