Some ISPs love to act like Big Brothers and constrict bandwidth for P2P protocols. Protocol Encryption in most of the torrent clients helps to over ride this bandwidth shaping. Enable outgoing protocol encryption and put a checkmark on Allow Incoming Legacy Connections. With protocol encryption, ISPs find it difficult if not impossible to detect that the traffic is coming from BitTorrent. Experiment with enabled, disabled and forced options because you could be getting better speeds with encryption disabled. Non-encryption makes a torrent connection compatible with someone who is not using encryption but as a minus it makes the torrent detectable but an ISP with a bandwidth restricting policy.
Whilst the ability to access books online was positively received, it became apparent that users disliked digital rights management (DRM) intensely. Feedback from library users was that they expected to be able to view, download and print e-book chapters just as they already did with e-journal articles: as DRM-free PDF files. As a result the library amended its strategy to increas- ingly buy e-books on publishers’ own platforms. These e-books were often in bundles acquired at the end of the financial year if sufficient funds were available.
The hundreds of hacks you’ll ﬁ nd inside are useful, frequently entertaining, and will save you countless hours at the keyboard. Whether you want to speed up your PC, customize the Windows interface, hack your wired and wireless network, get more out of the Web, make better use of email, use the Registry to bend the operating system to your will, record TV shows and burn DVDS, or use Windows for countless other useful tasks, you’ll ﬁ nd what you’re looking for here. And each hack doesn’t just show you how to do something; it also teaches why it works. Each hack is a starting point, rather than an ending point, so that you can apply the knowledge you’ve gained to create new hacks of your own. Try it out: who knows, in the next edition of this book, you might get a hack of your own published.
Nobody wants to get involved in a criminal case and I've yet to meet a hacker who was fully prepared for it happening to them. There are thousands of paper and electronic magazines, CD-ROMS, web pages and text files about hackers and hacking available, yet there is nothing in print until now that specifically covers what to do when an arrest actually happens to you. Most hackers do not plan for an arrest by hiding their notes or encrypting their data, and most of them have some sort of address book seized from them too (the most famous of which still remains the one seized from The Not So Humble Babe). Most of them aren't told the full scope of the investigation up front, and as the case goes on more comes to light, often only at the last minute. Invariably, the hacker in question was wiretapped and/or narced on by someone previously raided who covered up their own raid or minimized it in order to get off by implicating others. Once one person goes down it always affects many others later. My own
A Vector is just a standard class that encapsulates the functionality of an array but allows it to expand automatically. You can just keep on adding things to it, and each addition will behave the same. If you watch really closely you might notice a brief extra pause once in a while when adding objects, as Vector reallocates and copies. But you don't have to think about it. However, because Vector is a class and isn't part of the syntax of Java, you can't use Java's array syntax; you must use methods to access the Vector data. There are methods to add objects, retrieve objects, find objects, and tell you how big the Vector is and how big it can become without having to reallocate. Like those of all the collection classes in java.util, Vector's storing and retrieval methods are defined in terms of java.lang.Object. But since Object is the ancestor of every defined type, you can store objects of any type in a Vector (or any collection), and cast it when retrieving it. If you need to store a small number of built-ins (like int, float, etc.) into a collection containing other data, use the appropriate wrapper class (see the Introduction to Chapter 5). To store booleans, either use a java.util.BitSet (see the online documentation) or the Boolean wrapper class.
as an efficient content distribution approach . BitTorrent, the most popular P2P protocol, is recognized as a successful P2P system based on a set of efficient mechanisms that overcome many challenges other P2P protocols experience such as scalability, fairness, churn and resource utilization. However, some researchers argue that the BitTorrent fairness mechanism is not very effective as it allows free riders to download more content than they provide to the sharing community. Regardless of the academic concerns, BitTorrent traffic accounts for 17% to 50% of the total Internet upload traffic in some segments , . The current BitTorrent implementation is based on random graphs since such graphs are known to be robust , yet random graphs mean that BitTorrent is location un-aware which represented a burden on ISPs for many years  as traffic might cross their networks unnecessarily causing high fees to be paid to other ISPs. Existing research on energy aware BitTorrent has focused on the power consumption of both the network side and the peers’ side. At the peers’ side, studies such as the work in  suggested elevating the file sharing task to proxies which distribute the content locally to the clients. In  the authors used the result of the fluid model in  to study the energy efficiency of BitTorrent in steady state. At the network side, the authors in  evaluated the energy efficiency of Client-Server (C-S) and BitTorrent based P2P systems using a simplified model and concluded that P2P systems are not energy efficient in the network side compared to C-S systems due to the multiple hops needed to distribute file pieces between peers. The study suggests that smart peer selection mechanisms might help reduce the number of hops, and consequently the energy consumption. Similar observations are made in ,  where location un- awareness doubles the utilization of the access network yielding a higher power consumption. Adding the idle power consumption of the peripherals used for P2P content delivery can double the power consumption in the user’s equipments as shown in . However, other researchers in the literature argue that since users of P2P systems only use the already powered on peripherals, only the traffic induced power consumption should be taken into account as in . The authors in  studied the performance versus locality trade-offs in BitTorrent like protocols by developing an LP model and a heuristic.
