No Arabic abstract
IP spoofing enables reflection and amplification attacks, which cause major threats to the current Internet infrastructure. IP packets with incorrect source addresses would help to improve the situation. This is easy at the attackers network, but very challenging at Internet eXchange Points (IXPs) or in transit networks. In this reproducibility study, we revisit the paper textit{Detection, Classification, and Analysis of Inter-Domain Traffic with Spoofed Source IP Addresses} published at ACM IMC 2017. Using data from a different IXP and from a different time, we were not able to reproduce the results. Unfortunately, our analysis shows that the current state of art does introduce a methodology that does not comply with common real-world deployment.
Storage networking technology has enjoyed strong growth in recent years, but security concerns and threats facing networked data have grown equally fast. Today, there are many potential threats that are targeted at storage networks, including data modification, destruction and theft, DoS attacks, malware, hardware theft and unauthorized access, among others. In order for a Storage Area Network (SAN) to be secure, each of these threats must be individually addressed. In this paper, we present a comparative study by implementing different security methods in IP Storage network.
Multiple probabilistic packet marking (PPM) schemes for IP traceback have been proposed to deal with Distributed Denial of Service (DDoS) attacks by reconstructing their attack graphs and identifying the attack sources. In this paper, ten PPM-based IP traceback schemes are compared and analyzed in terms of features such as convergence time, performance evaluation, underlying topologies, incremental deployment, re-marking, and upstream graph. Our analysis shows that the considered schemes exhibit a significant discrepancy in performance as well as performance assessment. We concisely demonstrate this by providing a table showing that (a) different metrics are used for many schemes to measure their performance and, (b) most schemes are evaluated on different classes of underlying network topologies. Our results reveal that both the value and arrangement of the PPM-based scheme convergence times vary depending on exactly the underlying network topology. As a result, this paper shows that a side-by-side comparison of the scheme performance a complicated and turns out to be a crucial open problem in this research area.
We introduce an application of a mobile transient network architecture on top of the current Internet. This paper is an application extension to a conceptual mobile network architecture. It attempts to specifically reinforce some of the powerful notions exposed by the architecture from an application perspective. Of these notions, we explore the network expansion layer, an overlay of components and services, that enables a persistent identification network and other required services. The overlay abstraction introduces several benefits of which mobility and communication across heterogenous network structures are of interest to this paper. We present implementations of several components and protocols including gateways, Agents and the Open Device Access Protocol. Our present identification network implementation exploits the current implementation of the Handle System through the use of distributed, global and persistent identifiers called handles. Handles are used to identify and locate devices and services abstracting any physical location or network association from the communicating ends. A communication framework is finally demonstrated that would allow for mobile devices on the public Internet to have persistent identifiers and thus be persistently accessible either directly or indirectly. This application expands IP inter-operability beyond its current boundaries.
Datacenters provide the infrastructure for cloud computing services used by millions of users everyday. Many such services are distributed over multiple datacenters at geographically distant locations possibly in different continents. These datacenters are then connected through high speed WAN links over private or public networks. To perform data backups or data synchronization operations, many transfers take place over these networks that have to be completed before a deadline in order to provide necessary service guarantees to end users. Upon arrival of a transfer request, we would like the system to be able to decide whether such a request can be guaranteed successful delivery. If yes, it should provide us with transmission schedule in the shortest time possible. In addition, we would like to avoid packet reordering at the destination as it affects TCP performance. Previous work in this area either cannot guarantee that admitted transfers actually finish before the specified deadlines or use techniques that can result in packet reordering. In this paper, we propose DCRoute, a fast and efficient routing and traffic allocation technique that guarantees transfer completion before deadlines for admitted requests. It assigns each transfer a single path to avoid packet reordering. Through simulations, we show that DCRoute is at least 200 times faster than other traffic allocation techniques based on linear programming (LP) while admitting almost the same amount of traffic to the system.
Blockchains are typically managed by peer-to-peer (P2P) networks providing the support and substrate to the so-called distributed ledger (DLT), a replicated, shared, and synchronized data structure, geographically spread across multiple nodes. The Bitcoin (BTC) blockchain is by far the most well known DLT, used to record transactions among peers, based on the BTC digital currency. In this paper, we focus on the network side of the BTC P2P network, analyzing its nodes from a purely network measurements-based approach. We present a BTC crawler able to discover and track the BTC P2P network through active measurements, and use it to analyze its main properties. Through the combined analysis of multiple snapshots of the BTC network as well as by using other publicly available data sources on the BTC network and DLT, we unveil the BTC P2P network, locate its active nodes, study their performance, and track the evolution of the network over the past two years. Among other relevant findings, we show that (i) the size of the BTC network has remained almost constant during the last 12 months - since the major BTC price drop in early 2018, (ii) most of the BTC P2P network resides in US and EU countries, and (iii) despite this western network locality, most of the mining activity and corresponding revenue is controlled by major mining pools located in China. By additionally analyzing the distribution of BTC coins among independent BTC entities (i.e., single BTC addresses or groups of BTC addresses controlled by the same actor), we also conclude that (iv) BTC is very far from being the decentralized and uncontrolled system it is so much advertised to be, with only 4.5% of all the BTC entities holding about 85% of all circulating BTC coins.