Effective scheduling strategies for boosting performance on rule-based spam filtering frameworks

Ruano-Ordás, David; Fdez-Glez, Jorge; Fdez-Riverola, Florentino; Méndez, J.

doi:10.1016/j.jss.2013.07.036

Cited by 16 publications

(32 citation statements)

References 5 publications

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“…To take more advantage of the above mentioned advances (i.e. achieve the SFE conditions to stop a filter evaluation early and achieve an adequate parallelization of rules), some scheduling heuristics have been introduced [8,9,10].…”

Section: Throughput Optimizationmentioning

confidence: 99%

“…In this context, and given the extensive utilization and increasing significance of rule-based filtering frameworks for the anti-spam domain, several studies have addressed the optimization of parameters (rule scores and scheduling plan) to improve their accuracy [4,5,6,7] and classification throughput [8,9,10]. However, previous works on throughput optimization are based on simple heuristics without taking into account its relation to accuracy.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evolutionary Multi-objective Scheduling for Anti-Spam Filtering Throughput Optimization

Ruano-Ordás

Basto‐Fernandes

Yevseyeva

et al. 2017

Lecture Notes in Computer Science

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Abstract. This paper presents an evolutionary multi-objective optimization problem formulation for the anti-spam filtering problem, addressing both the classification quality criteria (False Positive and False Negative error rates) and email messages classification time (minimization). This approach is compared to single objective problem formulations found in the literature, and its advantages for decision support and flexible/adaptive anti-spam filtering configuration is demonstrated. A study is performed using the Wirebrush4SPAM framework anti-spam filtering and the SpamAssassin email dataset. The NSGA-II evolutionary multi-objective optimization algorithm was applied for the purpose of validating and demonstrating the adoption of this novel approach to the anti-spam filtering optimization problem, formulated from the multi-objective optimization perspective. The results obtained from the experiments demonstrated that this optimization strategy allows the decision maker (anti-spam filtering system administrator) to select among a set of optimal and flexible filter configuration alternatives with respect to classification quality and classification efficiency.

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Section: Throughput Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evolutionary Multi-objective Scheduling for Anti-Spam Filtering Throughput Optimization

Ruano-Ordás

Basto‐Fernandes

Yevseyeva

et al. 2017

Lecture Notes in Computer Science

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“…During this process, all the rules comprising the WSF2 filter are loaded into the ruleset data structure represented in Figure 1(b) and sorted by a rule-scheduling algorithm. This rule planning module is implemented into the prescheduler t data type and, as outlined in Ruano-Ordás and colleagues [34], it is responsible for elaborating an optional arrangement of the execution of the filtering rules in order to improve WSF2 classification throughput. Moreover, with the aim of reducing the filtering time, all available parsers, spam filtering techniques, and event-handlers are loaded into memory within this stage.…”

Section: Main Designmentioning

confidence: 99%

WSF2: A Novel Framework for Filtering Web Spam

Fdez-Glez

Ruano-Ordás

Laza

et al. 2016

Scientific Programming

Self Cite

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Over the last years, research on web spam filtering has gained interest from both academia and industry. In this context, although there are a good number of successful antispam techniques available (i.e., content-based, link-based, and hiding), an adequate combination of different algorithms supported by an advanced web spam filtering platform would offer more promising results. To this end, we propose the WSF2 framework, a new platform particularly suitable for filtering spam content on web pages. Currently, our framework allows the easy combination of different filtering techniques including, but not limited to, regular expressions and well-known classifiers (i.e., Naïve Bayes, Support Vector Machines, and C5.0). Applying our WSF2 framework over the publicly available WEBSPAM-UK2007 corpus, we have been able to demonstrate that a simple combination of different techniques is able to improve the accuracy of single classifiers on web spam detection. As a result, we conclude that the proposed filtering platform is a powerful tool for boosting applied research in this area.

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“…Step 7: Algorithm stores the newly classified pattern in its local cache for future use It has been adopted by international companies (such as Symantec or McAfee) and small and medium enterprises (SMEs) [11]. Anti-spam RBS are combination of a decision threshold value plus a set of scored rules (See Fig.…”

Section: Pattern Detectionmentioning

confidence: 99%

“…After examining all rules, a message is classified as spam if its global counter value is greater than or equal to the configured threshold. Both (i) scored rules and (ii) the filter threshold are commonly stored in regular text files in order to facilitate their exchange between computers [11].…”

Section: Pattern Detectionmentioning

confidence: 99%

Study on the Effectiveness of Spam Detection Technologies

Iqbal¹,

Abid²,

Ahmad³

et al. 2016

IJITCS

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Abstract-Nowadays, spam has become serious issue for computer security, because it becomes a main source for disseminating threats, including viruses, worms and phishing attacks. Currently, a large volume of received emails are spam. Different approaches to combating these unwanted messages, including challenge response model, whitelisting, blacklisting, email signatures and different machine learning methods, are in place to deal with this issue. These solutions are available for end users but due to dynamic nature of Web, there is no 100% secure systems around the world which can handle this problem. In most of the cases spam detectors use machine learning techniques to filter web traffic. This work focuses on systematically analyzing the strength and weakness of current technologies for spam detection and taxonomy of known approaches is introduced.

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Effective scheduling strategies for boosting performance on rule-based spam filtering frameworks

Cited by 16 publications

References 5 publications

Evolutionary Multi-objective Scheduling for Anti-Spam Filtering Throughput Optimization

Evolutionary Multi-objective Scheduling for Anti-Spam Filtering Throughput Optimization

WSF2: A Novel Framework for Filtering Web Spam

Study on the Effectiveness of Spam Detection Technologies

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