"May I borrow Your Filter?" Exchanging Filters to Combat Spam in a Community

Leveraging social networks in computer systems can be effective in dealing with a number of trust and security issues. Spam is one such issue where the "wisdom of crowds" can be harnessed by mining the collective knowledge of ordinary individuals. In this paper, we present a mechanism through which members of a virtual community can exchange information to combat spam. Previous attempts at collaborative spam filtering have concentrated on digest-based indexing techniques to share digests or fingerprints of emails that are known to be spam. We take a different approach and allow users to share their spam filters instead, thus dramatically reducing the amount of traffic generated in the network. The resultant diversity in the filters and cooperation in a community allows it to respond to spam in an autonomic fashion. As a test case for exchanging filters we use the popular SpamAssassin spam filtering software and show that exchanging spam filters provides an alternative method to improve spam filtering performance

Towards symbiotic spam e-mail filtering

This position paper discusses the use of symbiotic filtering, a novel distributed data mining approach that combines contentbased and collaborative filtering for spam detection

Symbiotic filtering for spam email detection

This paper presents a novel spam filtering technique called Symbiotic Filtering (SF) that aggregates distinct local filters from several users to improve the overall perfor- mance of spam detection. SF is an hybrid approach combining some features from both Collaborative (CF) and Content-Based Filtering (CBF). It allows for the use of social networks to personalize and tailor the set of filters that serve as input to the filtering. A comparison is performed against the commonly used Naive Bayes CBF algorithm. Several experiments were held with the well-known Enron data, under both fixed and incremental symbiotic groups. We show that our system is competitive in performance and is robust against both dictionary and focused con- tamination attacks. Moreover, it can be implemented and deployed with few effort and low communication costs, while assuring privacy.Fundação para a Ciência e a Tecnologia (FCT) - bolsa PTDC/EIA/64541/200

MapReduce based RDF assisted distributed SVM for high throughput spam filtering

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityElectronic mail has become cast and embedded in our everyday lives. Billions of legitimate emails are sent on a daily basis. The widely established underlying infrastructure, its widespread availability as well as its ease of use have all acted as catalysts to such pervasive proliferation. Unfortunately, the same can be alleged about unsolicited bulk email, or rather spam. Various methods, as well as enabling architectures are available to try to mitigate spam permeation. In this respect, this dissertation compliments existing survey work in this area by contributing an extensive literature review of traditional and emerging spam filtering approaches. Techniques, approaches and architectures employed for spam filtering are appraised, critically assessing respective strengths and weaknesses. Velocity, volume and variety are key characteristics of the spam challenge. MapReduce (M/R) has become increasingly popular as an Internet scale, data intensive processing platform. In the context of machine learning based spam filter training, support vector machine (SVM) based techniques have been proven effective. SVM training is however a computationally intensive process. In this dissertation, a M/R based distributed SVM algorithm for scalable spam filter training, designated MRSMO, is presented. By distributing and processing subsets of the training data across multiple participating computing nodes, the distributed SVM reduces spam filter training time significantly. To mitigate the accuracy degradation introduced by the adopted approach, a Resource Description Framework (RDF) based feedback loop is evaluated. Experimental results demonstrate that this improves the accuracy levels of the distributed SVM beyond the original sequential counterpart. Effectively exploiting large scale, ‘Cloud’ based, heterogeneous processing capabilities for M/R in what can be considered a non-deterministic environment requires the consideration of a number of perspectives. In this work, gSched, a Hadoop M/R based, heterogeneous aware task to node matching and allocation scheme is designed. Using MRSMO as a baseline, experimental evaluation indicates that gSched improves on the performance of the out-of-the box Hadoop counterpart in a typical Cloud based infrastructure. The focal contribution to knowledge is a scalable, heterogeneous infrastructure and machine learning based spam filtering scheme, able to capitalize on collaborative accuracy improvements through RDF based, end user feedback. MapReduce based RDF Assisted Distributed SVM for High Throughput Spam Filterin

