Reliable and Efficient Way to Broadcast Messages in a Group by Trust-Based Broadcast (TBB) Scheme

Nowadays information systems are being shifted to distributed architectures, i.e. Grid and Peer-to-peer (P2P) models to obtain the benefits like scalability, autonomy, and fault-tolerance. We consider the P2P model as a fully distributed, scalable system, which is composed of peer processes (peers). Here, a group of multiple peers cooperate with each other. Peers have to efficiently and flexibly deliver messages to every peer of the group in P2P overlay networks. In order to efficiently and reliably broadcast messages in a scalable group, we take advantage of the multipoint relaying (MPR) mechanism. Here, each peer sends messages to only a subset of its acquaintances. However, if a peer which forwards messages to other peers is faulty, the peers cannot receive messages. In this paper, we newly discuss a trustworthiness-based broadcast (TBB) algorithm where only trustworthy peers forward messages. That is, untrustworthy peers are peers which cannot forward the messages due to some faults. Here, the transmission fault implied by faults of untrustworthy peers can be reduced. We evaluate the TBB algorithm in terms of the number of messages transmitted

Acquaintance Management Algorithm Based on the Multi-Class Risk-Cost Analysis for Collaborative Intrusion Detection Network

The collaborative intrusion detection network (CIDN) framework provides collaboration capability among intrusion detection systems (IDS). Collaboration selection is done by an acquaintance management algorithm. A recent study developed an effective acquaintance management algorithm by the use of binary risk analysis and greedy-selection-sort based methods. However, most algorithms do not pay attention to the possibility of wrong responses in multi-botnet attacks. The greedy-based acquaintance management algorithm also leads to a poor acquaintance selection processing time when there is a high number of IDS candidates. The growing number of advanced distributed denial of service (DDoS) attacks make acquaintance management potentially end up with an unreliable CIDN acquaintance list, resulting in low decision accuracy. This paper proposes an acquaintance management algorithm based on multi-class risk-cost analysis and merge-sort selection methods. The algorithm implements merge risk-ordered selection to reduce computation complexity. The simulation result showed the reliability of CIDN in reducing the acquaintance selection processing time decreased and increasing the decision accuracy

Design and Management of Collaborative Intrusion Detection Networks

In recent years network intrusions have become a severe threat to the privacy and safety of computer users. Recent cyber attacks compromise a large number of hosts to form botnets. Hackers not only aim at harvesting private data and identity information from compromised nodes, but also use the compromised nodes to launch attacks such as distributed denial-of-service (DDoS) attacks. As a counter measure, Intrusion Detection Systems (IDS) are used to identify intrusions by comparing observable behavior against suspicious patterns. Traditional IDSs monitor computer activities on a single host or network traffic in a sub-network. They do not have a global view of intrusions and are not effective in detecting fast spreading attacks, unknown, or new threats. In turn, they can achieve better detection accuracy through collaboration. An Intrusion Detection Network (IDN) is such a collaboration network allowing IDSs to exchange information with each other and to benefit from the collective knowledge and experience shared by others. IDNs enhance the overall accuracy of intrusion assessment as well as the ability to detect new intrusion types. Building an effective IDN is however a challenging task. For example, adversaries may compromise some IDSs in the network and then leverage the compromised nodes to send false information, or even attack others in the network, which can compromise the efficiency of the IDN. It is, therefore, important for an IDN to detect and isolate malicious insiders. Another challenge is how to make efficient intrusion detection assessment based on the collective diagnosis from other IDSs. Appropriate selection of collaborators and incentive-compatible resource management in support of IDSs' interaction with others are also key challenges in IDN design. To achieve efficiency, robustness, and scalability, we propose an IDN architecture and especially focus on the design of four of its essential components, namely, trust management, acquaintance management, resource management, and feedback aggregation. We evaluate our proposals and compare them with prominent ones in the literature and show their superiority using several metrics, including efficiency, robustness, scalability, incentive-compatibility, and fairness. Our IDN design provides guidelines for the deployment of a secure and scalable IDN where effective collaboration can be established between IDSs

