Enabling Social Applications via Decentralized Social Data Management

An unprecedented information wealth produced by online social networks, further augmented by location/collocation data, is currently fragmented across different proprietary services. Combined, it can accurately represent the social world and enable novel socially-aware applications. We present Prometheus, a socially-aware peer-to-peer service that collects social information from multiple sources into a multigraph managed in a decentralized fashion on user-contributed nodes, and exposes it through an interface implementing non-trivial social inferences while complying with user-defined access policies. Simulations and experiments on PlanetLab with emulated application workloads show the system exhibits good end-to-end response time, low communication overhead and resilience to malicious attacks.Comment: 27 pages, single ACM column, 9 figures, accepted in Special Issue of Foundations of Social Computing, ACM Transactions on Internet Technolog

Storytelling Security: User-Intention Based Traffic Sanitization

Malicious software (malware) with decentralized communication infrastructure, such as peer-to-peer botnets, is difficult to detect. In this paper, we describe a traffic-sanitization method for identifying malware-triggered outbound connections from a personal computer. Our solution correlates user activities with the content of outbound traffic. Our key observation is that user-initiated outbound traffic typically has corresponding human inputs, i.e., keystroke or mouse clicks. Our analysis on the causal relations between user inputs and packet payload enables the efficient enforcement of the inter-packet dependency at the application level. We formalize our approach within the framework of protocol-state machine. We define new application-level traffic-sanitization policies that enforce the inter-packet dependencies. The dependency is derived from the transitions among protocol states that involve both user actions and network events. We refer to our methodology as storytelling security. We demonstrate a concrete realization of our methodology in the context of peer-to-peer file-sharing application, describe its use in blocking traffic of P2P bots on a host. We implement and evaluate our prototype in Windows operating system in both online and offline deployment settings. Our experimental evaluation along with case studies of real-world P2P applications demonstrates the feasibility of verifying the inter-packet dependencies. Our deep packet inspection incurs overhead on the outbound network flow. Our solution can also be used as an offline collect-and-analyze tool

Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments

Decentralized systems are a subset of distributed systems where multiple authorities control different components and no authority is fully trusted by all. This implies that any component in a decentralized system is potentially adversarial. We revise fifteen years of research on decentralization and privacy, and provide an overview of key systems, as well as key insights for designers of future systems. We show that decentralized designs can enhance privacy, integrity, and availability but also require careful trade-offs in terms of system complexity, properties provided, and degree of decentralization. These trade-offs need to be understood and navigated by designers. We argue that a combination of insights from cryptography, distributed systems, and mechanism design, aligned with the development of adequate incentives, are necessary to build scalable and successful privacy-preserving decentralized systems

The Reputation, Opinion, Credibility and Quality (ROCQ) Scheme

An implicit assumption of trust in the participants is at the basis of most Peer-to-Peer (P2P) networks. However, in practice, not all participants are benign or cooperative. Identifying such peers is critical to the smooth and effective functioning of a P2P network. In this paper, we present the ROCQ mechanism, a reputation-based trust management system that computes the trustworthiness of peers on the basis of transaction-based feedback. The ROCQ model combines four parameters: Reputation (R) or a peer's global trust rating, Opinion (O) formed by a peer's first-hand interactions, Credibility (C) of a reporting peer and Quality (Q) or the confidence a reporting peer puts on the judgement it provides. We then present a distributed implementation of our scheme over FreePastry, a structured P2P network. Experimental results considering different models for malicious behavior indicate the contexts in which the ROCQ scheme performs better than existing schemes