Cyber Infrastructure Protection: Vol. III

Despite leaps in technological advancements made in computing system hardware and software areas, we still hear about massive cyberattacks that result in enormous data losses. Cyberattacks in 2015 included: sophisticated attacks that targeted Ashley Madison, the U.S. Office of Personnel Management (OPM), the White House, and Anthem; and in 2014, cyberattacks were directed at Sony Pictures Entertainment, Home Depot, J.P. Morgan Chase, a German steel factory, a South Korean nuclear plant, eBay, and others. These attacks and many others highlight the continued vulnerability of various cyber infrastructures and the critical need for strong cyber infrastructure protection (CIP). This book addresses critical issues in cybersecurity. Topics discussed include: a cooperative international deterrence capability as an essential tool in cybersecurity; an estimation of the costs of cybercrime; the impact of prosecuting spammers on fraud and malware contained in email spam; cybersecurity and privacy in smart cities; smart cities demand smart security; and, a smart grid vulnerability assessment using national testbed networks.https://press.armywarcollege.edu/monographs/1412/thumbnail.jp

“May I borrow Your Filter?” Exchanging Filters to Combat Spam in a Community

Leveraging social networks in computer systems can be effective in dealing with a number of trust and security issues. Spam is one such issue where the “wisdom of crowds” can be harnessed by mining the collective knowledge of ordinary individuals. In this paper, we present a mechanism through which members of a virtual community can exchange information to combat spam. Previous attempts at collaborative spam filtering have concentrated on digest-based indexing techniques to share digests or fingerprints of emails that are known to be spam. We take a different approach and allow users to share their spam filters instead, thus dramatically reducing the amount of traffic generated in the network. The resultant diversity in the filters and cooperation in a community allows it to respond to spam in an autonomic fashion. As a test case for exchanging filters we use the popular SpamAssassin spam filtering software and show that exchanging spam filters provides an alternative method to improve spam filtering performance

Email stress and its management in public sector organisations

Email stress: what are its causes? how is it measured? can it be solved? The literature review revealed that, despite the term being well used and recognised, discussions surrounding the root cause of email stress had reached little consensus and the concept was not well understood. By its very nature, email stress theory had fallen victim to the academic debate between psychological vs. physiological interpretations of stress which, as a result of either choice, limited more progressive research. Likewise an array of email management strategies had been identified however, whilst some generated quick successes, they appeared to suffer longevity issues and were not maintained a few months after implementation in the workplace. The purpose of this research was to determine whether email communication causes employees psychological and physiological stress and investigate the impact of email management strategies in the workplace. A pragmatic philosophy placed the research problem as central and valued the differences between paradigms to promote a mixed-method approach to research. The decision to pair both case studies and action research methods ensured a framework for presenting results and an actionable solution was achieved. In direct response to the research aims an original email stress measuring methodology was devised that combined various data collection tools to measure and investigate email stress. This research design was applied and evaluated ‘email free time’ and email filing at the '''''''''''' '''''''''''''''''''''''''. Results of the study showed an increased stress response to occur during email use, i.e. caused employees’ increased blood pressure, heart rate, cortisol and perceived stress, and a number of adverse effects such as managing staff via email, social detachment, blame and cover-yourback culture were identified. Findings revealed ‘email free time’ was not a desirable strategy to manage email stress and related stressors, whereas email filing was found more beneficial to workers well-being. Consolidation of the data gathered from the literature review and research findings were used to develop an initial conceptualisation of email stress in the form of two models, i.e. explanatory and action. A focus group was conducted to validate the proposed models and a further investigation at the '''''''''''''''''''' ''''''''''''' was carried out to critique the use of an email training intervention. The results showed some improvements to employees’ behaviour after the training, e.g. improved writing style, email checked on fewer occasions each day and fewer sufferers of email addiction. The initial models devised, alongside the latter findings, were synthesised to create a single integrative multidimensional model of email stress and management strategies. The model made an original contribution to knowledge in terms of theory, i.e. to conceptualise email stress, and practice, i.e. to offer practical solutions to the email worker