SPAM

As all the traffic between the public Internet and the customer's desktop must be interconnected through ISP's access network, this work thus makes use of the transpor- tation traffic log gathered from backbone router to develop SMTP flooding detection system (SFDS), so that the most spam could be detected and stopped at the original fan-out network. The system has been deployed over a TANet (Taiwan Academic Net- work) backbone node for assisting network users grasping the abnormal SMTP sources with suddenly increase email requests. The result indicates that there is a high proportion of the notified spam could be detected in advance.

e-mail has become an important means of electronic communication but the viability of its usage is marred by Unsolicited Bulk e-mail (UBE) messages. UBE consists of many types like pornographic, virus infected and 'cry-for-help' messages as well as fake and fraudulent offers for jobs, winnings and medicines. UBE poses technical and socio-economic challenges to usage of e-mails. To meet this challenge and combat this menace, we need to understand UBE. Towards this end, the current paper presents a content-based textual analysis of nearly 3000 winnings-announcing UBE. Technically, this is an application of Text Parsing and Tokenization for an un-structured textual document and we approach it using Bag Of Words (BOW) and Vector Space Document Model techniques. We have attempted to identify the most frequently occurring lexis in the winnings-announcing UBE documents. The analysis of such top 100 lexis is also presented. We exhibit the relationship between occurrence of a word fr...

Email has become an important means of electronic communication but the viability of its usage is marred by Un-solicited Bulk Email (UBE) messages. UBE poses technical and socioeconomic challenges to usage of emails. Besides, the definition and understanding of UBE differs from one person to another. To meet these challenges and combat this menace, we need to understand UBE. Towards this end, this paper proposes a classifier for UBE documents. Technically, this is an application of un-structured document classification using text content analysis and we approach it using supervised machine learning technique. Our experiments show the success rate of proposed classifier is 98.50%. This is the first formal attempt to provide a novel tool for UBE classification and the empirical results show that the tool is strong enough to be implemented in real world.

Unsolicited bulk email (aka. spam) is a major problem onthe Internet. To counter spam, several techniques, ranging from spam filters to mail protocol extensions Iike hashcash, have been proposed. In this paper we investigate the effectiveness of several spam filtering techniques and technologies. Our analysis was performed by simulating email traffic under different conditions. We show that genetic algorithm based spam filters perform best at server level and naive Bayesian filters are the most appropriate for filtering at user level.

Towards Symbiotic Spam E-mail Filtering Clotilde Lopes1 and Paulo Cortez1 and Pedro Sousa2 Abstract. This position paper discusses the use of symbiotic filtering, a novel distributed data mining approach that combines contentbased and collaborative filtering for spam detection. 1 INTRODUCTION Unsolicited e-mail (spam) is a serious problem, as it consumes resources (eg time spent reading unwanted messages) and it is also used to spread malicious content (eg viruses). Currently, spam represents around 80-90% of all email messages ...

Cybercrime has grown voluminous pleats with veneration to the development of first-hand technology. The flout towards cybercrime has become todays prime centric with developing countries frugality as well. Nonetheless hefty figure of security and privacy available with modern expertise; phishing, spam and email fraud are more equally exasperating. In this intellect learning, the authors' primary interest is to make a healthy charge on phishing, spam and email fraud towards the wealthy personal information and realm.Official and business related information needs added exhaustive sanctuary and discretion from the hackers to be on the top in their one-to-one arena.

Buried in the source code for papers uploaded to Academia is an assessment of work quality, "high," "low," or "spam" (although at first this may be "null," or sometimes no quality may be assigned at all, perhaps because the upload is a video rather than an academic paper). Just how or why these assignments are made is a mystery that at the time of writing the Academia support team are looking into (inquiring after the engineering team). At times works that by no stretch can be regarded as spam are designated in this way. Whilst there does not seem to be a one-to-one relationship, it would seem that this may have an adverse impact on search engine visibility.

