The existing LTE mobile system uses the vertical model to handle the session-based security management. However, the goal of this paper is to propose a packet key-based security management scheme on the blockchain control plane to enhance the existing session key-based security scheme and overcome the limitation that the existing vertical model, as well as the Software-Defined Networking (SDN) based horizontal model, confronts within solving end-to-end security management. The proposed blockchain-based security management (BSM) scheme enables each peer to easily obtain the necessary parameters required to manage the packet key-based security system. The important features of the BSM scheme include the renewal process, which enables the different packet data streams to use completely different security parameters for the security management. In addition, because even blind values cannot be exposed to the possible attackers, our BSM scheme guarantees very secure end-to-end data transfer against active attacks such as falsification of data and transactions. Finally, this paper compares the BSM scheme with the existing vertical model to prove the advantageous effects on latency.
Wireless Virtualization (WiVi) is emerging as a new paradigm to provide high speed communications and meet Quality-of-Service (QoS) requirements of users while reducing the deployment cost of wireless infrastructure for future wireless networks. In WiVi, Wireless Infrastructure Providers (WIPs) sublease their RF channels through slicing to Mobile Virtual Network Operators (MVNOs) based on their Service Level Agreements (SLAs) and the MVNOs independently provide wireless services to their end users. This paper investigates the wireless network virtualization by leveraging both Blockchain technology and machine learning to optimally allocate wireless resources. To eliminate double spending (aka over-committing) of WIPs' wireless resources such as RF channels, Blockchain - a distributed ledger - technology is used where a reputation is used to penalize WIPs with past double spending habit. The proposed reputation based approach helps to minimize extra delay caused by double spending attempts and Blockchain operations. To optimally predict the QoS requirements of MVNOs for their users, linear regression - a machine learning approach - is used that helps to minimize the latency introduced due to (multiple wrong) negotiations for SLAs. The performance evaluation of the proposed approach is carried out by using numerical results obtained from simulations. Results have shown that the joint Blockchain and machine learning based approach outperforms the other approaches.
Caching and sharing contents among mobile devices via wireless device-to-device (D2D) communications is a promising way to offload data traffic. In order to encourage more content sharing among mobile devices, we propose a blockchain incentive scheme in this paper, where the base station (BS) can allocate computing power to mine blockchain in a period of time and give this mining profit to the mobile devices that share contents with others via D2D communication. In order to maximize the total profit, we develop the caching placement schemes considering different relationships between the allocated computing power and the shared data size. For the linear relationship, we can obtain the closed form expression of the optimal caching scheme and find that the mobile device prefers to cache the popular contents. For the nonlinear relationship, the optimal problem can be effectively solved by difference of convex (DC) programming and the results reveal that the mobile device prefers to caching different contents.
Mark A. Graham, Ayalvadi Ganesh, Robert J. Piechocki
The emergence of new connectivity services for automated transportation marks a paradigm shift for the operation of wireless networks. Furthermore, the advent of blockchain technology promises to enable a plethora of smart mobility services, which are not contingent on any central authorities. Concepts such as distributed ledger require efficient and reliable data dissemination between vehicles. Traditional techniques based on Automatic Repeat Request (ARQ) are well known to scale poorly in all-cast networks due to the feedback implosion problem. Fountain and network coding techniques are arguably the most promising alternative solutions. In this paper we derive new analytical bounds on transmit message lengths and quantify bandwidth delay trade-offs for fountain coding based data dissemination for CAVs.
In this thesis, we present a private distributed ledger system, DLedger, designed for wireless meshed Named Data Networking (NDN) protocol network. DLedger utilizes lightweight Proof-Of-Authentication as gating control mechanism combining data openness among the system peers with verifiable identity within the system. The lightweight nature of Proof-Of-Authentication makes it friendly for the ledger systems consisting of even the constrained Internet of Things (IoT) devices unlike "muscle show" approaches like Proof-Of-Work, Proof-Of-Space, etc. which are storage or computation intensive and combines data openness with anonymity (or pseudonymity). Moreover, different from the popular blockchain-based ledger systems, DLedger utilizes a Directed Acyclic Graph as a fundamental data structure so that its operations can tolerate network partitions. Built over NDN, DLedger truly leverages from its data-centric nature to facilitate data dissemination in peer-to-peer heterogenous IoT networks. We conclude the thesis by reasoning our design through simulation results and discussing a real-world use case.
