user accounts

Top PDF user accounts:

Detecting Unknown or Fake User Accounts on Different Micro blogging and Social Media Networks

Detecting Unknown or Fake User Accounts on Different Micro blogging and Social Media Networks

In terms of SMN management, matching anonymous users across different SMN platforms will give integrated details on every user and inform corresponding laws, like targeting services provisions. In theory, the cross-platform explorations permit a bird’s- eye read of SMN user behaviors. However, nearly all recent SMN-based studies focus on one SMN platform, yielding incomplete information. So, this study verifies strategy of crossing multiple social media network platforms to color a comprehensive image of those behaviors.
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Toots, tastes and tester shots: user accounts of drug sampling methods for gauging heroin potency

Toots, tastes and tester shots: user accounts of drug sampling methods for gauging heroin potency

Results: Across the study sites, multiple methods of sampling “ heroin ” were identified, sometimes used in combination, ranging from non-injecting routes (snorting, smoking or tasting a small amount prior to injection) to injecting a partial dose and waiting. Partial injection took different forms: a “ slow shot ” where the user injected a portion of the solution in the syringe, keeping the needle in the injection site, and continuing or withdrawing the syringe or a “ tester shot ” where the solution was divided into separate injections. Other techniques included getting feedback from others using heroin of the same batch or observing those with higher tolerance injecting heroin from the same batch before judging how much to inject themselves. Although a minority of those interviewed described using these drug sampling techniques, there is clearly receptivity among some users to protecting themselves by using a variety of methods.
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Wiley Microsoft PowerShell VBScript and JScript Bible Feb 2009 pdf

Wiley Microsoft PowerShell VBScript and JScript Bible Feb 2009 pdf

W indows scripting gives everyday users and administrators the ability to automate repetitive tasks, complete activities while away from the computer, and perform many other time-saving activities. Windows scripting accomplishes all of this by enabling you to create tools to automate tasks that would otherwise be handled manually, such as creating user accounts, generating log files, managing print queues, or examining system information. By eliminating manual processes, you can double, triple, or even quadruple your productivity and become more effective and efficient at your job. Best of all, scripts are easy to create and you can rapidly develop prototypes of applications, procedures, and utili- ties; and then enhance these prototypes to get exactly what you need, or just throw them away and begin again. This ease of use gives you the flex- ibility to create the kinds of tools you need without a lot of fuss.
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Self Organized Detection of Relationships in a Network

Self Organized Detection of Relationships in a Network

A typical local area network was selected with about five hundred and fifty user accounts. The accounts were grouped into five categories of access (i.e. credentials) on the network. These categories were ‘administration’, ‘faculty’, ‘student’, ‘staff’, and ‘public’. The actions sup- posed to be carried through these accounts during net- work access involved five different types of actions on twelve different target hosts or servers. The actions in- volved were ‘create’, ‘modify’, ‘read’, ‘delete’, and ‘not available/unauthorized’. The target hosts were centrally placed in a room. The service available on different tar- get hosts contained files and programs. The objective was to examine the network setup vis-à-vis Figure 4, usi- ng the procedure outlined in the algorithm described in the previous section.
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Symetric Groups of Authentications and Key Management with Session Based Automated Key Updation

Symetric Groups of Authentications and Key Management with Session Based Automated Key Updation

ABSTRACT: Authenticated key exchange (AKE) is one of the most important applications in applied cryptography, where a user interacts with a server to set up a session key where pre-registered information (aka. authentication factor), such as a password or biometrics, of the user is stored. While single-factor AKE is widely used in practice, higher security concerns call for multi-factor AKE schemes, e.g. combining both passwords and biometrics and device simultaneously. However, in some schemes, security is even weakened in the sense that leakage of one authentication factor will defeat the whole authentication process. Furthermore, an inevitable by-product arises that the usability of the protocol often drops greatly. To summarize, the existing multi-factor protocols did not provide enough security and efficiency simultaneously. Here, we make one step ahead by proposing a very efficient authentication method. We define the security model and give the according security analysis. To overcome the security issues proposed method implements textual, graphical, and biometric and device password to access the user accounts and an efficient AES algorithm for data transaction which is more secured algorithm is used.
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Symmetric Groups of Authentications and Key Management with Session Based Automated Key Updation

