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Anomaly Adjudication based Sinkhole Handling in Low Power Lossy Networks
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Ki-Hyung Kim | - |
| dc.contributor.author | CHEKKA KRISHNA SAI SREE | - |
| dc.date.accessioned | 2018-11-08T08:17:48Z | - |
| dc.date.available | 2018-11-08T08:17:48Z | - |
| dc.date.issued | 2014-02 | - |
| dc.identifier.other | 16215 | - |
| dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/12510 | - |
| dc.description | 학위논문(석사)--아주대학교 일반대학원 :컴퓨터공학과,2014. 2 | - |
| dc.description.tableofcontents | Table of Contents Acknowledgments 1 Abstract 2 Chapter 1 7 Introduction 7 1.1 Problem Statement 8 1.2 Aims and Objectives 9 1.3 Thesis Structure 9 Chapter 2 10 Background 10 2.1 RPL Overview 10 2.1.1 Upward Routing 10 2.1.2 Downward Routing 13 2.2. RPL Control Messages 14 2.2.1 DIO Message Structure 15 2.2.2 DODAG Information Solicitation 16 2.2.3 DAO Message Structure 17 2.3 Routing Metrics 18 2.4 Objective Function 19 2.5 Trickle Timer 20 2.6 RPL Traffic Pattern 20 2.6.1 Multipoint-to-Point 20 2.6.2 Point-to-Multipoint 21 2.6.3 Point-to-Point 21 2.7 RPL Security 21 2.8 Objective Function 22 Chapter 3 25 Related Work 25 Chapter 4 27 4.1 Contiki: A Sensor net Operating System 27 4.2 Cooja Simulator 27 Proposed Work 29 5.1 Proposed Algorithm 29 5.1.1 Version Number Authentication 31 5.1.2 Proposed Black Box Algorithm 32 5.2 Adjudication Algorithm 38 Chapter 6 39 Simulation Results 39 6.1 DODAG Network Setup 41 6.2 Experimental Results 42 Conclusion and Future Work 45 References 46 | - |
| dc.language.iso | eng | - |
| dc.publisher | The Graduate School, Ajou University | - |
| dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
| dc.title | Anomaly Adjudication based Sinkhole Handling in Low Power Lossy Networks | - |
| dc.type | Thesis | - |
| dc.contributor.affiliation | 아주대학교 일반대학원 | - |
| dc.contributor.department | 일반대학원 컴퓨터공학과 | - |
| dc.date.awarded | 2014. 2 | - |
| dc.description.degree | Master | - |
| dc.identifier.localId | 608207 | - |
| dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000016215 | - |
| dc.subject.keyword | Thesis submission | - |
| dc.description.alternativeAbstract | The growing interest for the Internet of Things has resulted in the large-scale deployment of Low power and Lossy Networks, such as wireless sensor networks and home automation systems. Today, Low Power and Lossy Networks (LLNs) represent one of the most interesting research areas. They include Wireless Personal Area Networks (WPANs), low-power Power Line Communication (PLC) networks and Wireless Sensor Networks (WSNs). Such networks are often optimized to save energy, support traffic patterns different from the standard unicast communication, run routing protocols over link layers with restricted frame-sizes and many others. These networks have strong constraints in terms of resources (energy, memory, and power) and their communication links are by nature characterized by a high loss rate and a low throughput. Moreover the traffic patterns are not simply point-to-point, but in many cases the devices communicate according to a point-to-multipoint or multipoint-to-point schema. Existing routing protocols for wired networks (OSPF, IS-IS) and for ad-hoc networks (AODV, OLSR) are not suitable to deal with all these requirements. The IETF ROLL working group has proposed a new routing protocol called RPL (Routing Protocol for Low power and Lossy Networks) based on IPv6 and specifically designed for these environments. These RPL-based networks may be exposed to a large variety of attacks, but the deployment of security mechanisms may also be quite expensive in terms of resources. In LLN’s where the energy is considered to be a weighted constraint, a security anomaly in the network is not affordable; one of the most troublesome with in those anomalies is sinkhole, which could exhaust the individual node to whole network. In sinkhole attack a malicious node advertises an artificial beneficial routing path and attracts many nearby nodes to route traffic through it. In this Thesis we defined different strategies for launching sinkhole attacks. We proposed a hash-based authentication for DODAG root messages such as DIO and behavioral anomaly detection with adjudicated verification for nodes that are suspected to be compromised. Finally, we demonstrate the attack and present some implementation details that emphasize the little effort that an attacker would need to put in order to break into a realistic sensor network. | - |
- Appears in Collections:
- Graduate School of Ajou University > Department of Computer Engineering > 3. Theses(Master)
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