Vulnerability Analysis of the Optimized Link State Routing Protocol version 2 (OLSRv2)

Mobile Ad hoc NETworks (MANETs) are leaving the confines of research laboratories, to find place in real-world deployments. Outside specialized domains (military, vehicular, etc.), city-wide community-networks are emerging, connecting regular Internet users with each other, and with the Internet, via MANETs. Growing to encompass more than a handful of ``trusted participants'', the question of preserving the MANET network connectivity, even when faced with careless or malicious participants, arises, and must be addressed. A first step towards protecting a MANET is to analyze the vulnerabilities of the routing protocol, managing the connectivity. By understanding how the algorithms of the routing protocol operate, and how these can be exploited by those with ill intent, countermeasures can be developed, readying MANETs for wider deployment and use. This paper takes an abstract look at the algorithms that constitute the Optimized Link State Routing Protocol version 2 (OLSRv2), and identifies for each protocol element the possible vulnerabilities and attacks -- in a certain way, provides a ``cookbook'' for how to best attack an operational OLSRv2 network, or for how to proceed with developing protective countermeasures against these attacks

Security Issues in the Optimized Link State Routing Protocol version 2 (OLSRv2)

Mobile Ad hoc NETworks (MANETs) are leaving the confines of research laboratories, to find place in real-world deployments. Outside specialized domains (military, vehicular, etc.), city-wide community-networks are emerging, connecting regular Internet users with each other, and with the Internet, via MANETs. Growing to encompass more than a handful of ``trusted participants'', the question of preserving the MANET network connectivity, even when faced with careless or malicious participants, arises, and must be addressed. A first step towards protecting a MANET is to analyze the vulnerabilities of the routing protocol, managing the connectivity. By understanding how the algorithms of the routing protocol operate, and how these can be exploited by those with ill intent, countermeasures can be developed, readying MANETs for wider deployment and use. This memorandum takes an abstract look at the algorithms that constitute the Optimized Link State Routing Protocol version 2 (OLSRv2), and identifies for each protocol element the possible vulnerabilities and attacks -- in a certain way, provides a ``cookbook'' for how to best attack an operational OLSRv2 network, or for how to proceed with developing protective countermeasures against these attacks

Digital Signatures for Admittance Control in the Optimized Link State Routing Protocol version 2

Public community Mobile Ad Hoc NETworks (MANETs), such as the ``Funkfeuer'' or ``Freifunk'' networks, scale up to several hundreds of routers, connecting users with each other, and with the Internet. As MANETs are typically operated over wireless channels (e.g. WiFi), access to these networks is granted to anyone in the radio range of another router in the MANET, and running the same MANET routing protocol. In order to protect the stability of the networks from malicious intruders, it is important to ensure that only trusted peers are admitted to participate in the control message exchange, and to provide means for logically ``disconnecting'' a non-trustworthy peer. This memorandum presents the concept of admittance control for the Optimized Link State Routing Protocol version 2 (OLSRv2), and suggests a security extension based on digital signatures. Due to the flexible message format of OLSRv2, this extension keeps compatibility with the core OLSRv2 specification. Several standard digital signature algorithms (RSA, DSA, ECDSA), as well as HMAC, are compared in terms of message overhead and CPU time for generating and processing signatures

Evaluasi Kinerja Protokol Perutean Proaktif Pada Jaringan Nirkabel AD HOC Multihop

Jaringan wireless ad hoc adalah sekumpulan node bergerak pada wireless secara dinamis membentuk suatu jaringan temporer tanpa menggunakan infrastruktur jaringan yang ada atau administrasi terpusat. Sejumlah rule protokol proaktif yang diteliti seperti OLSR (Optimized Link State Rute) dan FSR (Fisheye State Rute) sudah banyak diimplementasikan. Pada penelitian ini dilakukan percobaan menggunakan simulator level-paket pada 1 00 node bergerak secara acak pada lokasi 1 000 x I 000 meter persegi, untuk mengevaluasi dan membandingkan unjuk kerja kedua protocol rute proaktif pada jaringan wireless ad hoc multi-hop. Hasil penelitian pengiriman dan perawatan rute merupakan faktor terpenting yang mempengaruhi pengukuran unjuk kerja khususnya dalam hal laju keberhasilan penyampaian paket pada beban kerja jaringan tinggi dan peningkatan kecepatan node. Protokol dengan dasar kerja tabel, table-driven, OLSR (Optimized Link State Rute Protocol), memiliki unjuk kerja paling baik dibandingkan dengan (Fisheye State Rouring) FSR. Unjuk kerja rute protocol ini dianalisa dengan menggunakan waktu jeda dan kemampuan untuk mencari rute sehingga didapatkan throughput terbaik, waktu tunda (delay) tersingkat, perubahan kecepatan gerakan node dan ukuran area tertentu. Untuk memperoleh hasil yang diharapkan, dengan menggunakan model simulasi Network Simulator (NS-2) Allinone versi 2.28, untuk ketepatan model lapisan MAC dan sifat lapisan fisik baku wireless LAN IEEE 802.11 yang digunakan pada jaringan wireless ad hoc multi-hop. Perbandingan unjuk kerja protocol rute proaktif akan mendapat penilaian yang terbaik kualitas protocol rute yang diteliti berdasarkan keberhasilan penyampaian paket, throughput dan End-to-End delay adalah: Optimized Link State Rute (OLSR) dengan rata-rata throghput mencapai 99,5 %, juga merupakan protokol dengan unjuk kerja efisiensi protokol paling baik sedangkan Fisheye State Rute (FSR) merupakan protokol rute yang memiliki unjuk kerja tunda waktu penyampaian paket dari node sumber ke node tujuan terpendek. ====================================================================================================================================== An ad hoc wireless network is a collection of wireless mobile nodes dynamically forming a temporary network without the use of network infrastructure or centralized administration. A number of proactive routing protocols like Optimized Link State Routing (OLSR) and Fisheye State Routing (FSR) have been implemented. In this project an attempt has been made to compare the performance each protocol using a detailed packet-level simulator for 100 mobile nodes in location 1OOOx 1000 square meter, wireless ad hoc network. Results have shown that quick management of route maintenance is an important factor that effects all the performance measures, especially the successful delivery rate at high workloads and increasing speeds. Protocol based on table-driven, OLSR (Optimized Link State Routing), have poor performance. The source-initiated protocol like have better performance(Fisheye State Routing) FSR. Performances comparing analyzed with network workload variation, and mobile nodes speed variation on a fixed square area. Our simulation experiment used the ns-2 network simulator Version Allinone 2.28, to accurately model the MAC layer and physical layer behavior of the 802.11 wireless LAN standard for ad hoc wireless network multihop. Performance comparison for proactive routing protocol will be worked on routing protocol quality based on packet delivery, throughput and end-to-end delay.OLSR that reach throughput rate 99.5% is a protocol with the bast performance efeciency, mean while FSR is a routing protocol with the shortest end-to-end delay