Symmetric Groups of Authentications and Key Management with Session Based Automated Key Updation

Abstract : Authenticated key exchange (AKE) is one of the most important applications in applied cryptography, where a user interacts with a server to set up a session key where pre-registered information (aka. authentication factor), such as a password or biometrics, of the user is stored. While single-factor AKE is widely used in practice, higher security concerns call for multi-factor AKE schemes, e.g. combining both passwords and biometrics and device simultaneously. However, in some schemes, security is even weakened in the sense that leakage of one authentication factor will defeat the whole authentication process. Furthermore, an inevitable by-product arises that the usability of the protocol often drops greatly. To summarize, the existing multi-factor protocols did not provide enough security and efficiency simultaneously. Here, we make one step ahead by proposing a very efficient authentication method. We define the security model and give the according security analysis. To overcome the security issues proposed method implements textual, graphical, and biometric and device password to access the user accounts and an efficient AES algorithm for data transaction which is more secured algorithm is used.
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Mac OS X Server User Management

Mac OS X Server User Management

You can set up home directory locations when you create user accounts. If a user doesn’t have a home directory, he or she will not be able to log in (unless you select “Work offline if the user’s home directory is not available”; to do so, click Computers, then click Security). Mac OS 9 managed clients mount the user’s home directory automatically when a user logs in. The user is the owner of his or her own home directory and has full access to its contents. Macintosh Manager prevents access to other users’ home directories, even if the folder’s permissions have been set to allow access.
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DETECTION ENVIRONMENT FORMATION METHOD FOR ANOMALY DETECTION SYSTEMS

DETECTION ENVIRONMENT FORMATION METHOD FOR ANOMALY DETECTION SYSTEMS

However, when working with social data, factors such as instability in the quality of user content (spam and false accounts), problems with ensuring the privacy of users' personal data during storage and processing, as well as frequent updates of the user model and functionality should be taken into account. All this requires continuous improvement of algorithms for solving various analytical and business problems. The processing of social data also requires the development of appropriate algorithmic and infrastructural solutions that take into account their dimensionality. For example, the Facebook social network database today contains more than 1 billion user accounts and more than 100 billion connections between them. Every day, users add over 200 million photos and leave more than 2 billion comments on various network objects. To date, most of the existing algorithms that effectively solve actual problems are not able to process data of a similar dimension in a reasonable time. In this regard, there is a need for new solutions, 441 allowing for the distributed processing and storage of data without significant loss of quality results.
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070-6094-00_4404F05_Installation_Instruction_May86.pdf

070-6094-00_4404F05_Installation_Instruction_May86.pdf

When complete, you will return the customer a factory standard 4405 system with the addition of their old password file, containing user accounts, and blank user direct[r]

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Beyond the hashtag: Circumventing content moderation on social media

Beyond the hashtag: Circumventing content moderation on social media

In their Community Guidelines and similar publicfacing policies, the platforms explain that they prohibit user accounts and individual posts that ‘glorify’, ‘promote’ or ‘encourage’ eati[r]

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Syngress   MCSE Exam 70 294  Planning, Implementing and Main pdf

Syngress MCSE Exam 70 294 Planning, Implementing and Main pdf

In addition to names used by computers and domains, user accounts also have distinct methods of being named. User accounts have a UPN that can be used to log on from Windows 2000, XP Professional, and Server 2003 machines.They also have a backward- compatible login name known as the pre-Windows 2000 name. During the process of cre- ating a new user account, Active Directory will suggest a pre-Windows 2000 name that is based on the first 20 characters of the UPN that you type in. Either name can be changed at any time.The pre-Windows 2000 logon name is limited to 20 characters. Although the pre-Windows 2000 name can still be used to log on to domains on newer operating sys- tems, the UPN logon name is preferred when logging on from Windows 2000 or later. UPNs consist of a logon account name and a UPN suffix. By default, the UPN suffix is the domain name that contains the user account. For example, if the user account was located in a domain called syngress.com, then this domain name would also be the UPN suffix. The logon name and UPN suffix is connected together using the at (@) sign.This makes it appear like an Internet e-mail address (username@domain).
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Multi Bank Smart Card with User Behavior Monitoring Using HMM & Formula Verification

Multi Bank Smart Card with User Behavior Monitoring Using HMM & Formula Verification

