Techpush | Agent Based Efficient Anomaly Intrusion Detection System in Adhoc networks IEEE Project



Mobile Agent Based IDS
Intrusion Detection System

Agent Based Efficient Anomaly Intrusion Detection System in Adhoc networks
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Opinion Mining & Social Networking a Promising match Project





Opinion Mining and Social Networks:
a Promising Match
Abstract—In this paper we discuss the role and importance of social networks as preferred environments for opinion mining and sentiment analysis especially. We begin by briefly describing selected properties of social networks that are relevant with respect to opinion mining and we outline the general relationships between the two disciplines. We present the related work and provide basic definitions used in opinion mining. Then, we introduce our original method of opinion classification and we test the presented algorithm on real world datasets acquired from popular Polish social networks, reporting on the results. The  results are promising and soundly support the main thesis of the paper, namely, that social networks exhibit properties that make them very suitable for opinion mining activities.

Keywords: opinion mining, sentiment analysis, social
computing, social networks

I. INTRODUCTION
Graphs and networks certainly rank among one of the most popular data representation models due to their universal applicability to various application domains. The need to analyze and mine interesting knowledge from graph and network structures has been long recognized, but only recently the advances in information systems have enabled the analysis of graph structures at huge scales. Analysis of graph and network structures gained new momentum with the advent of social networks. While the analysis of social networks has been a field of intensive research, particularly in the domains of social sciences and psychology, economy or chemistry, it is the emergence of huge social networking services over the Web that
spawned the research into large-scale structural properties of social networks.. Social networks exhibit a very clear community structure. Such community structure partially stems from objective limitations (e.g., internal organizational structure of a company can be closely represented by the ties within a particular social network) or, to some extent, may result from subjective user actions and activities (e.g., bonding with other people who share one’s interests and hobbies). Unveiling the true structure of a social network and understanding of communities forming within the network is the key factor in understanding what the future structure of network will be. The main goal of social network analysis is the study of structural properties of networks. Structural analysis of the social network investigates the properties of individual vertices and the global properties of the network as a whole. It answers two basic classes of questions about the network: what is the structural position of any given individual node and what can be said about groups (communities) forming within the network. The main measurement of a node’s social power (also called member’s prestige) is centrality, which allows to determine node’s relative and absolute importance in the network. There are several methods to determine node’s centrality, such as the degree centrality (the number of links that connect to a given node), the betweenness centrality (the number of shortest paths between any pair of nodes in the network that traverse a given node) or the closeness centrality (the mean of shortest paths lengths to other nodes in the network). From the point of view of opinion mining the ability to assess the node’s prestige is essential as it allows to differentiate between opinions of different individuals. More specifically, node’s prestige allows to assign different weights to opinions and associate more importance to opinions expressed by prominent individuals. Another factor that is often considered in opinion mining is the identification of influential individuals. An influential individual does not have to be necessarily characterized with high degree centrality to influence the average opinion within the network. Usually, such individuals are characterized by high betweenness
centrality, impacting the dissemination of opinion rather than forming the opinion. For instance, an individual with high betweenness centrality can stop a negative opinion from spreading through the network, or, on the other hand, she can amplify the opinion. Due to psychological reasons humans tend to form their opinions in such way that the opinions conform with the norm established within a given social group. Thus,
when mining opinions one has to take into consideration the influence of the context in which the opinion is forming, i.e. the social milieu of an individual. Social networks are highly effective in bolstering group formation

Three-Dimensional Password for More Secure Authentication


Abstract—Current authentication systems suffer from many weaknesses. Textual passwords are commonly used; however, users do not follow their requirements. Users tend to choose meaningful words from dictionaries, which make textual passwords easy to break and vulnerable to dictionary or brute force attacks. Many available graphical passwords have a password
space that is less than or equal to the textual password space. Smart cards or tokens can be stolen. Many biometric authentications have been proposed; however, users tend to resist using biometrics because of their intrusiveness and the effect on their privacy. Moreover, biometrics cannot be revoked. In this paper, we present and evaluate our contribution, i.e., the 3-D password.
The 3-D password is a multifactor authentication scheme. To be authenticated, we present a 3-D virtual environment where the user navigates and interacts with various objects. The sequence of actions and interactions toward the objects inside the 3-D environment   constructs the user’s 3-D password. The 3-D password can combine most existing authentication schemes such as textual passwords, graphical passwords, and various types of biometrics into a 3-D virtual environment. The design of the 3-D virtual environment and the type of objects selected determine the 3-D password key space.

Index Terms—Authentication, biometrics, graphical passwords, multifactor, textual passwords, 3-D passwords, 3-D virtual environment.

Introduction:
THE DRAMATIC increase of computer usage has given rise to many security concerns. One major security concern is authentication, which is the process of validating who you are to whom you claimed to be. In general, human authentication techniques can be classified as knowledge based (what
you know), token based (what you have), and biometrics (what you are).
Knowledge-based authentication can be further divided into two categories as follows: 1) recall based and 2) recognition based [1]. Recall-based techniques require the user to repeat or reproduce a secret that the user created before. Recognitionbased techniques require the user to identify and recognize the
secret, or part of it, that the user selected before [1]. One of the most common recall-based authentication schemes used in the computer world is textual passwords. One major drawback of the textual password is its two conflicting requirements: the selection of passwords that are easy to remember and, at the same time, are hard to guess.