The fifth generation of mobile networks is rapidly evolving, fueled by the ever-growing mobile traffic over recent years. Ultra-reliable and low latency provisioning of services with ranging contextual parameters mapped to highly fluctuating levels of quality of service and quality of user experience, render the optimum operation point of the future networks unsustainable. Network coding is emerging once more as a potential key enabler for optimizing bandwidth requirements and energy consumption in highly dense mobile network environments. Nonetheless, network coding deployments still need to consider security vulnerabilities and their countermeasures, before they can be adapted as part of the emerging mobile network deployments. This paper studies the performance of random linear network coding for wireless mobile networks with an emphasis on pollution attacks while proposing a novel blockchain based message authentication scheme in order to minimize delays and signalling costs.
The device-to-device (D2D) communication is one of the promising technologies of the future Internet of Things (IoT), but its security-related issues remain challenging. The block-chain is considered to be a secure and reliable distributed ledger, so we can treat the device user equipment (D-UE) request for the reusing resources of cellular user equipment (C-UE) as a transaction and put it into a transaction pool, then package the record into the block-chain. In this paper, we study the D2D communication resource allocation scheme based on sparse code multiple access (SCMA). Firstly, the system's interference model and block-chain-based transaction flow are analyzed. Then we propose the optimization problem so that C-UE can get the maximum revenue by sharing its resources to D-UE. This problem is NP-hard, so we propose a heuristic algorithm based on semi-definite relaxation (SDR) programming to solve it. Finally, the performance of the proposed algorithm is verified by simulation of different system parameters.
Despite growing adoption of cryptocurrencies, making fast payments at scale remains a challenge. Payment channel networks (PCNs) such as the Lightning Network have emerged as a viable scaling solution. However, completing payments on PCNs is challenging: payments must be routed on paths with sufficient funds. As payments flow over a single channel (link) in the same direction, the channel eventually becomes depleted and cannot support further payments in that direction; hence, naive routing schemes like shortest-path routing can deplete key payment channels and paralyze the system. Today's PCNs also route payments atomically, worsening the problem. In this paper, we present Spider, a routing solution that "packetizes" transactions and uses a multi-path transport protocol to achieve high-throughput routing in PCNs. Packetization allows Spider to complete even large transactions on low-capacity payment channels over time, while the multi-path congestion control protocol ensures balanced utilization of channels and fairness across flows. Extensive simulations comparing Spider with state-of-the-art approaches shows that Spider requires less than 25% of the funds to successfully route over 95% of transactions on balanced traffic demands, and offloads 4x more transactions onto the PCN on imbalanced demands.
Named Data Networking is built with security which requires each named Data object to be digitally signed by its producer. Thus, the NDN project has proposed a key management model on NDN testbed for verification of the Data packet to be immune to distributing poisoned content. However, in practice, this model poses two challenges for verifying fake content: (1) the centralized architecture easily leads to a single point of failure, especially when the root key fails, its difficult to verify the keys across sites due to the lack of trust between them, and (2) excessive overhead of certificate chain traversal when verifying signature. This paper first proposes a blockchain-based key management scheme in NDN to address the problem of lack of mutual trust between sites without trust anchors. Specifically, all site nodes form a permissioned blockchain for storing public key hashes to ensure the authenticity, and the proxy gateway participates in verifying to reduce excessively frequent communication between the router and the blockchain. In addition, the NDN public key content object and the scheme of their storage, verification, and revocation are redesigned. The result of our analysis and evaluation shows that the proposed scheme is capable of supporting less verification numbers and higher verification efficiency.
Traditional centralized commerce on the Internet relies on trusted third parties to process electronic payments. It suffers from the weakness of the trust-based model. A pure decentralized mechanism called blockchain tackles the above problem and has become a hot research area. However, since each node in a blockchain system needs to store all transactions of the other nodes, as time continues, the storage room required to store the entire blockchain will be huge. Therefore, the current storage mechanism needs to be revised to cater to the rapidly increasing need for storage. Network coded (NC) distributed storage (DS) can significantly reduce the required storage room. This paper proposes a NC-DS framework to store the blockchain and proposes corresponding solutions to apply the NC-DS to the blockchain systems. Analysis shows that the proposed scheme achieves significant improvement in saving storage room.