ABSTRACT: Big data is a trending topic that captures considerable attention of many researchers. It is really opportunity based environment where many data scientists were created. Big data analytics would definitely lead to valuable knowledge for many organizations. Integration of Big Data, Business analytical and RFID like technology is supposed to be recent trends in IT. In this paper we propose an idea for a banking sector particularly for a Debit/ATM card transaction in which multiple user accounts were integrated into a single smart card with unique PIN numbers accordingly. The user behaviour is monitored through HMM model and this smart card is also tracked using RFID technology. From our perception we can assure this idea will improve the existing bank management system.
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The Reach of Politics via Twitter—Can That Be Real?

The Reach of Politics via Twitter—Can That Be Real?

In Table 4, twenty percent of the followers of these messages are fake followers. The percentage of inactive followers is 44%. In writing about the followers of “stars” authors have fre- quently come close to characterizing the inactive followers as also not real; accounts that were opened and then the persons never returned. But that seems a somewhat less likely interpre- tation in this case. We know that many people use Twitter as a source of very fast news (Pew Research Center for the People & the Press, 2012). Since these 200 messages are largely from sources of the news media it does not seem unexpected that 44% of the followers are inactive. This interpretation is also consistent with the report of the CEO of Twitter. Dick Costolo announced that 40% of the people with Twitter accounts do not tweet, but use Twitter to follow others (Long, 2012). And 36% of the followers are good; they follow, are followed and post messages to Twitter. The raw numbers are taken from a sample. Comparing the size of this sample with the report about number of messages from Twitter this looks like roughly a one-third sample (Boynton, 2012c). In this sample the 500 million that are inactive or good is a very big communication stream. It is not the number of people receiving a message, but it is a meas- ure of the flow of communication that evening. Messages were going out at a very high volume to followers of the high profile user accounts.
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Tampering with Twitter’s Sample API

Tampering with Twitter’s Sample API

To collect Twitter data, researchers typically use the freely available API endpoints for public data. There are three different APIs to collect Twitter data. The Representational State Transfer (REST) API provides information about individual user accounts or popular topics and allows for sending or liking Tweets as well as following accounts. The Stream- ing APIs are used for real-time collection of Tweets and come in two flavors. First, the Filter API extracts Tweets based upon a user’s query containing keywords, user accounts, or geographic areas. The Filter API is used for studying Twitter content based on a pre- defined set of topics, user accounts, or locations. In contrary, the Sample API delivers a purportedly random 1% sample of all publicly sent Tweets, currently about 3.5 to 4 mil- lion Tweets per day. When interested in trends or emerging topics, the Sample API is used. By archiving Sample API Tweets, non-predictable events (e.g. natural disasters, terrorist attacks) can be analyzed in retrospect because this sample cuts across all topics on the site.
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A Narrative Study Exploring Survivor/Service User Professionals' Accounts
of Sharing Personal Experiences at Work

A Narrative Study Exploring Survivor/Service User Professionals' Accounts of Sharing Personal Experiences at Work

Laura firstly uses a 'representativeness' discourse (70-2) to position herself as not really , or, no longer 'one of them', perhaps, also an attempt to justify clients’ 'othering' of her. Switching from “telling” (73) to “disclose” (75) whilst broadening to all clients (75), Laura then draws upon a 'self-disclosure' discourse to construct it as changing the boundaries of the relationship (implying concern should only be about the client; 75-8), becoming 'non-therapeutic' (80). However, she contests this, reconstructing non-disclosure as an unhelpful distancing, with implications of power (81-3). The vulnerability Laura would feel (77-8), suggests the boundary is to protect her from exposure. Although this seems like an individualising explanation, vulnerability is perhaps conferred by a dominant 'mental illness' discourse which would construct her as incapable (76). Supporting this interpretation, following the second story of clients othering her, Laura justifies not sharing with: “I don't want that bad day to be seen as oh she's ill or she's mad and we can't trust her to cope” [659]. The media work (97-9) perhaps stands as a reminder of the importance of her survivor/service-user experiences to her identity as a psychologist (having chosen to ‘speak out’), as well as creating a risk of being 'found out'.
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Captcha as Graphical Passwords Scheme for Authentication of Users