Web3Recommend: Decentralised recommendations with trust and relevance

Web3Recommend is a decentralized Social Recommender System implementation that enables Web3 Platforms on Android to generate recommendations that balance trust and relevance. Generating recommendations in decentralized networks is a non-trivial problem because these networks lack a global perspective due to the absence of a central authority. Further, decentralized networks are prone to Sybil Attacks in which a single malicious user can generate multiple fake or Sybil identities. Web3Recommend relies on a novel graph-based content recommendation design inspired by GraphJet, a recommendation system used in Twitter enhanced with MeritRank, a decentralized reputation scheme that provides Sybil-resistance to the system. By adding MeritRank's decay parameters to the vanilla Social Recommender Systems' personalized SALSA graph algorithm, we can provide theoretical guarantees against Sybil Attacks in the generated recommendations. Similar to GraphJet, we focus on generating real-time recommendations by only acting on recent interactions in the social network, allowing us to cater temporally contextual recommendations while keeping a tight bound on the memory usage in resource-constrained devices, allowing for a seamless user experience. As a proof-of-concept, we integrate our system with MusicDAO, an open-source Web3 music-sharing platform, to generate personalized, real-time recommendations. Thus, we provide the first Sybil-resistant Social Recommender System, allowing real-time recommendations beyond classic user-based collaborative filtering. The system is also rigorously tested with extensive unit and integration tests. Further, our experiments demonstrate the trust-relevance balance of recommendations against multiple adversarial strategies in a test network generated using data from real music platforms

WARP: A ICN architecture for social data

Social network companies maintain complete visibility and ownership of the data they store. However users should be able to maintain full control over their content. For this purpose, we propose WARP, an architecture based upon Information-Centric Networking (ICN) designs, which expands the scope of the ICN architecture beyond media distribution, to provide data control in social networks. The benefit of our solution lies in the lightweight nature of the protocol and in its layered design. With WARP, data distribution and access policies are enforced on the user side. Data can still be replicated in an ICN fashion but we introduce control channels, named \textit{thread updates}, which ensures that the access to the data is always updated to the latest control policy. WARP decentralizes the social network but still offers APIs so that social network providers can build products and business models on top of WARP. Social applications run directly on the user's device and store their data on the user's \textit{butler} that takes care of encryption and distribution. Moreover, users can still rely on third parties to have high-availability without renouncing their privacy

Managing the Internet of Things based on its Social Structure

Society is moving towards an “always connected” paradigm, where the Internet user is shifting from persons to things, leading to the so called Internet of Things (IoT) scenario. The IoT vision integrates a large number of technologies and foresees to embody a variety of smart objects around us (such as sensors, actuators, smartphones, RFID, etc.) that, through unique addressing schemes and standard communication protocols, are able to interact with each Others and cooperate with their neighbors to reach common goals [2, 3]. IoT is a hot research topic, as demonstrated by the increasing attention and the large worldwide investments devoted to it. It is believed that the IoT will be composed of trillions of elements interacting in an extremely heterogeneous way in terms of requirements, behavior and capabilities; according to [4], by 2015 the RIFD devices alone will reach hundreds of billions. Unquestionably, the IoT will pervade every aspect of our world and will have a huge impact in our everyday life: indeed, as stated by the US National Intelligence Council (NIC) [5], “by 2025 Internet nodes may reside in everyday things − food packages, furniture, paper documents, and more”. Then, communications will not only involve persons but also things thus bringing about the IoT environment in which objects will have virtual counterparts on the Internet. Such virtual entities will produce and consume services, collaborate toward common goals and should be integrated with all the other services. One of the biggest challenges that the research community is facing right now is to be able to organize such an ocean of devices so that the discovery of objects and services is performed efficiently and in a scalable way. Recently, several attempts have been made to apply concepts of social networking to the IoT. There are scientific evidences that a large number of individuals tied in a social network can provide far more accurate answers to complex problems than a single individual (or a small group of – even knowledgeable – individuals) [1]. The exploitation of such a principle, applied to smart objects, has been widely investigated in Internet-related researches. Indeed, several schemes have been proposed that use social networks to search Internet resources, to route traffic, or to select effective policies for content distribution. The idea that the convergence of the “Internet of Things” and the “Social Networks” worlds, which up to now were mostly kept separate by both scientific and industrial communities, is possible or even advisable is gaining momentum very quickly. This is due to the growing awareness that a “Social Internet of Things” (SIoT) paradigm carries with it many desirable implications in a future world populated by objects permeating the everyday life of human beings. Therefore, the goal of this thesis is to define a possible architecture for the SIoT, which includes the functionalities required to integrate things into a social network, and the needed strategies to help things to create their relationships in such a way that the resulting social network is navigable. Moreover, it focuses on the trustworthiness management, so that interaction among objects that are friends can be done in a more reliable way and proposes a possible implementation of a SIoT network. Since this thesis covers several aspects of the Social internet of Things, I will present the state of the art related to the specific research activities at the beginning of every Chapter. The rest of the thesis is structured as follows. In Chapter 1, I identify appropriate policies for the establishment and the management of social relationships between objects, describe a possible architecture for the IoT that includes the functionalities required to integrate things into a social network and analyze the characteristics of the SIoT network structure by means of simulations. Chapter 2 addresses the problem of the objects to manage a large number of friends, by analyzing possible strategies to drive the objects to select the appropriate links for the benefit of overall network navigability and to speed up the search of the services. In Chapter 3, I focus on the problem of understanding how the information provided by members of the social IoT has to be processed so as to build a reliable system on the basis of the behavior of the objects and define two models for trustworthiness management starting from the solutions proposed for P2P and social networks. Chapter 4 presents an implementation of a SIoT platform and its major functionalities: how to register a new social object to the platform, how the system manages the creation of new relationships, and how the devices create groups of members with similar characteristics. Finally, in Chapter 5, conclusions will be drawn regarding the effectiveness of the proposed Introduction 3 algorithms, and some possible future works will be sketche

