Peer-assisted delivery network (PDN) can significantly reduce the bandwidth cost incurred by traditional CDN services. However, it is unclear whether they have been deployed extensively and their security implications have never been investigated thoroughly. In this paper, we report the first effort to address this issue through an automatic pipeline to discover real-world PDN services and their customers, and a PDN analysis framework to test the potential security and privacy risks of these services. Our results have revealed the extensive adoption of PDN across the Internet, especially by Chinese video platforms. Most importantly, our analysis on these PDN services has brought to light a series of novel security vulnerabilities, i.e., free riding of PDN services, video segment pollution, and unreported privacy risks, i.e., resource squatting and extensive leakage of video viewers' IPs. We have responsibly disclosed these security risks to relevant PDN providers which in turn have well acknowledged our findings.

In the age of pervasive computing, traditionally centralized cloud storage (CCS) services may not fit in well due to their centralized architecture, limited worldwide availability, high expense, and security and privacy concerns. To address these issues, decentralized cloud storage (DCS) services emerged recently. However, previous works focus on analyzing the technical design of DCS services, e.g., their incentive mechanisms. Little is known regarding how well these DCS services work in real-world operations. In this paper, we fill this gap by providing the first empirical measurement of Storj, one of the most extensive in-operation decentralized cloud storage services, focusing on its ecosystem, performance, and security implications. Our study is made possible through multiple measurement techniques to automatically capture storage nodes, profile Storj's quality of service, understand co-located network threats, and evaluate potential attacks in a simulated environment. Leveraging these techniques, a set of insightful findings have been distilled. Particularly, we have observed over 32K storage nodes as well as 155K unique node IP addresses, which are widely distributed in 122 countries, 2,418 ASNs, and 205 /8 IPv4 prefixes. Regarding performance, storage customers located in Europe or the United States tend to enjoy a better storage performance than those in Asia-Pacific, likely due to the imbalanced distribution of storage nodes in different regions. Lastly, what is concerning is that 4.48% of IPs of storage nodes were found to have been associated with various malicious activities, especially botnets and cryptomining. Another vulnerability is that a malicious storage node could exploit multiple channels to boost its storage reputation while demoting that of benign nodes.

Database driven dynamic spectrum sharing is one of the most promising dynamic spectrum access (DSA) solution to address the spectrum scarcity issue. In such a database-driven DSA system, the centralized spectrum management infrastructure, called spectrum access system (SAS), collects sensitive operational data of both incumbent users (IUs) and secondary users (SUs), which makes privacy protection critical in this paradigm. However, the few existing solutions rely on online trusted third party, which requires extra infrastructure and brings the risk of single point failure. To address the shortcomings of existing solutions, we propose a privacy enhanced and database-driven dynamic spectrum sharing (PeDSS) framework in this paper, which preserves the privacy for both IUs and SUs in database-driven DSA systems without the need for online trusted third party. Privacy for both IUs and SUs are formally defined and analyzed, and experiment results show that SAS under PeDSS is able to handle a single spectrum request in 0.51 ms on average, which is three orders of magnitude faster than prior arts.

Dynamic spectrum access (DSA) technique has emerged as a fundamental approach to mitigate the spectrum scarcity problem. As a key form of DSA, the government is proposing to release more federal spectrum for sharing with commercial wireless users. However, the flourish of federal-commercial sharing hinges upon how the federal privacy is managed. In current DSA proposals, the sensitive exclusion zone (E-Zone) information of federal incumbent users (IUs) needs to be shared with a spectrum access system (SAS) to realize spectrum allocation. However, SAS is not necessarily trust-worthy for holding the sensitive IU E-Zone data, especially considering that FCC allows some industry third parties (e.g., Google) to operate SAS for better efficiency and scalability. Therefore, the current proposals dissatisfy the IUs' privacy requirement. To address the privacy issue, this paper presents an IU-privacy-preserving SAS (IP-SAS) design, which realizes the spectrum allocation process through secure computation over ciphertext based on homomorphic encryption so that none of the IU EZone information is exposed to SAS. This paper also proposes mechanisms to prevent malicious parties from compromising IP-SAS. We prove the privacy-preserving properties of IP-SAS and demonstrate the scalability and practicality of IP-SAS using experiments based on real-world data. Evaluation results show that IP-SAS can respond an SU's spectrum request in 1.25 seconds with communication overhead of 17.8 KB.

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 need to be shared with a central server. However, the operation data of government IUs are often classified information and the SU operation data may also be commercial secrets. The current system design dissatisfies the privacy requirement of both IUs and SUs, since the central server is not necessarily trustworthy 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 s with communication overhead of less than 4 MB.

