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1. Edge computing framework for distributed smart applications

   https://doi.org/10.1109/UIC-ATC.2017.8397448  

   Liu, Kaikai; Gurudutt, Abhishek; Kamaal, Tejeshwar; Divakara, Chinmayi; Prabhakaran, Praveen (August 2017, The IEEE Smart World Congress 2017 (IEEE SWC 2017))

   The rapid growth in technology and wide use of internet has increased smart applications such as intelligent transportation control system, and Internet of Things, which heavily rely on an efficient and reliable connectivity network. To overcome high bandwidth work load on the network, as well as minimize latency for real-time applications, the computation can be moved from the central cloud to a distributed edge cloud. The edge computing benefits various smart applications that uses distributed network for data analytics and services. Different from the existing cloud management solutions, edge computing needs to move cloud management services towards distributed heterogeneous edge nodes for multi-tenant user applications. However, existing cloud management services do not offer remote deployment of multi-tenant user applications on the cloud of edge nodes. In this paper, we propose a practical edge cloud software framework for deploying multi-tenant distributed smart applications. Having multiple distributed end nodes, auto discovery of all active end nodes is required for deploying multi-tenant user applications. However, existing cloud solutions require either private network or fixed IP address, which is not achievable for the distributed edge nodes. Most of the edge nodes connected through the public internet without fixed IP, and some of them even connect through IEEE 802.15 based sensor networks. We propose to build a software platform to manage the distributed edge nodes as well as support services to deploy and launch isolated, multi-tenant user applications through a lightweight container. We propose an architectural solution to remotely access edge cloud management services through intermittent internet connections. We open sourced our whole set of software solutions, and analyzed the major performance metrics of the edge cloud platform. 

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2. Ephemeral Exit Bridges for Tor

   Zhang, Zhao; Vaidya, Tavish; Subramanian, Kartik; Zhou, Wenchao; Sherr, Micah (July 2020, 50th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2020))

   This paper examines an existential threat to Tor— the increasing frequency at which websites apply discriminatory behavior to users who arrive via the anonymity network. Our main contribution is the introduction of Tor exit bridges. Exit bridges, constructed as short-lived virtual machines on cloud service providers, serve as alternative egress points for Tor and are designed to bypass server-side censorship. Due to the proliferation of managed cloud-based desktop services (e.g., Amazon Workspaces), there is already a surprisingly large fraction of web requests that originate in the cloud. Trivially disrupting exit bridges by blocking requests from the cloud would thus lead to significant collateral damage. Our experiments demonstrate that exit bridges effectively circumvent server-side blocking of Tor with low overhead. Ad- ditionally, we perform a cost-analysis of exit bridges and show that even a large-scale deployment can be done at low cost. 

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3. Multi-Tenant Cloud FPGA: A Survey on Security, Trust and Privacy

   https://doi.org/10.1145/3713078  

   Kawser_Ahmed, Muhammed; Panoff_Kealoha, Maximillian; Mandebi_Mbongue, Joel; Saha, Sujan Kumar; Nghonda_Tchinda, Erman; Mbua, Peter Esenju; Bobda, Christophe (January 2025, ACM Transactions on Reconfigurable Technology and Systems)

   With the growing demand for enhanced performance and scalability in cloud applications and systems, data center architectures are evolving to incorporate heterogeneous computing fabrics that leverage CPUs, GPUs, and FPGAs. Unlike traditional processing platforms like CPUs and GPUs, FPGAs offer the unique ability for hardware reconfiguration at run-time, enabling improved and tailored performance, flexibility, and acceleration. FPGAs excel at executing large-scale search optimization, acceleration, and signal processing tasks while consuming low power and minimizing latency. Major public cloud providers, such as Amazon, Huawei, Microsoft, Alibaba, and others, have already begun integrating FPGA-based cloud acceleration services into their offerings. Although FPGAs in cloud applications facilitate customized hardware acceleration, they also introduce new security challenges that demand attention. Granting cloud users the capability to reconfigure hardware designs after deployment may create potential vulnerabilities for malicious users, thereby jeopardizing entire cloud platforms. In particular, multi-tenant FPGA services, where a single FPGA is divided spatially among multiple users, are highly vulnerable to such attacks. This paper examines the security concerns associated with multi-tenant cloud FPGAs, provides a comprehensive overview of the related security, privacy and trust issues, and discusses forthcoming challenges in this evolving field of study. 

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4. COMET: Distributed Metadata Service for Multi-cloud Experiments

   https://doi.org/10.1109/ICNP.2019.8888138  

   Thareja, Komal; Wang, Cong; Ruth, Paul; Mandal, Anirban; Baldin, Ilya; Stealey, Michael (October 2019, 2019 IEEE 27th International Conference on Network Protocols (ICNP))

   A majority of today's cloud services are independently operated by individual cloud service providers. In this approach, the locations of cloud resources are strictly constrained by the distribution of cloud service providers' sites. As the popularity and scale of cloud services increase, we believe this traditional paradigm is about to change toward further federated services, a.k.a., multi-cloud, due to the improved performance, reduced cost of compute, storage and network resources, as well as increased user demands. In this paper, we present COMET, a lightweight, distributed storage system for managing metadata on large scale, federated cloud infrastructure providers, end users, and their applications (e.g. HTCondor Cluster or Hadoop Cluster). We showcase use case from NSF's, Chameleon, ExoGENI and JetStream research cloud testbeds to show the effectiveness of COMET design and deployment. 

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5. An Empirical Analysis of the Commercial VPN Ecosystem

   https://doi.org/10.1145/3278532.3278570  

   Khan, Mohammad Taha; DeBlasio, Joe; Voelker, Geoffrey M.; Snoeren, Alex C.; Kanich, Chris; Vallina-Rodriguez, Narseo (October 2018, Proceedings of the Internet Measurement Conference (IMC'18))

   Global Internet users increasingly rely on virtual private network (VPN) services to preserve their privacy, circumvent censorship, and access geo-filtered content. Due to their own lack of technical sophistication and the opaque nature of VPN clients, however, the vast majority of users have limited means to verify a given VPN service’s claims along any of these dimensions. We design an active measurement system to test various infrastructural and privacy aspects of VPN services and evaluate 62 commercial providers. Our results suggest that while commercial VPN services seem, on the whole, less likely to intercept or tamper with user traffic than other, previously studied forms of traffic proxying, many VPNs do leak user traffic—perhaps inadvertently—through a variety of means. We also find that a non-trivial fraction of VPN providers transparently proxy traffic, and many misrepresent the physical location of their vantage points: 5–30% of the vantage points, associated with 10% of the providers we study, appear to be hosted on servers located in countries other than those advertised to users. 

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