La deteccion de intrusos en redes de computadoras a partir del enfoque de aprendizaje automatico presenta algunas deficiencias dadas por la propia naturaleza de la aplicacion. La principal viene dada por el modesto despliegue de sistemas de deteccion basados en algoritmos de aprendizaje bajo las restricciones impuestas por los entornos reales. En este articulo se describen y proponen tres variantes de pre procesamiento sobre el conjunto de datos KDD99, incluye seleccion de atributos. Luego la experimentacion se realiza primeramente a partir de evaluar algoritmos representativos en entornos estacionarios sobre las variantes obtenidas a partir de pre procesar KDD99. Por ultimo, dado que el trafico de red es un flujo constante de datos, en el cual pueden existir variaciones de conceptos relacionadas con las tasas de falsos positivos, unido al hecho de que no se encuentran muchas investigaciones que aborden la deteccion de intrusos en entornos de flujos de datos nos conduce a realizar u...

Many successful query expansion techniques ignore information about the term dependencies that exist within natural language. However, researchers have recently demonstrated that consistent and significant improvements in retrieval effectiveness can be achieved by explicitly modelling term dependencies within the query expansion process. This has created an increased interest in dependency-based models. State-of-the-art dependency-based approaches primarily model term associations known within structural linguistics as syntagmatic associations, which are formed when terms co-occur together more often than by chance. However, structural linguistics proposes that the meaning of a word is also dependent on its paradigmatic associations, which are formed between words that can substitute for each other without effecting the acceptability of a sentence. Given the reliance on word meanings when a user formulates their query, our approach takes the novel step of modelling both syntagmatic and paradigmatic associations within the query expansion process based on the (pseudo) relevant documents returned in web search. The results demonstrate that this approach can provide significant improvements in web retrieval effectiveness when compared to a strong benchmark retrieval system.

SUMMARYIP prefix hijacking is a major threat to the security of the Internet routing system owing to the lack of authoritative prefix ownership information. Despite many efforts to design IP prefix hijack detection schemes, no existing design satisfies all the critical requirements of a truly effective system, i.e. to be real‐time, deployable, and robust. In this paper, we present a novel approach that detects IP prefix hijacking in the current Internet environment. The focus of this work is on maintaining the Border Gateway Protocol routing infrastructure and not relying on mutual cooperation to ensure ease of deployment. In addition, we look at fingerprinting two autonomous systems that have the same IP prefix to distinguish hijacking events from legitimate routing updates. This paper proposes a practical and deployable IP prefix hijacking detection algorithm with live hosts on the Internet. Copyright © 2012 John Wiley & Sons, Ltd.

A social behavioral profile accurately reflects a user’s OSN activity patterns. People access OSNs using both traditional desktop PCs and new emerging mobile devices. With more than one billion users worldwide, OSNs are a new venue of innovation with many challenging research problems. In this paper, we study the social behaviors of OSN users, i.e., their usage of OSN services, and the application of which in detecting the compromised accounts. We capture user behavior with the following metrics: user connectivity, user activity and user reactions.we validate and characterize the user social activity on OSN.The study is based on detailed clickstream data ,the clickstream data reveals key features of the social network workloads, such as how frequently people connect to social networks and for how long, as well as the types and sequences of activities that users conduct on these sites. we pay attention to the characteristics of social behaviors we review malicious behaviors of OSN us...

Instant messaging is popular and relatively new form of social interaction. Instant Messengers (IMs) and Social Networking Sites (SNS) may contain harmful and suspicious messages, which are untraced, leading to hindrance for network communication and cyber security. In this paper, we provided an introduction to various frameworks and review the details of different systems developed so far. Here we attempted to analysis various frameworks and classify them based on different factors, which leads to a better understanding on their operation. We also discuss the implementation details of these systems including the tools used by various authors and the metrics used to measure their performance.

This article presents an extensive characterization of a spam-infected e-mail workload. The study aims at identifying and quantifying the characteristics that significantly distinguish spam from non-spam (i.e., legitimate) traffic, assessing the impact of spam on the aggregate traffic, providing data for creating synthetic workload models, and drawing insights into more effective spam detection techniques. Our analysis reveals significant differences in the spam and non-spam workloads. We conjecture that these differences are consequence of the inherently different mode of operation of the e-mail senders. Whereas legitimate e-mail transmissions are driven by social bilateral relationships, spam transmissions are a unilateral spammer-driven action.