Related Work
Many graphical password schemes have been proposed  [6]–[8], [10]–[12]. Blonder [6] introduced the first graphical password schema. Blonder’s idea of graphical passwords is that by having a predetermined image, the user can select or touch regions of the image causing the sequence and the location of
the touches to construct the user’s graphical password. After Blonder [6], the notion of graphical passwords was developed. Many graphical password schemes have been proposed. Existing graphical passwords can be categorized into two categories as follows: 1) recall based and 2) recognition based [1]. Dhamija and Perrig [7] proposed Déjà Vu, which is a recognition-based graphical password system that authenticates users by choosing portfolios among decoy portfolios. These portfolios are art randomized portfolios. Each image is derived from an 8-B seed. Therefore, an authentication server does not need to store the whole image; it simply needs to store the 8-B seed. Another recognition-based graphical password is Passfaces [8]. Passfaces simply works by having the user select a subgroup of k faces from a group of n faces. For authentication, the system shows m faces and one of the faces belongs to the subgroup k. The user has to do the selection many times to complete the authentication process. Another scheme is the Story scheme [9], which requires the selection of pictures of objects (people, cars, foods, airplanes, sightseeing, etc.) to form a story line.

Our Approach
3-D PASSWORD SCHEME
In this section, we present a multifactor authentication scheme that combines the benefits of various authentication schemes. We attempted to satisfy the following requirements. 1) The new scheme should not be either recall based or recognition based only. Instead, the scheme should be a combination of recall-, recognition-, biometrics-, and token-based authentication schemes.
2) Users ought to have the freedom to select whether the 3-D password will be solely recall-, biometrics-, recognition-, or token-based, or a combination of two schemes or more. This freedom of selection is necessary because users
are different and they have different requirements. Some users do not like to carry cards. Some users do not like to provide biometrical data, and some users have poor memories. Therefore, to ensure high user acceptability,
the user’s freedom of selection is important. 3) The new scheme should provide secrets that are easy to remember and very difficult for intruders to guess. 4) The new scheme should provide secrets that are not easy to write down on paper. Moreover, the scheme secrets should be difficult to share with others. 5) The new scheme should provide secrets that can be easily
revoked or changed. Based on the aforementioned requirements, we propose

3D Password Overview
The 3-D password is a multifactor authentication scheme. The 3-D password presents a 3-D virtual environment containing various virtual objects. The user navigates through this environment and interacts with the objects. The 3-D password is simply the combination and the sequence of user interactions
that occur in the 3-D virtual environment. The 3-D password can combine recognition-, recall-, token-, and biometrics-based systems into one authentication scheme. This can be done by designing a 3-D virtual environment that contains objects that request information to be recalled, information to be recognized, tokens to be presented, and biometrical data to be verified. For example, the user can enter the virtual environment and type something on a computer that exists in (x1, y1, z1) position, then enter a room that has a fingerprint recognition device that exists in a position (x2, y2, z2) and provide his/her fingerprint. Then, the user can go to the virtual garage, open the car door, and turn on the radio to a specific channel. The combination and the sequence of the previous actions toward the specific objects construct the user’s 3-D password.

(10, 24, 91) Action = Open the office door;
(10, 24, 91) Action = Close the office door;
(4, 34, 18) Action = Typing, “F”;
(4, 34, 18) Action = Typing, “A”;
(4, 34, 18) Action = Typing, “L”;
(4, 34, 18) Action = Typing, “C”;
(4, 34, 18) Action = Typing, “O”;
(4, 34, 18) Action = Typing, “N”;
(10, 24, 80) Action = Pick up the pen;
(1, 18, 80) Action = Drawing, point = (330, 130).

Persuasive Cued Click-Points: Design, implementation, and evaluation of a knowledge-based authentication mechanism


Abstract—This paper presents an integrated evaluation of the Persuasive Cued Click-Points graphical password scheme,
including usability and security evaluations, and implementation considerations. An important usability goal for knowledge-based
authentication systems is to support users in selecting passwords of higher security, in the sense of being from an expanded
effective security space. We use persuasion to influence user choice in click-based graphical passwords, encouraging users to
select more random, and hence more difficult to guess, click-points.
Index Terms—authentication, graphical passwords, usable security, empirical studies


problems of knowledge-based authentication,
typically text-based passwords, are well known.
Users often create memorable passwords that are easy
for attackers to guess, but strong system-assigned
passwords are difficult for users to remember [6].
A password authentication system should encourage
strong passwords while maintaining memorability.
We propose that authentication schemes allow
user choice while influencing users towards stronger
passwords. In our system, the task of selecting weak
passwords (which are easy for attackers to predict)
is more tedious, discouraging users from making
such choices. In effect, this approach makes choosing
a more secure password the path-of-least-resistance.
Rather than increasing the burden on users, it is
easier to follow the system’s suggestions for a secure
password — a feature lacking in most schemes.