Payment channels secured with cryptocurrency as collateral enable users to make many transactions with few blockchain broadcasts. Networks of payment channels have emerged as a proposed solution to Bitcoin’s scaling problem. Since the proposal of the first payment channel network, the Lightning Network, alternatives promising significant improvements, such as the Sprites protocol, have been proposed. Without at-scale implementations to analyze in situ, it is difficult to make meaningful comparisons of payment channel network protocols. In order to bridge this gap, we introduce a new simulation framework that can be used to evaluate how different payment channel network protocols will perform in both the expected and worst cases. \n \nOur framework is generic and accommodates benchmarking across different variants of payment channel network protocols, network topologies, routing algorithms, and user behaviors. User spending behavior in our payment channel network simulator is generated based on behavioral modeling techniques used in credit card fraud research. Our simulation is the first payment channel network simulator to seed user behaviors with data from real-world credit card users. \n \nOur framework can be used to evaluate expected case performance and resiliency to attacks across different payment channel network protocols and routing algorithms. We demonstrate the utility of our framework through comparisons of the Lightning Network to Sprites. We also compare the proposed decentralized routing algorithm, Flare, to an ideal centralized routing algorithm. Our results reveal that if spending behaviors are similar to those of credit card users, scale-free network topologies achieve higher throughput and resiliency compared to small-world networks. We also confirm that the Sprites protocol enjoys numerous advantages over the Lightning Network including smaller durations, shorter path length payments, and greater resiliency, all of which are most significant in decentralized topologies using decentralized routing algorithms.
Blockchain provides a new approach for participants to maintain reliable databases in untrusted networks without centralized authorities. However, there are still many serious problems in real blockchain systems in IP network such as the lack of support for multicast and the hierarchies of status. In this paper, we design a bitcoin-like blockchain system named BlockNDN over Named Data Networking and we implement and deploy it on our cluster as well. The resulting design solves those problems in IP network. It provides completely decentralized systems and simplifies system architecture. It also improves the weak-connectivity phenomenon and decreases the broadcast overhead.
This paper discusses novel joint (intracell and intercell) resource allocation algorithms for self-organized interference coordination in multicarrier multiple-input multiple-output (MIMO) small cell networks. The proposed algorithms enable interference coordination autonomously, over multiple degrees of freedom, such as base station transmit powers, transmit precoders, and user scheduling weights. A generic$\alpha$-fair utility maximization framework is considered to analyze performance-fairness tradeoff and to quantify the gains achievable in interference-limited networks. The proposed scheme involves limited inter-base station signaling in the form of two step (power and precoder) pricing. Based on this decentralized coordination, autonomous power and precoder update decision rules are considered, leading to algorithms with different characteristics in terms of user data rates, signaling load, and convergence speed. Simulation results in a practical setting show that the proposed pricing-based self-organization can achieve up to$100\%$improvement in cell-edge data rates when compared to baseline optimization strategies. Furthermore, the convergence of the proposed algorithms is also proved theoretically.
The flow of information among people in today's world is essential. People need to exchange data, but they also need to store larger chunks of data for future retrieval. Various business schemes have grown by feeding themselves on these assumptions. Some of them provide the needed infrastructure, such as, cables or wireless base stations in case of GSM/LTE networks, while others provide complementary storage capabilities (cloud storage services). In this paper, we introduce a Fully Distributed GRIDNET protocol (FD-GRIDNET). It facilitates a solution to a problem of motivating users to intercede in a data exchange. MANET/DTN networks were envisioned as a target environment, however we do not restrain our protocol by design only to such. FD-GRIDNET is the first fully distributed data exchange protocol, which rewards intermediaries with a cryptocurrency, one created on behalf of the described communication system itself. It constitutes a communication system with a closed economy cycle, where acting as a router earns cryptocurrency, which in turn can be used for one's own needs, such as, but not limited to - data transmission. Indeed, FD-GRIDNET can be said to facilitate a cryptocurrency of its own. It builds upon a proof-of-work concept, but introduces elements of proof-of-stake as well.
User, content, and device names as a security primitive have been an attractive approach especially in the context of Information-Centric Networking (ICN) architectures. We leverage Hierarchical Identity Based Encryption (HIBE) to build (content) name-based security mechanisms used for securely distributing content. In contrast to similar approaches, in our system each user maintains his own Private Key Generator used for generating the master secret key and the public system parameters required by the HIBE algorithm. This way our system does not suffer from the key escrow problem, which is inherent in many similar solutions. In order to disseminate the system parameters of a content owner in a fully distributed way, we use blockchains, a distributed, community managed, global list of transactions.
