Biblio

Dynamic spectrum access (DSA) is a promising platform to solve the spectrum shortage problem, in which auction based mechanisms have been extensively studied due to good spectrum allocation efficiency and fairness. Recently, Sybil attacks were introduced in DSA, and Sybil-proof spectrum auction mechanisms have been proposed, which guarantee that each single secondary user (SU) cannot obtain a higher utility under more than one fictitious identities. However, existing Sybil-poof spectrum auction mechanisms achieve only Sybil-proofness for SUs, but not for primary users (PUs), and simulations show that a cheating PU in those mechanisms can obtain a higher utility by Sybil attacks. In this paper, we propose TSUNAMI, the first Truthful and primary user Sybil-proof aUctioN mechAnisM for onlIne spectrum allocation. Specifically, we compute the opportunity cost of each SU and screen out cost-efficient SUs to participate in spectrum allocation. In addition, we present a bid-independent sorting method and a sequential matching approach to achieve primary user Sybil-proofness and 2-D truthfulness, which means that each SU or PU can gain her maximal utility by bidding with her true valuation of spectrum. We evaluate the performance and validate the desired properties of our proposed mechanism through extensive simulations.

The US Federal Communications Commission (FCC) has recently mandated the database-driven dynamic spectrum access where unlicensed secondary users search for idle bands and use them opportunistically. The database-driven dynamic spectrum access approach is regarded for minimizing any harmful interference to licensed primary users caused by RF channel sensing uncertainties. However, when several secondary users (or several malicious users) query the RF spectrum database at the same time, spectrum server could experience denial of service (DoS) attack. In this paper, we investigate the Aggregated-Query-as-a-Secure-Service (AQaaSS) for querying RF spectrum database by secondary users for opportunistic wireless communications where selected number of secondary users aka grid leaders, query the database on behalf of all other secondary users, aka grid followers and relay the idle channel information to grid followers. Furthermore, the grid leaders are selected based on their both reputation or trust level and location in the network for the integrity of the information that grid followers receive. Grid followers also use the weighted majority voting to filter out comprised information about the idle channels. The performance of the proposed approach is evaluated using numerical results. The proposed approach gives lower latency (or same latency) to the secondary users and lower load (or same load) to the RF spectrum database server when more number of secondary users (or less number of secondary users) query than that of the server capacity.

In order to cater the growing spectrum demands of large scale future 5G Internet of Things (IoT) applications, Dynamic Spectrum Access (DSA) based networks are being proposed as a high-throughput and cost-effective solution. However the lack of understanding of DSA paradigm's inherent security vulnerabilities on IoT networks might become a roadblock towards realizing such spectrum aware 5G vision. In this paper, we make an attempt to understand how such inherent DSA vulnerabilities in particular Spectrum Sensing Data Falsification (SSDF) attacks can be exploited by collaborative group of selfish adversaries and how that can impact the performance of spectrum aware IoT applications. We design a utility based selfish adversarial model mimicking collaborative SSDF attack in a cooperative spectrum sensing scenario where IoT networks use dedicated environmental sensing capability (ESC) for spectrum availability estimation. We model the interactions between the IoT system and collaborative selfish adversaries using a leader-follower game and investigate the existence of equilibrium. Using simulation results, we show the nature of adversarial and system utility components against system variables. We also explore Pareto-optimal adversarial strategy design that maximizes the attacker utility for varied system strategy spaces.

Cloud-centric cognitive cellular networks utilize dynamic spectrum access and opportunistic network access technologies as a means to mitigate spectrum crunch and network demand. However, furnishing a carrier with personally identifiable information for user setup increases the risk of profiling in cognitive cellular networks, wherein users seek secondary access at various times with multiple carriers. Moreover, network access provisioning - assertion, authentication, authorization, and accounting - implemented in conventional cellular networks is inadequate in the cognitive space, as it is neither spontaneous nor scalable. In this paper, we propose a privacy-enhancing user identity management system using blockchain technology which places due importance on both anonymity and attribution, and supports end-to-end management from user assertion to usage billing. The setup enables network access using pseudonymous identities, hindering the reconstruction of a subscriber's identity. Our test results indicate that this approach diminishes access provisioning duration by up to 4x, decreases network signaling traffic by almost 40%, and enables near real-time user billing that may lead to approximately 3x reduction in payments settlement time.

Centralized spectrum management is one of the key dynamic spectrum access (DSA) mechanisms proposed to govern the spectrum sharing between government incumbent users (IUs) and commercial secondary users (SUs). In the current centralized DSA designs, the operation data of both government IUs and commercial SUs needs to be shared with a central server. However, the operation data of government IUs is often classified information and the SU operation data may also be commercial secret. The current system design dissatisfies the privacy requirement of both IUs and SUs since the central server is not necessarily trust-worthy for holding such sensitive operation data. To address the privacy issue, this paper presents a privacy-preserving centralized DSA system (P2-SAS), which realizes the complex spectrum allocation process of DSA through efficient secure multi-party computation. In P2-SAS, none of the IU or SU operation data would be exposed to any snooping party, including the central server itself. We formally prove the correctness and privacy-preserving property of P2-SAS and evaluate its scalability and practicality using experiments based on real-world data. Experiment results show that P2-SAS can respond an SU's spectrum request in 6.96 seconds with communication overhead of less than 4 MB.