With millions of users tweeting around the world, real time search systems and different types of mining tools are emerging to allow people tracking the repercussion of events and news on Twitter. However, although appealing as mechanisms to ease the spread of news and allow users to discuss events and post their status, these services open opportunities for new forms of spam. Trending topics, the most talked about items on Twitter at a given point in time, have been seen as an opportunity to generate traffic and revenue. ...

The EASY-GOING deconvolution (EGdeconv) program is extended to enable fast and automated fitting of multiple quantum magic angle spinning (MQMAS) spectra guided by evolutionary algorithms. We implemented an analytical crystallite excitation model for spectrum simulation. Currently these efficiencies are limited to two-pulse and z-filtered 3QMAS spectra of spin 3/2 and 5/2 nuclei, whereas for higher spinquantum numbers ideal excitation is assumed. The analytical expressions are explained in full to avoid ambiguity and facilitate others to use them. The EGdeconv program can fit interaction parameter distributions. It currently includes a Gaussian distribution for the chemical shift and an (extended) Czjzek distribution for the quadrupolar interaction. We provide three case studies to illustrate EGdeconv's capabilities for fitting MQMAS spectra. The EGdeconv program is available as is on our website http:// egdeconv.science.ru.nl for 64-bit Linux operating systems.

The amount of information that people share on social networks is constantly increasing. People also comment, annotate, and tag their own content (videos, photos, notes, etc.), as well as the content of others. In many cases, the content is tagged manually. One way to make this time-consuming manual tagging process more efficient is to propagate tags from a small set of tagged images to the larger set of untagged images automatically. In such a scenario, however, a wrong or a spam tag can damage the integrity and reliability of the automated propagation system. Users may make mistakes in tagging, or irrelevant tags and content may be added maliciously for advertisement or self-promotion. Therefore, a certain mechanism insuring the trustworthiness of users or published content is needed. In this chapter, we discuss several image retrieval methods based on tags, various approaches to trust modeling and spam protection in social networks, and trust modeling in geotagging systems. We th...

A soft error redirection is a URL redirection to a page that returns the HTTP status code 200 (OK) but has actually no relevant content to the client request. Since such redirections degrade the performance of web search engines in many ways, it is highly desirable to remove as many of them as possible. We propose a novel approach to detect soft error redirections by analyzing redirection logs collected during crawling operation. Experimental results on huge crawl data show that our measure can classify soft error redirections effectively.

Short Message Service (SMS) has become one of the most important media of communications due to the rapid increase of mobile users and it's easy to use operating mechanism. This flood of SMS goes with the problem of spam SMS that are generated by spurious users. The detection of spam SMS has gotten more attention of researchers in recent times and is treated with a number of different machine learning approaches. Supervised machine learning approaches, used so far, demands a large amount of labeled data which is not always available in real applications. The traditional semi-supervised methods can alleviate this problem but may not produce good results if they are provided with only positive and unlabeled data. In this paper, we have proposed a novel semi-supervised learning method which makes use of frequent itemset and ensemble learning ðFIELÞ to overcome this limitation. In this approach, Apriori algorithm has been used for finding the frequent itemset while Multinomial Naive Bayes, Random Forest and LibSVM are used as base learners for ensemble learning which uses majority voting scheme. Our proposed approach works well with small number of positive data and different amounts of unlabeled dataset with higher accuracy. Extensive experiments have been conducted over UCI SMS spam collection data set, SMS spam collection Corpus v.0.1 Small and Big which show significant improvements in accuracy with very small amount of positive data. We have compared our proposed FIEL approach with the existing SPY-EM and PEBL approaches and the results show that our approach is more stable than the compared approaches with minimum support.

This study examined the influence of workload and dual-task performance decrements associated with the SPAM technique. Participants performed the Air Traffic Scenarios Test (ATST), which is a low fidelity air traffic control simulator developed by the Federal Aviation Administration. Performance on the ATST was followed by post-run questionnaires (baseline conditions) or in conjunction with SPAM queries, word shadowing lists, or memory lists (secondary task conditions). SPAM was no different from our baseline conditions in terms of subjective workload. In comparison to other secondary tasks, SPAM tended to yield workload levels intermediate to List Memory (high cognitive load) and Word Shadowing (low cognitive load). SPAM was found to lower performance relative to baseline conditions in three of the seven observed performance measures. These findings suggest that the use of a "ready" prompt for probe question administration is not sufficient for reducing performance decrements associated with secondary tasks.

