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The recent privacy incidents reported in major media about global social networks raised real public concerns about centralized architectures. P2P social networks constitute an interesting paradigm to give back users control over their data and relations. While basic social network functionalities such as commenting, following, sharing, and publishing content are widely available, more advanced features related to information retrieval and recommendation are still challenging. This is due to the absence of a central server that has a complete view of the network. In this paper, we propose a new recommender system called P2PCF. We use collaborative filtering approach to recommend content in P2P social networks. P2PCF enables privacy preserving and tackles the cold start problem for both users and content. Our proposed approach assumes that the rating matrix is distributed within peers, in such a way that each peer only sees interactions made by her friends on her timeline. Recommendations are then computed locally within each peer before they are sent back to the requester. Our evaluations prove the effectiveness of our proposal compared to a centralized scheme in terms of recall and coverage.

Whenever a user tries communicating with another recipient on the Internet, vibrant information is sent over different networks until the information is intercepted or normally reaches the recipient. Precarious information crisscrossing networks is usually encrypted. In order to conceal the sender's identity, different implementations have proven successful -one of which is the invention of anonymous communication systems. There are many anonymous communication systems developed but, the Onion Router (Tor) is the greatest organized anonymous communication system, which offers online anonymity and privacy. There are a vast number of obstacles in security that have to be considered when deploying Tor. This paper thoroughly investigates and presents these security issues in Tor.

Application Layer Multicast (ALM) is considered as an attractive approach for implementing wide area multicast services. In ALM, multicast functionality is implemented at the edge instead of the core network (routers). As opposed to network-layer multicast, application layer multicast requires no infrastructure support and can be easily deployed in the Internet. In this paper, we propose a new efficient and scalable model for optimizing application layer multicast using HPM architecture (HPM: A novel hierarchical Peer-to-Peer model for lookup acceleration with provision of physical proximity). This approach benefits from P2P properties and characteristics. In this contribution, we consider our optimized tree construction algorithm simultaneously for each ring of HPM. The global tree construction algorithm is composed of two steps. In the first step, we construct a sub-tree for each ring; the second step is to build a global tree using sub sets of adjacent rings in HPM architecture. The proposed model inherits from main P2P attributes such as: scalability, fault tolerance characterized HPM. Preliminarily performance evaluations show that results are globally satisfactory, the depth of the resulting multicast tree is optimized.

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