Captcha as Graphical Passwords Scheme for Authentication of Users

secured login authentication and validation sche me. It allows the user choice towards stronger and secured passwords than the conventional text passwords. In this syste m, text based captcha grid and image based captcha grid plays as a graphical passwords. Click text grid comprises of characters (i.e.) alphabets, numbers, special characters, in that grid confusing characters will be excluded like „0‟ & „o‟ to avoid confusion. For click image, pools of image can be displayed, in that user need to choose their required passwords by done through enter via click based. So it resists the bots and online guessing attacks. By using hard AI problem, user can bypass the dictionary attacks; Xss(cross side scripting) doesn’t work with the distorted images. By using dual view technology, it eradicates shoulder surfing attacks and relay attacks. It allows the user for secured and trustable authentication.
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Tontine Savings Accounts

Tontine Savings Accounts

investors against market risk or longevity risk, so they don’t need to set aside reserves to back up any guarantees. For a relatively trivial fee, they would merely invest and custody passively-managed funds, keep track of when investors die, reallocate forfeited assets to surviving investor accounts, and deliver payouts.

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Syngress   Mission Critical!   Windows 2000 Server Administr pdf

Syngress Mission Critical! Windows 2000 Server Administr pdf

X.500 is a directory service standard ratified by the International Telecommunications Union (ITU-T) in 1988 and modified in 1993 and 1997. It was intended to provide a means to develop an easy-to-use elec- tronic directory of people that would be available to all Internet users. The X.500 directory specifies a common root of a hierarchical tree. Contrary to its name, the root of the tree is at the top level, and all other containers are below it. The X.500 standard includes several types of containers with a specific naming convention for them. In this naming convention, each por- tion of a name is specified by the abbreviation of the object type or con- tainer it represents. A user has a CN= before the username to represent its “Common Name,” a C= precedes a country, and an organization is heralded by an O=. When compared to IP domain names—for example, host.subdo- main.domain—the X.500 version of CN=host/C=US/O=Org appears exces- sively complicated.
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ABSTRACT: In social network worldwide there are a lot of people having twitter accounts. Every new and old user

ABSTRACT: In social network worldwide there are a lot of people having twitter accounts. Every new and old user

ABSTRACT: In social network worldwide there are a lot of people having twitter accounts. Every new and old user trying to create a new account in twitter for his own purposes like they can follow and tweet to the celebrity and the popular persons but some users giving the fake details in their profile like country, place, and locations. Twitter a micro blogging service that enables users to post messages (―tweets‖) of up to 140 Characters supports a variety of communicative practices; participants use Twitter to converse with individuals, groups, and the public at large, so when conversations emerge, they are often experienced by broader audiences than just the interlocutors. This paper examines the practice of retweeting as a way of intelligence commenting in a group likewise digital marketing by which participants can be ―in a conversation.‖ While retweeting has become a convention inside Twitter, participants embrace it for diverse reasons and using varying styles. Our data and analysis reveal the messiness of retweeting by highlighting how issues of authorship, attribution, and communicative fidelity are negotiated in diverse ways. Using a series of case studies and empirical data, this paper maps out different conversational aspects of retweeting digital intelligence commenting.
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Efficient Spam Filtering System Based on Smart Cooperative Subjective and Objective Methods

Efficient Spam Filtering System Based on Smart Cooperative Subjective and Objective Methods

 When viewing the list of emails in any folder in any email account, the user has two modes or options: the Lightweight mode and the full processing mode. In lightweight mode, no spam analysis takes place; the headers only are fetched form the remote email serv- ers. No data is stored on the system database. This mode may be fast in the beginning because no email body is downloaded nor spam processing. However, the user can have all the other classical features like moving the emails to another folder or deleting the emails. In addition, in this mode, the user can classify any email he/she opens as spam, gray or non-spam. His rating and spam-classification on a message will be taken into account. In the Full processing mode, the unread emails in the Inboxes are thoroughly ex- amined using the objective and the subjective spam filtering techniques. Email contents (except the at- tachments) are fetched from the server only once, af- ter being processed, they are stored on the system in- ternal database. Viewing the emails using this mode may by slow at the beginning depending upon the number of non-fetched emails. After fetching the emails, reviewing the email folders will be very fast.  When the user open any email in any account, he/she
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