Designing A Trust Management System for Malicious Node Detection and Prevention in Internet of Things / (Record no. 615832)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04341nam a22001697a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NUST |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 005.8,ALT |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Altaf, Ayesha |
| 9 (RLIN) | 124449 |
| 245 ## - TITLE STATEMENT | |
| Title | Designing A Trust Management System for Malicious Node Detection and Prevention in Internet of Things / |
| Statement of responsibility, etc. | Ayesha Altaf |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Rawalpindi, |
| Name of publisher, distributor, etc. | MCS (NUST), |
| Date of publication, distribution, etc. | September 2011 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xviii, 129 p |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Internet of Things (IoT) is a rapidly growing field that provides seamless connectivity to<br/>physical objects to make them part of a smart environment. To fully utilize the potential<br/>power of these connected objects of IoT, trust existence among these objects is essential.<br/>Traditional security measures are not enough to provide comprehensive security to this smart<br/>world. Trust is used to mitigate the risk of uncertainty while connecting nodes to the Internet.<br/>This dissertation proposed the secure trust model for IoT-based Smart City for secure and<br/>trustworthy communication.<br/>We have proposed an adaptive Context-Based Trust Evaluation System (CTES) model,<br/>which focuses on calculating trust based on direct observations and indirect recommendations<br/>of communicating nodes. Each node takes recommendations from its identical contextsimilar<br/>nodes and filters out the malicious nodes. The weighing factor is dynamically assigned<br/>based on the previously calculated trust score experienced by the user. To enhance<br/>the security of smart buildings in IoT, this research also proposes an adaptive Context-Based<br/>Trust Evaluation System for Smart Building (CTES-SB) applications. The trust score for<br/>service is calculated based upon the client’s previous interaction and recommendation from<br/>context-similar clients. Using CTES-SB, the client selects the best service provider based<br/>on the previous and current trust scores for the next interaction.<br/>This research provides a classification of Trust Related Attacks (TRA) and a comparison<br/>of existing trust models with respect to TRA and Function Requirements (FR) of IoT. This<br/>comparison aim is to summarize the FR of IoT which must be considered while designing<br/>the Trust Management System (TMS). This research also focuses on the formal verification<br/>of the proposed CTES model. We analyze the effects of calculation of trust in terms<br/>of CTES accuracy, dynamic assignment for , and resiliency against Ballot Stuffing and<br/>Bad-Mouthing attacks to avoid bad nodes. The adaptive weights assigned to direct observations<br/>and indirect recommendations ensure the effectiveness of the Context-Based Trust<br/>Evaluation System Model (CTES) in detecting On-Off attacks. Moreover, context similarity<br/>measure calculations filter out those bad nodes which are posing a Sybil Attack.<br/>The similarity measure adapted in the proposed CTES is used to avoid the nodes which<br/>are changing their identity and making the environment vulnerable by posing a Sybil attack.<br/>Similarly, the dynamic assignment of makes the smart network safer by avoiding On–Off<br/>attacks of neighboring nodes. It is therefore verified and tested through simulation that by<br/>using these measures, the trust score of the suspected nodes becomes lower than the trust level and is hence discarded. The proposed CTES has been simulated on Contiki Cooja.<br/>The results ensure the significance of the proposed CTES model for dynamic assignment<br/>of and provide satisfactory results against EigenTrust, ServiceTrust, and ServiceTrust++<br/>in terms of detecting malicious nodes and isolating them from providing recommendations.<br/>The comparison is in terms of filtering the malicious nodes from the network and the result<br/>shows that the trust converges quickly toward the ground-truth value. This is because<br/>EigenTrust establishes global trust thus failed in breaking chains of malicious nodes whereas<br/>ServiceTrust and ServiceTrust++ use uniform trust propagation with trust decay which helps<br/>them to identify some malicious chains and result in fewer failed services than EigenTrust.<br/>It has been observed that CTES is effective in a malicious environment for 22% of failed<br/>services in comparison of 45% to 60% of failed provided services in EigenTrust and ServiceTrust. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | PhD Information Security Thesis |
| 9 (RLIN) | 132793 |
| 651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME | |
| Geographic name | PhD IS Thesis |
| 9 (RLIN) | 132794 |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Supervised by Dr. Haier Abbas |
| 9 (RLIN) | 132792 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Thesis |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Full call number | Barcode | Date last seen | Price effective from | Koha item type | Public note |
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| Military College of Signals (MCS) | Military College of Signals (MCS) | Thesis | 01/17/2026 | 005.8,ALT | MCSPhD IS-07 | 01/17/2026 | 01/17/2026 | Thesis | Almirah No.68, Shelf No.5 |