Question

a) We discussed TOR, which enables, for example, anonymous Internet browsing.
• Briefly explain how TOR provides anonymous Internet browsing. You can draw a figure to illustrate your argumentation.
• TOR also allows   so called hidden services.   Please briefly explain what a hidden service is and how TOR enables it.

You can draw a figure to illustrate your argumentation.

b) Describe the MapReduce algorithm.

Split it into its phases. For each phase include: what it does and who is responsible (the MapReduce framework or the programmer).  

Answer 1

answer a)-

i -

Tor is free and open-source software for enabling anonymous communication. The name is derived from an acronym for the original software project name "The Onion Router". Tor directs Internet traffic through a free, worldwide, volunteer overlay network consisting of more than seven thousand relays to conceal a user's location and usage from anyone conducting network surveillance or traffic analysis. Using Tor makes it more difficult to trace Internet activity to the user: this includes "visits to Web sites, online posts, instant messages, and other communication forms". Tor's intended use is to protect the personal privacy of its users, as well as their freedom and ability to conduct confidential communication by keeping their Internet activities unmonitored.Tor does not prevent an online service from determining when it is being accessed through Tor. Tor protects a user's privacy, but does not hide the fact that someone is using Tor. Some websites restrict allowances through Tor.

ii --

Tor can also provide anonymity to websites and other servers. Servers configured to receive inbound connections only through Tor are called onion services (formerly, hidden services).Rather than revealing a server's IP address (and thus its network location), an onion service is accessed through its onion address, usually via the Tor Browser. The Tor network understands these addresses by looking up their corresponding public keys and introduction points from a distributed hash table within the network. It can route data to and from onion services, even those hosted behind firewalls or network address translators (NAT), while preserving the anonymity of both parties. Tor is necessary to access these onion services.Tor is decentralized by design; there is no direct readable list of all onion services, although a number of onion services catalog publicly known onion addresses.Because onion services route their traffic entirely through the Tor network, connection to an onion service is encrypted end-to-end and not subject to eavesdropping. There are, however, security issues involving Tor onion services.

answer B )-

The MapReduce algorithm contains two important tasks, namely Map and Reduce.

• The map task is done by means of Mapper Class
• The reduce task is done by means of Reducer Class.

Mapper class takes the input, tokenizes it, maps and sorts it. The output of Mapper class is used as input by Reducer class, which in turn searches matching pairs and reduces them.

MapReduce implements various mathematical algorithms to divide a task into small parts and assign them to multiple systems. In technical terms, MapReduce algorithm helps in sending the Map & Reduce tasks to appropriate servers in a cluster.

These mathematical algorithms may include the following −

• Sorting
• Searching
• Indexing
• TF-IDF

Sorting

Sorting is one of the basic MapReduce algorithms to process and analyze data. MapReduce implements sorting algorithm to automatically sort the output key-value pairs from the mapper by their keys.

• Sorting methods are implemented in the mapper class itself.

• In the Shuffle and Sort phase, after tokenizing the values in the mapper class, the Context class (user-defined class) collects the matching valued keys as a collection.

• To collect similar key-value pairs (intermediate keys), the Mapper class takes the help of RawComparator class to sort the key-value pairs.

• The set of intermediate key-value pairs for a given Reducer is automatically sorted by Hadoop to form key-values (K2, {V2, V2, …}) before they are presented to the Reducer.

Searching

Searching plays an important role in MapReduce algorithm. It helps in the combiner phase (optional) and in the Reducer phase.

Indexing

Normally indexing is used to point to a particular data and its address. It performs batch indexing on the input files for a particular Mapper.

The indexing technique that is normally used in MapReduce is known as inverted index. Search engines like Google and Bing use inverted indexing technique.

TF-IDF

TF-IDF is a text processing algorithm which is short for Term Frequency − Inverse Document Frequency. It is one of the common web analysis algorithms. Here, the term 'frequency' refers to the number of times a term appears in a document.

Term Frequency (TF)

It measures how frequently a particular term occurs in a document. It is calculated by the number of times a word appears in a document divided by the total number of words in that document.

Inverse Document Frequency (IDF)

It measures the importance of a term. It is calculated by the number of documents in the text database divided by the number of documents where a specific term appears.