The Semantic Web Services Initiative Architecture (SWSA) committee has created a set of architectural and protocol abstractions as a foundation for Semantic Web service technologies.This article summarizes the committee’s findings, emphasizing its review of requirements gathered from several different environments.The authors also identify the scope and potential requirements for a Semantic Web services architecture.

Internet based communication systems appear in many forms from email to Instant Messenger and chat services to Voice over IP (VoIP). Common weaknesses of these current communication systems include inherent security vulnerabilities to attacks such as SPAM/SPIT/SPIM and DDoS, a lack of separation between routing address and identity, and a lack of message receiver controllability. Based on these observations, we describe preliminary ideas and analysis of a new communication architecture called DSL (Davis Social Links), which integrates the trust relationships of social networks into the internet communication infrastructure to provide receiver controllability, traceability, and global connectivity without centralized services or globally unique IDs. Although it is still in the early stages of development, we believe that DSL can help thwart many largescale information-based attacks faced by the Internet community.

Kebutuhan air merupakan salah satu kebutuhan utama yang sangat berpengaruh bagi makhluk hidup di dunia. Khusus untuk manusia, air bersih sangat penting untuk menunjang kehidupan sehari-hari seperti kebutuhan rumah tangga, kebutuhan industri dan tempat umum. Penelitian ini bertujuan untuk mengetahui jumlah kebutuhan air bersih dalam 10 tahun ke depan (2030). Dengan menggunakan data yang diperoleh dari PDAM Delta Tirta Sidoarjo dan beberapa rujukan terkait, diperoleh informasi bahwa Total kebutuhan air bersih menurut jumlah penduduk sebesar 14.487.336 L/hari/orang pada tahun 2020 dan 17.281.512 L/hari/orang pada tahun 2030 mengalami peningkatan sebesar 2.794.176 L/hari/orang.Total kebutuhan air menurut jumlah pelanggan sebesar 3.522.150 L/hari/orang pada tahun 2020 dan 4.430.250 L/hari/orang pada tahun 2030 mengalami peningkatan sebesar 908.100 L/hari/orang. NRW kehilangan air pada tahun 2020 sebesar 33,40% dan pada tahun 2030 NRW kehilangan air sebesar 39,80%.Pada tahun 2020 sampai 2...

Este trabajo se propone revisar el tema del archivo y la construcción de la memoria como instancias claves del proceso de desubjetivación en Spam de Rafael Spregelburd. Los intentos de (re)construir una voz a partir de (sus) desechos (correo basura) y de los diversos artefactos tecnológicos y soportes que configuran esta subjetividad siempre mediada o diferida, nos conducen a pensar ambas nociones, por un lado, como dispositivos escénicos, esto es, indagar acerca de las relaciones intermediales en el teatro contemporáneo y la producción del dramaturgo específicamente; y, por otro lado, como problemas teóricos a partir de la figura del entre que atraviesa toda la pieza. Por tal motivo dedicaremos una parte significativa del análisis a las didascalias, que se configuran como intervalo y diferimiento entre el texto teatral y la puesta en escena, así como una interrupción intratextual.

The problem of optimization has always existed in all scientific and industrial fields. This issue has been raised in mathematics and computer science as finding the best answer among different answers. This problem has become an essential area for research in the last decades. Not only analytical methods but also meta-heuristic methods have been developed to solve this problem. The Lion Optimizing Algorithm (LOA) is a meta-heuristic algorithm for optimization problems. The LOA was inspired by various aspects of lions' lives, such as hunting, mating, roaming, defense, and migration. So far, this algorithm has been used in several fields such as classification, clustering, image processing, cloud computing, and task scheduling. The LOA has proved promising results in these areas. Multiple algorithms have flourished to tackle various constraints and challenges of the LOA. In this paper, the LOA, its variants, and applications are reviewed from the beginning until now.