Today's Internet is full of applications by which users share potentially private information with each other. Recently, the privacy concerns of users are rising and users gradually become more suspicious with respect to the use of their (personal) information. In this thesis, we aim at bringing secure multi-party computation closer to common Internet users. The main goal is to design and implement privacy-preserving reconciliation-based applications for multiple users which are secure against passive and active attackers. Additionally, our solutions should be efficient enough to be practical and usable enough even for non-technical users.As a main contribution in theory, we present different privacy-preserving multi-party reconciliation protocols based on an additively homomorphic cryptosystem that are secure against passive attackers (semi-honest model). We also propose reconciliation protocols that are secure against active attackers (malicious model) by applying zero-knowledge proof techniques. The stronger security model comes at the price of efficiency. As a prerequisite, we develop several novel cryptographic tools in the areas of privacy-preserving set operations and zero-knowledge proofs of knowledge. We also analyze to what extent fully homomorphic cryptosystems can be used for multi-party privacy-preserving reconciliation protocols. As a main contribution in practice, we introduce SMC-MuSe, a framework for Secure Multi-Party Computation on MultiSets. SMC-MuSe is a carefully designed framework for secure multi-party computation including an implementation of different cryptographic components, a support infrastructure, multi-party privacy-preserving reconciliation protocols, and two user-friendly applications for the desktop and mobile environment. We also evaluate the efficiency of the SMC-MuSe framework. In particular, we measure the computation and communication overhead of all implemented components within the SMC-MuSe framework. As a third line of work, we propose different application scenarios in the areas of event scheduling, e-voting, and electronic auctions for reconciliation protocols. We examine the practicability of one particular user-friendly application of SMC-MuSe by conducting a user study on our Android application Prefer. The user study shows that Prefer is a useful and very interesting application for today's smartphone users. Finally, we show the potential of reconciliation protocols for common Internet users by conducting a user study on privacy-preserving reconciliation in the Internet. The user study shows that our reconciliation protocols are useful in different application scenarios for common Internet users.
Majed Haddad, Eitan Altman, Sana Ben Jemaa, Salah Eddine Elayoubi · 5 authors
Distributing Radio Resource Management (RRM) in heterogeneous wireless networks is an important research and development axis that aims at reducing network complexity, signaling, and processing load in heterogeneous environments. Performing decision-making involves incorporating cognitive capabilities into the mobiles such as sensing the environment and learning capabilities. This falls within the larger framework of cognitive radio (Mitola, 2000) and self-organizing networks (3GPP, 2008). In this context, RRM decision making can be delegated to mobiles by incorporating cognitive capabilities into mobile handsets, resulting in the reduction of signaling and processing burden. This may however result in inefficiencies such as those known as the “Tragedy of commons” (Hardin, 1968) that are inherent to equilibria in non-cooperative games. Due to the concern for efficiency, centralized network architectures and protocols keep being considered and being compared to decentralized ones. From the point of view of the network architecture, this implies the co-existence of network-centric and terminal-centric RRM schemes. Instead of taking part within the debate among the supporters of each solution, the authors propose a hybrid scheme where the wireless users are assisted in their decisions by the network that broadcasts aggregated load information (Elayoubi, 2010). At some system’s states, the network manager may impose his decisions on the network users. In other states, the mobiles may take autonomous actions in reaction to information sent by the network. Specifically, the authors derive analytically the utilities related to the Quality of Service (QoS) perceived by mobile users and develop a Bayesian framework to obtain the equilibria. They then analyze the performance of the proposed scheme in terms of achievable throughput (for both mobile terminals and the network) and evaluate the price of anarchy which measures how good the system performance is when users play selfishly instead of playing to achieve the social optimum (Johari, 2004). Numerical results illustrate the advantages of using the hybrid game framework in a network composed of HSDPA and 3G LTE system that serve streaming and elastic flows. Finally, this chapter addresses current questions regarding the integration of the proposed hybrid Stackelberg scheme in practical wireless systems, leading to a better understanding of actual cognitive radio gains.
