237 research outputs found

    A Dynamic Trust Management Scheme to Mitigate Malware Proliferation in P2P Networks

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    Trust management schemes for peer-to-peer networks

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    Peer-to-peer (P2P) networking enables users with similar interests to exchange, or obtain files. This network model has been proven popular to exchange music, pictures, or software applications. These files are saved, and most likely executed, at the downloading host. At the expense of this mechanism, worms, viruses, and malware find an open front door to the downloading host and gives them a convenient environment for successful proliferation throughout the network. Although virus detection software is currently available, this countermeasure works in a reactive fashion, and in most times, in an isolated manner. A trust management scheme is considered to contain the proliferation of viruses in P2P networks. Specifically, a cooperative and distributed trust management scheme based on a two-layer approach to bound the proliferation of viruses is proposed. The new scheme is called double-layer dynamic trust (DDT) management scheme. The results show that the proposed scheme bounds the proliferation of malware. With the proposed scheme, the number of infected hosts and the proliferation rate are limited to small values. In addition, it is shown that network activity is not discouraged by using the proposed scheme. Moreover, to improve the efficiency on the calculation of trust values of ratio based normalization models, a model is proposed for trust value calculation using a three-dimensional normalization to represent peer activity with more accuracy than that of a conventional ratio based normalization. Distributed network security is also considered, especially in P2P network security. For many P2P systems, including ad hoc networks and online markets, reputation systems have been considered as a solution for mitigating the affects of malicious peers. However, a sybil attack, wherein forging identities is performed to unfairly and arbitrarily influence the reputation of peers in a network or community. To defend against sybil attack, each reported transaction, which is used to calculate trust values, is verified. In this thesis, it is shown that peer reputation alone cannot bound network subversion of a sybil attack. Therefore, a new trust management framework, called Sybildefense, is introduced. This framework combines a trust management scheme with a cryptography mechanism to verify different transaction claims issue by peers, including those bogus claims of sybil peers. To improve the efficiency on the identification of honest peers from sybil peers, a k-means clustering mechanism is adopted. Moreover, to include a list of peer’s trustees in a warning messages is proposed to generate a local table for a peer that it is used to identify possible clusters of sybil peers. The defensive performance of these algorithms are compared under sybil attacks. The performance results show that the proposed framework (Sybildefense) can thwart sybil attacks efficiently

    A survey on security, privacy and anonymity in legal distribution of copyrighted multimedia content over peer-to-peer networks

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    A Practical Approach to Protect IoT Devices against Attacks and Compile Security Incident Datasets

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    open access articleThe Internet of Things (IoT) introduced the opportunity of remotely manipulating home appliances (such as heating systems, ovens, blinds, etc.) using computers and mobile devices. This idea fascinated people and originated a boom of IoT devices together with an increasing demand that was difficult to support. Many manufacturers quickly created hundreds of devices implementing functionalities but neglected some critical issues pertaining to device security. This oversight gave rise to the current situation where thousands of devices remain unpatched having many security issues that manufacturers cannot address after the devices have been produced and deployed. This article presents our novel research protecting IOT devices using Berkeley Packet Filters (BPFs) and evaluates our findings with the aid of our Filter.tlk tool, which is able to facilitate the development of BPF expressions that can be executed by GNU/Linux systems with a low impact on network packet throughput

    Decentralized Federated Learning: Fundamentals, State-of-the-art, Frameworks, Trends, and Challenges

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    In the last decade, Federated Learning (FL) has gained relevance in training collaborative models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the most common approach in the literature, where a central entity creates a global model. However, a centralized approach leads to increased latency due to bottlenecks, heightened vulnerability to system failures, and trustworthiness concerns affecting the entity responsible for the global model creation. Decentralized Federated Learning (DFL) emerged to address these concerns by promoting decentralized model aggregation and minimizing reliance on centralized architectures. However, despite the work done in DFL, the literature has not (i) studied the main aspects differentiating DFL and CFL; (ii) analyzed DFL frameworks to create and evaluate new solutions; and (iii) reviewed application scenarios using DFL. Thus, this article identifies and analyzes the main fundamentals of DFL in terms of federation architectures, topologies, communication mechanisms, security approaches, and key performance indicators. Additionally, the paper at hand explores existing mechanisms to optimize critical DFL fundamentals. Then, the most relevant features of the current DFL frameworks are reviewed and compared. After that, it analyzes the most used DFL application scenarios, identifying solutions based on the fundamentals and frameworks previously defined. Finally, the evolution of existing DFL solutions is studied to provide a list of trends, lessons learned, and open challenges

    The Evolution of Embedding Metadata in Blockchain Transactions

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    The use of blockchains is growing every day, and their utility has greatly expanded from sending and receiving crypto-coins to smart-contracts and decentralized autonomous organizations. Modern blockchains underpin a variety of applications: from designing a global identity to improving satellite connectivity. In our research we look at the ability of blockchains to store metadata in an increasing volume of transactions and with evolving focus of utilization. We further show that basic approaches to improving blockchain privacy also rely on embedding metadata. This paper identifies and classifies real-life blockchain transactions embedding metadata of a number of major protocols running essentially over the bitcoin blockchain. The empirical analysis here presents the evolution of metadata utilization in the recent years, and the discussion suggests steps towards preventing criminal use. Metadata are relevant to any blockchain, and our analysis considers primarily bitcoin as a case study. The paper concludes that simultaneously with both expanding legitimate utilization of embedded metadata and expanding blockchain functionality, the applied research on improving anonymity and security must also attempt to protect against blockchain abuse.Comment: 9 pages, 6 figures, 1 table, 2018 International Joint Conference on Neural Network

    A Survey on Security for Mobile Devices

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    Nowadays, mobile devices are an important part of our everyday lives since they enable us to access a large variety of ubiquitous services. In recent years, the availability of these ubiquitous and mobile services has signicantly increased due to the dierent form of connectivity provided by mobile devices, such as GSM, GPRS, Bluetooth and Wi-Fi. In the same trend, the number and typologies of vulnerabilities exploiting these services and communication channels have increased as well. Therefore, smartphones may now represent an ideal target for malware writers. As the number of vulnerabilities and, hence, of attacks increase, there has been a corresponding rise of security solutions proposed by researchers. Due to the fact that this research eld is immature and still unexplored in depth, with this paper we aim to provide a structured and comprehensive overview of the research on security solutions for mobile devices. This paper surveys the state of the art on threats, vulnerabilities and security solutions over the period 2004-2011. We focus on high-level attacks, such those to user applications, through SMS/MMS, denial-of-service, overcharging and privacy. We group existing approaches aimed at protecting mobile devices against these classes of attacks into dierent categories, based upon the detection principles, architectures, collected data and operating systems, especially focusing on IDS-based models and tools. With this categorization we aim to provide an easy and concise view of the underlying model adopted by each approach
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