1. Genetic stock identification (GSI) frequently is used to assess spawning/breeding population contributions to mixtures of individuals. Although multiple estimation routines are available for conducting GSI, their performance may vary depending on characteristics of assessed source populations and mixtures and of employed genetic markers. 2. We conducted simulations to compare performance of several likelihood-based GSI estimation routines. Estimation routines were implemented in SPAM, ONCOR and AD Model Builder (ADMB). Two ADMB routines were evaluated, one based on conditional maximum likelihood estimation (ADMB-MLE), similar to SPAM and ONCOR, and one based on conditional penalized maximum likelihood estimation (ADMB-PMLE). The simulations examined how performance varied by number of source populations, population divergence levels, number of evaluated loci, and source population and mixture sample sizes. Evaluations included scenarios with many loci with low levels of polymorphism for assessing performance when single nucleotide polymorphism (SNP) markers are incorporated in analyses. 3. Mixture sample size and source population genetic divergence accounted for most of the explained variability in simulation results. Overall, routines based on conditional maximum likelihood estimation (SPAM, ONCOR and ADMB-MLE) had similar levels of accuracy, including scenarios mimicking SNP markers, with SPAM having slightly better accuracy than ONCOR and ADMB-MLE. The accuracy of the ADMB-PMLE routine in many scenarios was noticeably poorer than the other routines, although in some instances accuracy of the ADMB-PMLE estimates approached the other routines with large mixture sample sizes. SPAM, ONCOR and ADMB-MLE also generally had similar levels of performance with respect to consistency, whereas ADMB-PMLE varied widely in consistency due in part to poor accuracy. 4. Because SPAM and ONCOR typically performed better than the ADMB-MLE routine, there appears to be little need for users to program their own likelihood-based estimation routines for standard GSI analyses, although for specialized applications (e.g. modelling contributions as functions of ecological or demographic features), it may be necessary for users to program their own routines. Given the performance of the ADMB-PMLE routine, additional research is needed to determine an appropriate configuration (e.g. penalty, optimization algorithm) for a penalized maximum likelihood GSI estimator.

In this paper, I develop an economic argument for regulating the sending of junk emails, and examine the efficiency of various approaches to regulate junk emails. The first part of the paper develops an externality model of spam to show that in the absence of regulation, junk emails are inefficient. Next, I analyse the regulatory approaches presently used in the United States in three categories: opt-out, filtering and blocking, and opt-in. The study finds that spam can be both a positive externality as well as a negative one. However, the likelihood of being a negative externality is more probable. Absence regulation, no allocation of a property right to spam leads to an efficient level of spam. An examination of the three categories show that only the opt-in approach ensures that there is no net social loss, but not necessarily at a socially efficient level of spam. Hence, it is only a second best solution. Based on the conclusions that opt-in is the best solution given the constraints of transaction cost, the paper suggests a set of policy conclusions that serve as guidelines for countries enacting laws to regulate junk emails or spam.

In earlier days we were asking our friends or relatives for their opinions regarding products which we want to purchase from the merchants. But now a day's E-commerce is gaining more and more popularity. Whatever query we are having, we can find its answer from World Wide Web. Merchants are also selling their products online and at a same time they are asking customer's review regarding products, which customer has bought. This would be beneficial to merchants as well as customers also. As the numbers of customers are growing, reviews received by products are also growing in large amount. Thus, mining opinions from product reviews is an important research topic. However, existing research is more focused towards classification and summarization of such online opinions. An important issue related to the trustworthiness of online opinions has been neglected most often. There is no reported study on assessing the trustworthiness of reviews. This research paper aims to first classify the opinion (positive or negative) carried out by detection of a review(spam or a nonspam) based on rating behavior and finally removing spam reviews, which provides a trusted review to help the customer in taking appropriate buying decision. This paper proposes a novel and effective technique, which will represent classified opinion in form of "chernoff face".