Managing the Internet of Things based on its Social Structure

Society is moving towards an “always connected” paradigm, where the Internet user is shifting from persons to things, leading to the so called Internet of Things (IoT) scenario. The IoT vision integrates a large number of technologies and foresees to embody a variety of smart objects around us (such as sensors, actuators, smartphones, RFID, etc.) that, through unique addressing schemes and standard communication protocols, are able to interact with each Others and cooperate with their neighbors to reach common goals [2, 3]. IoT is a hot research topic, as demonstrated by the increasing attention and the large worldwide investments devoted to it. It is believed that the IoT will be composed of trillions of elements interacting in an extremely heterogeneous way in terms of requirements, behavior and capabilities; according to [4], by 2015 the RIFD devices alone will reach hundreds of billions. Unquestionably, the IoT will pervade every aspect of our world and will have a huge impact in our everyday life: indeed, as stated by the US National Intelligence Council (NIC) [5], “by 2025 Internet nodes may reside in everyday things − food packages, furniture, paper documents, and more”. Then, communications will not only involve persons but also things thus bringing about the IoT environment in which objects will have virtual counterparts on the Internet. Such virtual entities will produce and consume services, collaborate toward common goals and should be integrated with all the other services. One of the biggest challenges that the research community is facing right now is to be able to organize such an ocean of devices so that the discovery of objects and services is performed efficiently and in a scalable way. Recently, several attempts have been made to apply concepts of social networking to the IoT. There are scientific evidences that a large number of individuals tied in a social network can provide far more accurate answers to complex problems than a single individual (or a small group of – even knowledgeable – individuals) [1]. The exploitation of such a principle, applied to smart objects, has been widely investigated in Internet-related researches. Indeed, several schemes have been proposed that use social networks to search Internet resources, to route traffic, or to select effective policies for content distribution. The idea that the convergence of the “Internet of Things” and the “Social Networks” worlds, which up to now were mostly kept separate by both scientific and industrial communities, is possible or even advisable is gaining momentum very quickly. This is due to the growing awareness that a “Social Internet of Things” (SIoT) paradigm carries with it many desirable implications in a future world populated by objects permeating the everyday life of human beings. Therefore, the goal of this thesis is to define a possible architecture for the SIoT, which includes the functionalities required to integrate things into a social network, and the needed strategies to help things to create their relationships in such a way that the resulting social network is navigable. Moreover, it focuses on the trustworthiness management, so that interaction among objects that are friends can be done in a more reliable way and proposes a possible implementation of a SIoT network. Since this thesis covers several aspects of the Social internet of Things, I will present the state of the art related to the specific research activities at the beginning of every Chapter. The rest of the thesis is structured as follows. In Chapter 1, I identify appropriate policies for the establishment and the management of social relationships between objects, describe a possible architecture for the IoT that includes the functionalities required to integrate things into a social network and analyze the characteristics of the SIoT network structure by means of simulations. Chapter 2 addresses the problem of the objects to manage a large number of friends, by analyzing possible strategies to drive the objects to select the appropriate links for the benefit of overall network navigability and to speed up the search of the services. In Chapter 3, I focus on the problem of understanding how the information provided by members of the social IoT has to be processed so as to build a reliable system on the basis of the behavior of the objects and define two models for trustworthiness management starting from the solutions proposed for P2P and social networks. Chapter 4 presents an implementation of a SIoT platform and its major functionalities: how to register a new social object to the platform, how the system manages the creation of new relationships, and how the devices create groups of members with similar characteristics. Finally, in Chapter 5, conclusions will be drawn regarding the effectiveness of the proposed Introduction 3 algorithms, and some possible future works will be sketche