Biblio
Proof-of-work (PoW) is an algorithmic tool used to secure networks by imposing a computational cost on participating devices. Unfortunately, traditional PoW schemes require that correct devices perform computational work perpetually, even when the system is not under attack. We address this issue by designing a general PoW protocol that ensures two properties. First, the network stays secure. In particular, the fraction of identities in the system that are controlled by an attacker is always less than 1/2. Second, our protocol's computational cost is commensurate with the cost of an attacker. That is, the total computational cost of correct devices is a linear function of the attacker's computational cost plus the number of correct devices that have joined the system. Consequently, if the network is attacked, we ensure security, with cost that grows linearly with the attacker's cost; and, in the absence of attack, our computational cost is small. We prove similar guarantees for bandwidth cost. Our results hold in a dynamic, decentralized system where participants join and depart over time, and where the total computational power of the attacker is up to a constant fraction of the total computational power of correct devices. We show how to leverage our results to address important security problems in distributed computing including: Sybil attacks, Byzantine Consensus, and Committee Election.
Advanced Metering Infrastructure (AMI) forms a communication network for the collection of power data from smart meters in Smart Grid. As the communication within an AMI needs to be secure, key management becomes an issue due to overhead and limited resources. While using public-keys eliminate some of the overhead of key management, there is still challenges regarding certificates that store and certify the public-keys. In particular, distribution and storage of certificate revocation list (CRL) is major a challenge due to cost of distribution and storage in AMI networks which typically consist of wireless multi-hop networks. Motivated by the need of keeping the CRL distribution and storage cost effective and scalable, in this paper, we present a distributed CRL management model utilizing the idea of distributed hash trees (DHTs) from peer-to-peer (P2P) networks. The basic idea is to share the burden of storage of CRLs among all the smart meters by exploiting the meshing capability of the smart meters among each other. Thus, using DHTs not only reduces the space requirements for CRLs but also makes the CRL updates more convenient. We implemented this structure on ns-3 using IEEE 802.11s mesh standard as a model for AMI and demonstrated its superior performance with respect to traditional methods of CRL management through extensive simulations.
In recent years the use of wireless ad hoc networks has seen an increase of applications. A big part of the research has focused on Mobile Ad Hoc Networks (MAnETs), due to its implementations in vehicular networks, battlefield communications, among others. These peer-to-peer networks usually test novel communications protocols, but leave out the network security part. A wide range of attacks can happen as in wired networks, some of them being more damaging in MANETs. Because of the characteristics of these networks, conventional methods for detection of attack traffic are ineffective. Intrusion Detection Systems (IDSs) are constructed on various detection techniques, but one of the most important is anomaly detection. IDSs based only in past attacks signatures are less effective, even more if these IDSs are centralized. Our work focuses on adding a novel Machine Learning technique to the detection engine, which recognizes attack traffic in an online way (not to store and analyze after), re-writing IDS rules on the fly. Experiments were done using the Dockemu emulation tool with Linux Containers, IPv6 and OLSR as routing protocol, leading to promising results.
Internet of Things (IoT) will be emerged over many of devices that are dynamically networked. Because of distributed and dynamic nature of IoT, designing a recommender system for them is a challenging problem. Recently, cognitive systems are used to design modern frameworks in different types of computer applications such as cognitive radio networks and cognitive peer-to-peer networks. A cognitive system can learn to improve its performance while operating under its unknown environment. In this paper, we propose a framework for cognitive recommender systems in IoT. To the best of our knowledge, there is no recommender system based on cognitive systems in the IoT. The proposed algorithm is compared with the existing recommender systems.
Different wireless Peer-to-Peer (P2P) routing protocols rely on cooperative protocols of interaction among peers, yet, most of the surveyed provide little detail on how the peers can take into consideration the peers' reliability for improving routing efficiency in collaborative networks. Previous research has shown that in most of the trust and reputation evaluation schemes, the peers' rating behaviour can be improved to include the peers' attributes for understanding peers' reliability. This paper proposes a reliability based trust model for dynamic trust evaluation between the peers in P2P networks for collaborative routing. Since the peers' routing attributes vary dynamically, our proposed model must also accommodate the dynamic changes of peers' attributes and behaviour. We introduce peers' buffers as a scaling factor for peers' trust evaluation in the trust and reputation routing protocols. The comparison between reliability and non-reliability based trust models using simulation shows the improved performance of our proposed model in terms of delivery ratio and average message latency.
Different wireless Peer-to-Peer (P2P) routing protocols rely on cooperative protocols of interaction among peers, yet, most of the surveyed provide little detail on how the peers can take into consideration the peers' reliability for improving routing efficiency in collaborative networks. Previous research has shown that in most of the trust and reputation evaluation schemes, the peers' rating behaviour can be improved to include the peers' attributes for understanding peers' reliability. This paper proposes a reliability based trust model for dynamic trust evaluation between the peers in P2P networks for collaborative routing. Since the peers' routing attributes vary dynamically, our proposed model must also accommodate the dynamic changes of peers' attributes and behaviour. We introduce peers' buffers as a scaling factor for peers' trust evaluation in the trust and reputation routing protocols. The comparison between reliability and non-reliability based trust models using simulation shows the improved performance of our proposed model in terms of delivery ratio and average message latency.
Online social networks are attracting billions of nowadays, both on a global scale as well as in social enterprise networks. Using distributed hash tables and peer-to-peer technology allows online social networks to be operated securely and efficiently only by using the resources of the user devices, thus alleviating censorship or data misuse by a single network operator. In this paper, we address the challenges that arise in implementing reliably and conveniently to use distributed data structures, such as lists or sets, in such a distributed hash-table-based online social network. We present a secure, distributed list data structure that manages the list entries in several buckets in the distributed hash table. The list entries are authenticated, integrity is maintained and access control for single users and also groups is integrated. The approach for secure distributed lists is also applied for prefix trees and sets, and implemented and evaluated in a peer-to-peer framework for social networks. Evaluation shows that the distributed data structure is convenient and efficient to use and that the requirements on security hold.