Internet of Things (IoT) is a promising technology enabling physical devices like cameras, home appliances, and other devices to communicate and interoperate with each other. The next wave transforms our homes, society, enterprises, and cities with the massive presence of IoT devices. The devices in the Internet of Things (IoT) may exchange sensitive data, and an important issue for any organization is to get the data secured and protected. The preliminary requirement for this is a mechanism detecting and reporting anomalies automatically to some central controller. Therefore, this mechanism should be able to classify legit IoT devices from unauthorized ones. Malicious IoT devices, non-IoT devices, and other types of man-in-themiddle traffic sources must be quarantined for noncompliance. This helps formulate administrative policies and regulate/police traffic in the network for better QoS management. This work proposed a framework-based hierarchical deep neural network (HDNNs) to distinguish IoT devices from non-IoT devices using a feature set of IoT-specific traffic. A system has been designed based on HDNN that classifies IoT devices to their specific categories and identifies new entrants with reasonable accuracy. The results show that HDNN can distinguish IoT and non-IoT devices with higher accuracy and as well as classify IoT devices into the respective classes with the required accuracy.

At present, spam is an actual and increasing problem that compromises email communications across the world. Thus, several solutions have been proposed to stop or reduce the amount of this threat. However, methods based on negative selection algorithm (NSA) lack continuous adaptability and suffer from low detection performance. Moreover, these methods require a large number of detectors to cover all non-self spaces. Thus, this study proposes a new e-mail detection approach based on an improved NSA called combined clustered NSA and fruit fly optimization (CNSA-FFO). The system combines actual NSA with k-means clustering and FFO to enhance the efficiency of classic NSA. Experiments results in spam benchmark show that the performance of CNSA-FFO is better than the classic NSA and NSA-PSO, especially in terms of detection accuracy, positive prediction, and computational complexity.

O grande número de mensagens indesejadas recebidas pelos usuários em suas caixas de correio eletrônico faz com que se busquem formas de combater ou amenizar os problemas ocasionados pelo recebimento de spams. O presente trabalho destina-se ao estudo de técnicas e ferramentas que podem ser utilizadas no combate ao spam, apresentando o funcionamento do correio eletrônico e do protocolo SMTP, as formas mais comuns de spams existentes atualmente, estatísticas de ocorrência, bem como as formas utilizadas para envio desse tipo de mensagem. Também será mostrado o funcionamento e um comparativo dos testes realizados com três ferramentas open source: Bogofilter, SpamAssassin e SpamPal destinadas ao combate ao spam.

Spam has long been identified as a problem that web search engines are required to deal with. Large collection sizes are also an increasing issue for institutions that do not have the necessary resources to process them in their entirety. In this paper we investigate the effect that withholding documents identified as spam has on the resources required to process large collections. We also investigate the resulting search effectiveness and efficiency when different amounts of spam are withheld. We find that by removing spam at indexing time we are able to decrease the index size without affecting the indexing throughput, and are able to improve search precision for some thresholds.

In this paper we aim to detect the compromised machines in a network that are involved in the spamming activities, widely known as spam zombies. Given that spamming provides a key economic incentive for attackers to recruit the large number of compromised machine, we develop a spam zombie detection system named SPOT by keeping track of outgoing messages in a network. SPOT is designed based on a powerful statistical tool called Sequential Probability Ratio Test (SPRT), which has bounded false positive and false negative error rates.

This article is discusses about the implementation of legal certainty at Perumda Tirta Manuntung Balikpapan in the company's management authority within practices and to explain various deviations of legal certainty that occur in Perumda Tirta Manuntung Balikpapan. The legal certainty of Perumda Tirta Manuntung Balikpapan is based on Regional Regulation Number 8 of 2020 which concern about General Companies of Tirta Manuntung Balikpapan Region. This article is used normative juridicial as the methodology with a literature study approach by qualitative analysis. The results of this article showed us in conceptual, it is based on Regional Regulation Number 8 of 2020 which concern about General Companies Perumda Tirta Manuntung Balikpapan, it has been running based on substance which regulate about legal certainty of Perumda Tirta Manuntung to manage a company. But sometimes, the legal certainty doesn't running based on regulation and it getting some deviations which will inflict a financial loss who accure in the Perumda Tirta Manuntung Balikpapan. Furthermore, the bureaucratic intervention can make Perumda Tirta Manuntung Balikpapan can't managing it based on good corporate governance and independecy principle by substance that has been promulgated.