In this paper, we present a delay based routing algorithm for ad hoc wireless networks. In an ad hoc environment there is no wired infrastructure and the mobile hosts work as a router to maintain the status about the connectivity. A mobile ad hoc network is an autonomous collection of mobile users (nodes) that communicates over relatively bandwidthconstrained wireless links. Each node is equipped with wireless receivers and transmitters using antennas that may be omnidirectional, highly directional, or possibly steer able. Due to nodal mobility, the network topology may change rapidly and unpredictably over time. The network is decentralized, where network organization and message delivery must be executed by the nodes themselves, i.e., routing functionally will be incorporated into mobile nodes. The design of the network protocols for mobile ad hoc network is a complex issue. These networks need efficient distributed algorithm to determine network organization (connectivity), link scheduling, and routing. But, the existing routing algorithms designed for ad hoc wireless networks have slow response, excessive overhead and become unsuitable under the above considerations. The full approach, for referring the internal state of the network relies on Round Trip Time (RTT) measurements only. We consider the RTT mean and RTT variance as fuzzy input variables and delay as a fuzzy output variable. Under such condition the performance of the proposed algorithm is tested. It is shown that under these conditions the algorithm gives better results. The proposed routing algorithm is simulated in MATLAB 6.5.
I Wayan Mustika, Koji Yamamoto, Hidekazu Murata, Susumu Yoshida
This paper proposes a game-theoretic approach for self-organized resource allocation in OFDMA femtocells with closed access configuration. The objective of the proposed scheme is to overcome the interference problem caused by co-channel operation of femtocells in an existing macrocell network using a self-organization capability of femto users. Inspired by the emerging cognitive radio technology, each femto user acts as an autonomous entity and attempts to select the most appropriate subset of resource blocks in a decentralized manner in order to mitigate the cross- and co-tier interference. Such a self-organized resource allocation scheme can be modeled as a potential game, which guarantees the convergence to a Nash equilibrium as long as distributed sequential play based on the best response strategy is adopted. Simulation results show that the proposed scheme improves the capacity of the femtocell network, while minimizing the performance degradation of the macrocell network.
Francisco Bernardo, R. Agustı́, J. Pérez-Romero, O. Sallent
This paper presents a decentralized framework for dynamic spectrum assignment in multicell orthogonal frequency division multiple access (OFDMA) networks. The proposed framework allows each cell to autonomously decide the frequency resources it should use through a procedure that incorporates concepts from self-organization and machine learning in multiagent systems (MASs). Simulation results have been obtained for several scenarios, including both macrocells (MCs) and femtocells (FCs), revealing important improvements in terms of spectral efficiency and intercell interference mitigation over reference approaches, and close performance with the one obtained by a centralized strategy. Results also suggest that the framework would be practical for future FC cellular deployments where a high degree of independence of the network nodes is expected to reduce operational costs.
Thomas Elsner, Nhung T. H. Nguyen, Björn Scheuermann
WiFi sharing communities offer an attractive alternative to commercial hot-spots and cellular networks for users who seek Internet access while being away from home. The growing number of mobile devices with Internet usage capabilities has formed a basis for the establishment and growth of several such communities. However, critical security problems exist in all current WiFi sharing approaches because they employ a central operator. We show how to overcome these issues by decentralizing the community's organization structure and present radioActive WiFi, a system that implements this approach.
Rafael Pass, Wei-Lung Dustin Tseng, Douglas Wikström
We show that only languages in BPP have public-coin black-box zero-knowledge protocols that are secure under an unbounded (polynomial) number of parallel repetitions. This result holds both in the plain model (without any setup) and in the bare public key model (where the prover and the verifier have registered public keys). We complement this result by constructing a public-coin black-box zero-knowledge proof based on one-way functions that remains secure under any a priori bounded number of concurrent executions. A key step (of independent interest) in the analysis of our lower bound shows that any public-coin protocol, when repeated sufficiently in parallel, satisfies a notion of “resettable soundness” if the verifier picks its random coins using a pseudorandom function.
Oana-Mădălina Ciobotaru, Dominique Unruh, Michael Backes
Long-term security ensures that a protocol remains secure even in the future, when the adversarial computational power could, potentially, become unlimited. The notion of universal composability preserves the security of a cryptographic protocol when it is used in combination with any other protocols, in possibly complex systems. The area of long-term universally composable secure protocols has been developed mostly by Müller-Quade and Unruh. Their research conducted so far has shown the existence of secure long-term UC commitments under general cryptographic assumptions, thus without having an emphasis on the efficiency of the protocols designed. Building on their work and using very efficient zero-knowledge proofs of knowledge from [CL02], this thesis presents a new long-term universally composable secure commitment protocol that is both efficient and plausible to use in practice.