Economic metric to improve spam detectors
Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task....
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Gillani, Fida [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016transfer abstract |
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| Schlagwörter: |
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| Umfang: |
13 |
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| Übergeordnetes Werk: |
Enthalten in: Claude C. Roy, MD, October 21, 1928–July 2, 2015 - Alvarez, Fernando ELSEVIER, 2015, London |
|---|---|
| Übergeordnetes Werk: |
volume:65 ; year:2016 ; pages:131-143 ; extent:13 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.jnca.2016.02.019 |
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ELV03549977X |
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| 520 | |a Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. | ||
| 520 | |a Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. | ||
| 650 | 7 | |a Spam economics |2 Elsevier | |
| 650 | 7 | |a Consumer economics theory |2 Elsevier | |
| 650 | 7 | |a Spam detection |2 Elsevier | |
| 650 | 7 | |a Anomaly detection |2 Elsevier | |
| 650 | 7 | |a Email spam |2 Elsevier | |
| 700 | 1 | |a Al-Shaer, Ehab |4 oth | |
| 700 | 1 | |a AsSadhan, Basil |4 oth | |
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10.1016/j.jnca.2016.02.019 doi GBVA2016019000003.pica (DE-627)ELV03549977X (ELSEVIER)S1084-8045(16)30008-X DE-627 ger DE-627 rakwb eng 004 004 DE-600 610 VZ 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl 42.15 bkl Gillani, Fida verfasserin aut Economic metric to improve spam detectors 2016transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. Spam economics Elsevier Consumer economics theory Elsevier Spam detection Elsevier Anomaly detection Elsevier Email spam Elsevier Al-Shaer, Ehab oth AsSadhan, Basil oth Enthalten in Academic Press Alvarez, Fernando ELSEVIER Claude C. Roy, MD, October 21, 1928–July 2, 2015 2015 London (DE-627)ELV013451553 volume:65 year:2016 pages:131-143 extent:13 https://doi.org/10.1016/j.jnca.2016.02.019 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_40 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ 42.15 Zellbiologie VZ AR 65 2016 131-143 13 045F 004 |
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10.1016/j.jnca.2016.02.019 doi GBVA2016019000003.pica (DE-627)ELV03549977X (ELSEVIER)S1084-8045(16)30008-X DE-627 ger DE-627 rakwb eng 004 004 DE-600 610 VZ 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl 42.15 bkl Gillani, Fida verfasserin aut Economic metric to improve spam detectors 2016transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. Spam economics Elsevier Consumer economics theory Elsevier Spam detection Elsevier Anomaly detection Elsevier Email spam Elsevier Al-Shaer, Ehab oth AsSadhan, Basil oth Enthalten in Academic Press Alvarez, Fernando ELSEVIER Claude C. Roy, MD, October 21, 1928–July 2, 2015 2015 London (DE-627)ELV013451553 volume:65 year:2016 pages:131-143 extent:13 https://doi.org/10.1016/j.jnca.2016.02.019 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_40 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ 42.15 Zellbiologie VZ AR 65 2016 131-143 13 045F 004 |
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10.1016/j.jnca.2016.02.019 doi GBVA2016019000003.pica (DE-627)ELV03549977X (ELSEVIER)S1084-8045(16)30008-X DE-627 ger DE-627 rakwb eng 004 004 DE-600 610 VZ 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl 42.15 bkl Gillani, Fida verfasserin aut Economic metric to improve spam detectors 2016transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. Spam economics Elsevier Consumer economics theory Elsevier Spam detection Elsevier Anomaly detection Elsevier Email spam Elsevier Al-Shaer, Ehab oth AsSadhan, Basil oth Enthalten in Academic Press Alvarez, Fernando ELSEVIER Claude C. Roy, MD, October 21, 1928–July 2, 2015 2015 London (DE-627)ELV013451553 volume:65 year:2016 pages:131-143 extent:13 https://doi.org/10.1016/j.jnca.2016.02.019 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_40 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ 42.15 Zellbiologie VZ AR 65 2016 131-143 13 045F 004 |
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10.1016/j.jnca.2016.02.019 doi GBVA2016019000003.pica (DE-627)ELV03549977X (ELSEVIER)S1084-8045(16)30008-X DE-627 ger DE-627 rakwb eng 004 004 DE-600 610 VZ 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl 42.15 bkl Gillani, Fida verfasserin aut Economic metric to improve spam detectors 2016transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. Spam economics Elsevier Consumer economics theory Elsevier Spam detection Elsevier Anomaly detection Elsevier Email spam Elsevier Al-Shaer, Ehab oth AsSadhan, Basil oth Enthalten in Academic Press Alvarez, Fernando ELSEVIER Claude C. Roy, MD, October 21, 1928–July 2, 2015 2015 London (DE-627)ELV013451553 volume:65 year:2016 pages:131-143 extent:13 https://doi.org/10.1016/j.jnca.2016.02.019 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_40 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ 42.15 Zellbiologie VZ AR 65 2016 131-143 13 045F 004 |
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10.1016/j.jnca.2016.02.019 doi GBVA2016019000003.pica (DE-627)ELV03549977X (ELSEVIER)S1084-8045(16)30008-X DE-627 ger DE-627 rakwb eng 004 004 DE-600 610 VZ 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl 42.15 bkl Gillani, Fida verfasserin aut Economic metric to improve spam detectors 2016transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. Spam economics Elsevier Consumer economics theory Elsevier Spam detection Elsevier Anomaly detection Elsevier Email spam Elsevier Al-Shaer, Ehab oth AsSadhan, Basil oth Enthalten in Academic Press Alvarez, Fernando ELSEVIER Claude C. Roy, MD, October 21, 1928–July 2, 2015 2015 London (DE-627)ELV013451553 volume:65 year:2016 pages:131-143 extent:13 https://doi.org/10.1016/j.jnca.2016.02.019 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_40 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ 42.15 Zellbiologie VZ AR 65 2016 131-143 13 045F 004 |
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Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. 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Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. |
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Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. |
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Economic lifting has made email spam a scathing threat to the society due to its related exploits. Many spam detection schemes have been proposed employing the tendency of spam to alter the normal statistical behavior of mail traffic. Threshold tuning of these detectors is still a challenging task. Since, shooting down benign emails as spam (false positive), in pursuit of higher detection rates, can be detrimental. In this paper, we introduce a novel economic metric, based on the underlying spam economic system, to assist detectors in keeping their false positives at bay by associating detection accuracy to the spammer׳s cost. Hence, the sensitivity of a detector does not need to be tuned all the way up to maximize detection, but enough to make spamming cost unbearable to the spammer. Since, spam is all about making money ultimately. We also show that the statistical features used in our spam detectors can easily differentiate spam from benign and we also show that these features are hard to evade by the spammer. Our evaluation shows the effectiveness of this approach in considerably reducing the false positives for these detectors. |
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