With increase in amount of information being stored in remote locations, there is a need to have an efficient method that facilitates information retrieval. Most information retrieval operations use client server architecture which ends up taking much of bandwidth. Client server architecture moves data during operation and this takes too much bandwidth. This paper discusses mobile agents which present an ideal method that can be used in information retrieval due their ability to move the code instead of data and this property makes them suitable in saving bandwidth. Mobile agent is a technology generating a lot of interest due to its benefits in areas such as ecommerce, information retrieval. Mobile agent is a program that acts on behalf of the user and it is capable of moving from one location to another and performs action. The experiment was carried out to compare the performance of mobile agents and client server method in which it was found that mobile agents formed better that...

E-mail communication still has to cope with certain security problems. The most visible result is the mass of unsolicited messages outnumbering the regular e-mails in magnitudes. The technical reasons for this unfavorable situation are manifold, e.g., unreliable sender authentication, loose and ad-hoc coupling between the involved servers, and only few ways to complain about misbehavior of users of foreign systems. In this paper, we will show that resolving these problems requires a deeper analysis of the related economic aspects. We will demonstrate in a simplified game-theoretical model that the individual choices of the involved parties will lead to a suboptimal state, where less effort is put into the security of e-mail communication. As a consequence, some kind of cooperation between the involved parties is needed to implement functions which provide a social benefit rather than an individual one.

Commette il reato di diffamazione aggravata colui il quale, inoltrando messaggi nella rete internet attraverso un gruppo di discussione, insulti il proprio antagonista definendolo “spammer” e diffondendo la notizia di sue precedenti condanne.
La circostanza che l'imputato si sia auto investito del compito di individuare, affrontare e segnalare con ogni sistema di diffusione, coloro che in rete lo raggiungono con messaggi pubblicitari non desiderati (c.d. “spam”) non assume importanza scriminante; il diritto di critica non può, infatti, estendersi sino a consentire l'offesa e l'umiliazione pubblica dei
propri avversari, neppure di coloro che siano stati sanzionati amministrativamente e penalmente per violazione delle regole del codice di riservatezza

In this article, we aim at relating emotions and gender stereotypes through the analysis of the narratives containedinspame-mails.Wewillpresentfourdifferenttypesofspame-mailsfromacorpus consistingof450emails,theirlengthbeingbetweenfourandfifty-twolinesofextension.Theywere receivedbetweenlate2009andmid-2013,andwritteninEnglish,Spanish,PortugueseandFrench. Ouranalysiswillbecarriedoutintwosteps.Inthefirststep,thediscursive-linguisticstrategieswill bedescribed.Inthesecondstep,thelinguisticexpressionofemotionswillbeaddressed.Wewill relyonthePositioningTheoryofRomHarrétoidentifywhereauthorsandreadersarepositioned inthenarratives.

This research entitled "Analysis local financial performance Its Influence To Capital Expenditure Of Regency Of Batang Hari ". The purpose of the study is 1). To know and DOF, RKD And RKKD of the districts of Batang Hari region; 2). To know and analyze the influence of DOF, RKD And RKKD on capital expenditure The districts of Batang Hari. This research uses descriptive quantitative analysis method. Descriptive analysis to analyze local financial capacity and quantitative analysis to analyze the influence of local financial ability on capital expenditure. The result of analysis shows that the financial capacity of Batang Hari Regency is seen from the degree of fiscal autonomy and the ratio of regional financial independence is categorized very low as well as the regional financial dependency ratio is still very high. The degree of fiscal autonomy have significant effect on the capital spending of the local government of Batang Hari Regency, then the ratio of local financial...

This thesis is dedicated to my parents and my loving husband ACKNOWLEDGMENTS I would like to take this opportunity to thank everyone who enabled my research. I would like to express my sincere gratitude and appreciation to my advisor, Professor Kenneth J. Christensen, for providing me with the opportunity to work in the research area of controlling spam, for his expert guidance and mentorship, and for his encouragement and support at all levels. I would also like to thank Professors Miguel Labrador and Nagarajan Ranganathan for serving on my committee and for offering constructive comments.. I would like to thank Dr. David Rabson , Department of Physics for offering his comments and support. I would like to thank all staff members of USF Tech Support for their timely help in supporting my test environment. I would like to thank my family and friends for their lifelong love and support. Finally, special thanks go to my husband Kamal, for his support, encouragement and patience.