MPR selection to the OLSR quality of service in MANET using minmax algorithm

Optimized link state routing (OLSR) is a routing protocol that has a small delay, low traffic control, support the application of denser networks, and adopts the concept of multipoint relays (MPR). The problem of OLSR is routing table updating which continually causes excessive packet delivery, and energy consumption becomes increased. This article proposes the improvement of OLSR performance using the min-max algorithm based on the quality of service (QoS) with considering the density of the node. The Min-max algorithm works in selecting MPR nodes based on the largest signal range. The QoS parameters analyzed with a different number of nodes are packet delivery ratio (PDR), throughput, delay, energy consumption, and topology control (TC). Simulation result of network simulator version 2 (NS-2) shows that OLSR performance using the min-max algorithm can increase PDR of 91.17%, packet loss of 60.77% and reduce topology control packet of 8.07%, energy consumption of 16.82% compared with standard OLSR

Predicting topology propagation messages in mobile ad hoc networks: The value of history

This research was funded by the Spanish Government under contracts TIN2016-77836-C2-1-R,TIN2016-77836-C2-2-R, and DPI2016-77415-R, and by the Generalitat de Catalunya as Consolidated ResearchGroups 2017-SGR-688 and 2017-SGR-990.The mobile ad hoc communication in highly dynamic scenarios, like urban evacuations or search-and-rescue processes, plays a key role in coordinating the activities performed by the participants. Particularly, counting on message routing enhances the communication capability among these actors. Given the high dynamism of these networks and their low bandwidth, having mechanisms to predict the network topology offers several potential advantages; e.g., to reduce the number of topology propagation messages delivered through the network, the consumption of resources in the nodes and the amount of redundant retransmissions. Most strategies reported in the literature to perform these predictions are limited to support high mobility, consume a large amount of resources or require training. In order to contribute towards addressing that challenge, this paper presents a history-based predictor (HBP), which is a prediction strategy based on the assumption that some topological changes in these networks have happened before in the past, therefore, the predictor can take advantage of these patterns following a simple and low-cost approach. The article extends a previous proposal of the authors and evaluates its impact in highly mobile scenarios through the implementation of a real predictor for the optimized link state routing (OLSR) protocol. The use of this predictor, named OLSR-HBP, shows a reduction of 40–55% of topology propagation messages compared to the regular OLSR protocol. Moreover, the use of this predictor has a low cost in terms of CPU and memory consumption, and it can also be used with other routing protocols.Peer ReviewedPostprint (published version

Experimental evaluation of a MANET testbed in indoor stairs scenarios

In recent years, Mobile Ad hoc Networks (MANETs) are continuing to attract the attention for their potential use in several fields. Mobility and the absence of any fixed infrastructure make MANETs very attractive for mobility and rescue operations and time-critical applications. In this paper, we present the implementation and analysis of our implemented MANET testbed considering the Optimized Link State Routing (OLSR) protocol. We consider two models. One when all the nodes are static and another one when one node is moving. The mobile node moves toward the destination at a regular speed and when arrives at the corner of stairs is stops for about three seconds. In this work, we assess the performance of our MANET testbed in terms of throughput and packet loss. From our experiments, we found that the OLSR protocol has a good performance when nodes are in stationary state. However, when the node moves the throughput is decreased. We observed that the number of packet loss increases after 2-hops for static model and after 1-hop for moving model. But, when the node is moving, the packet loss for 2-hops to 4-hops is almost the same.Peer ReviewedPostprint (published version

Speed-Aware Routing for UAV Ad-Hoc Networks

In this paper we examine mobile ad-hoc networks (MANET) composed by unmanned aerial vehicles (UAVs). Due to the high-mobility of the nodes, these networks are very dynamic and the existing routing protocols partly fail to provide a reliable communication. We present Predictive-OLSR an extension to the Optimized Link-State Routing (OLSR) protocol: it enables efficient routing in very dynamic conditions. The key idea is to exploit GPS information to aid the routing protocol. Predictive-OLSR weights the expected transmission count (ETX) metric, taking into account the relative speed between the nodes. We provide numerical results obtained by a MAC-layer emulator that integrates a flight simulator to reproduce realistic flight conditions. These numerical results show that Predictive-OLSR significantly outperforms OLSR and BABEL, providing a reliable communication even in very dynamic conditions.Comment: submitted to GlobeCom'13 Workshop - Wi-UA