A setup used to capture BTSync related traffic is shown Fig 6. Here re0 and re1 represent network cards where 1GBps interfaces with a mirrored traffic are attached. These interfaces are combined into single virtual interface lagg0 using OS lagg driver. VLANs vlan0 and vlan1 then are extracted from it using vlan driver. A number of BP filters (scripts) are started on virtual network interfaces. Some of these scripts, which generate a big amount of data very quickly, rotate captured buffers, and a script (match?) tests the previous buffer for implications of BTSync related traffic. Based on the result of this test, the buffer is either discarded or saved for later analysis. For performance reasons, only simple tests were used to prevent queueing of untested buffers, which would lead to swapping in the OS and as a result to a process stall.
Overall, our study presents a comprehensive analysis of BitTorrent traffic relevant to cache design and it performs a wide evaluation of the effectiveness of several different designs for caching BitTorrent traffic. Nevertheless, our find- ings may be extended in various directions which we left out of our scope. First, given that our results show that a marked temporal locality in BitTorrent traffic chiefly influences cache effectiveness, future research should extend our evaluation exploring optimizations in a LRU-based cache. Such opti- mizations can focus on the development of an efficient cache implementation, analyzing, for example, how variations in the number of cache users impacts on replacement policy effectiveness. Furthermore, future research should explore a hybrid approach that combines both caching and locality- aware mechanisms. Our results show that the traffic reduc- tion achieved by each one of these strategies leaves a margin for applying further reduction techniques. In this direction, future work should analyze if the traffic reductions achieved by each mechanisms are indeed complementary, and how each mechanism impacts on the effectiveness of the other.
This thesis includes a security analysis of the transport layer. To make BitTorrent more Internet Service Provider friendly, BitTorrent Inc. invented the Micro Transport Protocol. It is based on User Data- gram Protocol with a novel congestion control called Low Extra Delay Background Transport. This protocol assumes that the receiver always provides correct feedback, otherwise this deteriorates throughput or yields to corrupted data. I show through experimental evaluation, that a misbehaving Micro Transport Protocol receiver which is not interested in data integrity, can increase the bandwidth of the sender by up to five times. This can cause a congestion collapse and steal a large share of a victim’s bandwidth. I present three attacks, which increase bandwidth usage significantly. I have tested these attacks in real world environments and demonstrate their severity both in terms of the number of packets and total traffic generated. I also present a countermeasure for protecting against these attacks and evaluate the performance of this defensive strategy.
We perform experiments using private torrents in our testbed consisting of 32 nodes with a controller and a monitor node. These nodes are desktop machines, which are running the BitTorrent Transmission version 2.61 and Deluge version 1.3.5 (libtorrent 0.16.10) over Ubuntu GNU Linux 12.04.1 LTS. A network diagram can be seen in Figure 2. We wrote a distributed experiment library in Perl to simultaneously control all nodes. This software monitors and records the status of each peer at every second. This includes: nodes in peer set, nodes in active peer set, interested and choked states for each of the peers in the active peer set, and upload and download rate with each of the peers in the active peer set. In all experiments, the seeder distributes a file with a size of 100 MiB and a piece size of 64 KiB. The controller node executes the experiments and monitors each of these nodes.
Nowadays, P2P networks , such as BitTorrent [8-10], Gnutella, and eDonkey, have become irreplaceable media for information dissemination and sharing over the Internet due to its extensive application. The huge amount of data exchanged through P2P networks and the global-scale of P2P infrastructure creates an environment where communication has a potential to be hidden among the mass of regular users and corresponding host message exchanges. BitTorrent network which inherited the characteristics of high speed and huge flux of P2P networks is extensively used throughout the world.
The nodes joining the network is modeled to study the performance of bandwidth distribution of a peer to peer network based on a probabilistic approach. Most of the connections are assumed to be an ADSL with a low upload bandwidth value than the download bandwidth value. Table 1 bives the uplink/downlink bandwidth value to be used in the simulation. A file size of 500 Mb with the block size of 256 Kb is used in the simulation with an initial seed having a bandwidth of 1024 Kbps. There can be 200 active nodes at a given time. The file size of 500 Mb is splitted into a 256 Kb blocks resulting in a total of 2000 blocks. The maximum number of neighbour for each node is limited upto 5. The efficiency of a bittorrent is evaluated by the mean utilization of uplinks or downlinks over time. Utilization point can be calculated by an aggregate traffic flow ratio of all uplinks/downlinks to the aggregate capacity of all system uplinks. The maximum data can be served when the network uplinks are saturated. The uplink utilization is considered to be a key performance determinant though the downlink utilization is an important access link asymmetry .