In the current scenario, the data on the web is growing exponentially. Social media is generating a large amount of data such as reviews, comments, and customer's opinions on a daily basis. This huge amount of user generated data is worthless unless some mining operations are applied to it. As there are a number of fake reviews so opinion mining technique should incorporate Spam detection to produce a genuine opinion. Nowadays, there are a number of people using social media opinions to create their call on shopping for product or service. Opinion Spam detection is an exhausting and hard problem as there are many faux or fake reviews that have been created by organizations or by the people for various purposes. They write fake reviews to mislead readers or automated detection system by promoting or demoting target products to promote them or to degrade their reputations. The proposed technique includes Ontology, Geo location and IP address tracking, Spam words Dictionary using Naïve Bayes, Brand only review detection and tracking account used.

Nous essayons, dans ces quelques lignes, présenter le phénomène du spamming qui pose de sérieux problèmes au bon fonctionnement de la messagerie électronique en particulier, et du commerce électronique en générale. En effet, l'ampleur des Spams ne cesse de croître et ces préjudices ne cessent de se limiter. Le Canada qui occupe le 4ème rang mondial avec un taux de plus de 50% de connexion Internet à domicile, subit le mal du spamming et essaye de trouver des solutions techniques et juridiques qui peuvent surmonter cet obstacle.

Voice over internet protocol is an artistic technology in Internet today. And it's very powerful over the PSTN. As VoIP is more flexible and low cost compare to PSTN, many marketing agencies uses it for marketing call or for message broadcasting calls and messages which make customary users disgruntled. This problem is known as unsolicited bulk calls, called spam over VoIP. In Cellular technology, One method has been implemented to protect the Spam call, called Do Not Disturb(DND).Which is complex to accomplish in VoIP Scenario. This papet presents the fundamentals of SIP(Session Initiation Protocol). SIP is the one of the protocols for the VoIP application which has been text based open protocol. Proposed works on a survey on detection and prevention on spam over VoIP. Main focus of proposed work is to provide a mechanism to protect spam call in VoIP scenario. Proposed work contains an innovative solution, which would combined the multiple spam improvement techniques in order to get maximum success rate for blocking spam call.

We propose a new spam detection algorithm that uses structural relationships between senders and recipients of email as the basis for spam detection. A unifying representation of users and receivers in the vectorial space of their contacts is constructed, that leads to a natural definition of similarity between them. This similarity is then used to group email senders and recipients into clusters. Historical information about the messages sent and received by the clusters is obtained by forwarding messages to an auxiliary ...

In this paper, I develop an economic argument for regulating the sending of junk emails, and examine the efficiency of various approaches to regulate junk emails. The first part of the paper develops an externality model of spam to show that in the absence of regulation, junk emails are inefficient. Next, I analyse the regulatory approaches presently used in the United States in three categories: opt-out, filtering and blocking, and opt-in. The study finds that spam can be both a positive externality as well as a negative one. However, the likelihood of being a negative externality is more probable. Absence regulation, no allocation of a property right to spam leads to an efficient level of spam. An examination of the three categories show that only the opt-in approach ensures that there is no net social loss, but not necessarily at a socially efficient level of spam. Hence, it is only a second best solution. Based on the conclusions that opt-in is the best solution given the constraints of transaction cost, the paper suggests a set of policy conclusions that serve as guidelines for countries enacting laws to regulate junk emails or spam.

As the email is becoming a prominent mode of communication so are the attempts to misuse it to take undue advantage of its low cost and high reachability. However, as email communication is very cheap, spammers are taking advantage of it for advertising their products, for committing cybercrimes. So, researchers are working hard to combat with the spammers. Many spam detections techniques and systems are built to fight spammers. But the spammers are continuously finding new ways to defeat the existing filters. This paper describes the existing spam filters techniques and proposes a multi-level architecture for spam email detection. We present the analysis of the architecture to prove the effectiveness of the architecture.