Dynamic spectrum access (DSA) technique has emerged as a fundamental approach in improving spectrum utilization to mitigate the spectrum scarcity problem. As a key form of DSA, government is proposing to release more federal spectrum for sharing with commercial wireless users. However, the flourish of federal-commercial sharing hinges upon how federal privacy issues are managed. In current DSA proposals, the sensitive operation information of federal incumbent users (IUs) needs to be shared with a dynamic spectrum access system (SAS) to realize spectrum allocation. However, SAS is not necessarily trust-worthy for holding such sensitive IU data, especially considering that FCC allows some industry third parties (e.g., Google) to operate SAS for better efficiency and scalability. Therefore, the current proposals dissatisfy the IUs' privacy requirement. To address the privacy issues, this paper presents an IU-privacy-preserving SAS (IP-SAS) design, which realizes the spectrum allocation process through secure computation over ciphertext based on homomorphic encryption so that none of the IU operation information is exposed to SAS.

The legacy concept of exclusion zones (EZs) is inept at enabling efficient utilization of fallow spectrum by secondary users (SUs), since legacy EZs are static and overly-conservative. The notion of a static EZ implies that it has to protect incumbent users (IUs) from the union of likely interference scenarios, leading to a worst-case, conservative solution. In this paper, we propose the concept of dynamic, multi-tier EZs, which takes advantage of participatory spectrum sensing carried out by SUs to support efficient database-driven spectrum sharing while protecting IUs against SU-induced aggregate interference. Specifically, the database directly incentivizes SUs to participate in spectrum sensing, which augments geolocation database by defining smaller EZs with dynamic boundaries and creating additional spectrum access opportunities for SUs. We propose an incentive mechanism based on a two-level game-theoretic model, in which the database conducts dynamic pricing in a first-level Stackelberg game in the presence of SUs who strategically contribute to spectrum sensing in a second-level stochastic game. The existence of an equilibrium solution is proven. According to our findings, the proposed incentive mechanism for the concept of dynamic, multi-tier EZs is effective to improve spectrum utilization efficiency while guaranteeing incumbent protection.

Dynamic spectrum access (DSA) technique has emerged as a fundamental approach to mitigate the spectrum scarcity problem. As a key form of DSA, government is proposing to release more federal spectrum for sharing with commercial wireless users. However, the flourish of federal-commercial sharing hinges upon how the federal privacy is managed. In current DSA proposals, the sensitive exclusion zone (E-Zone) information of federal incumbent users (IUs) needs to be shared with a spectrum access system (SAS) to realize spectrum allocation. However, SAS is not necessarily trust-worthy for holding the sensitive IU E-Zone data, especially considering that FCC allows some industry third parties (e.g., Google) to operate SAS for better efficiency and scalability. Therefore, the current proposals dissatisfy the IUs' privacy requirement. To address the privacy issue, this paper presents an IU-privacy-preserving SAS (IP-SAS) design, which realizes the spectrum allocation process through secure computation over ciphertext based on homomorphic encryption.

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.

Cognitive Radio (CR) is an intelligent radio technology to boost spectrum utilization and is likely to be widely spread in the near future. However, its flexible software-oriented design may be exploited by an adversary to control CR devices to launch large scale attacks on a wide range of critical wireless infrastructures. To proactively mitigate the potentially serious threat, this paper presents MadeCR, a Correlation-based Malware detection system for CR. MadeCR exploits correlations among CR applications' component actions to detect malicious behaviors. In addition, a significant contribution of the paper is a general experimentation method referred to as mutation testing to comprehensively evaluate the effectiveness of the anomaly detection method against a large number of artificial malware cases. Evaluation shows that MadeCR detects malicious behaviors within 1.10s at an accuracy of 94.9%.

Dynamic spectrum access (DSA) technique has been widely accepted as a crucial solution to mitigate the potential spectrum scarcity problem. As a key form of DSA, government is proposing to release more federal spectrum for sharing with commercial wireless users. However, the flourish of federal-commercial sharing hinges upon how privacy issues are managed. In current DSA proposals, the sensitive operation parameters of both federal incumbent users (IUs) and commercial secondary users (SUs) need to be shared with the dynamic spectrum access system (SAS) to realize efficient spectrum allocation. Since SAS is not necessarily operated by a trusted third party, the current proposals dissatisfy the privacy requirement of both IUs and SUs. To address the privacy issues, this paper presents a privacy-preserving SAS design, which realizes the complex spectrum allocation decision process of DSA through secure computation over ciphertext based on homomorphic encryption, thus none of the IU or SU operation parameters are exposed to SAS.

No abstract available.