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Book Reviews by kapil gupta

Research paper thumbnail of Kapil gupta Et

this presentation is persenal

Papers by kapil gupta

Research paper thumbnail of User Session Modeling for Effective Application Intrusion Detection

IFIP – The International Federation for Information Processing

With the number of data breaches on a rise, effective and efficient detection of anomalous activi... more With the number of data breaches on a rise, effective and efficient detection of anomalous activities in applications which manages data is critical. In this paper, we introduce a novel approach to improve attack detection at application layer by modeling user sessions as a sequence of events instead of analyzing every single event in isolation. We also argue that combining application access logs and the corresponding data access logs to generate unified logs eliminates the need to analyze them separately thereby resulting in an efficient and accurate system. We evaluate various methods such as conditional random fields, support vector machines, decision trees and naive Bayes, and experimental results show that our approach based on conditional random fields is feasible and can detect attacks at an early stage even when they are disguised within normal events.

Research paper thumbnail of Layered Approach Using Conditional Random Fields for Intrusion Detection

IEEE Transactions on Dependable and Secure Computing, 2010

Intrusion detection faces a number of challenges; an intrusion detection system must reliably det... more Intrusion detection faces a number of challenges; an intrusion detection system must reliably detect malicious activities in a network and must perform efficiently to cope with the large amount of network traffic. In this paper, we address these two issues of Accuracy and Efficiency using Conditional Random Fields and Layered Approach. We demonstrate that high attack detection accuracy can be achieved by using Conditional Random Fields and high efficiency by implementing the Layered Approach. Experimental results on the benchmark KDD '99 intrusion data set show that our proposed system based on Layered Conditional Random Fields outperforms other well-known methods such as the decision trees and the naive Bayes. The improvement in attack detection accuracy is very high, particularly, for the U2R attacks (34.8 percent improvement) and the R2L attacks (34.5 percent improvement). Statistical Tests also demonstrate higher confidence in detection accuracy for our method. Finally, we show that our system is robust and is able to handle noisy data without compromising performance.

Research paper thumbnail of The impact of minor Cr additions in low alloy steel on corrosion behavior in simulated well environment

npj Materials Degradation

Low alloy steel samples with different Cr content (0‒3 wt%) have been exposed to simulated well e... more Low alloy steel samples with different Cr content (0‒3 wt%) have been exposed to simulated well environment. It is revealed that the 3%Cr sample initially has the highest corrosion resistance. However, due to faster formation of a FexCayCO3 protective scale in the 0%Cr sample, this sample demonstrates the highest corrosion resistance after 2 days of exposure. While the FexCayCO3 scale is also formed in the 1%Cr sample, the scale is weakly adhered and porous, which does not enable good corrosion resistance. Although the scale formation is delayed in a sample with 3 wt%Cr, once it is formed, the presence of Cr-rich phase in this scale provides greater long-term corrosion protection. Localized corrosion attack is observed in the samples with 0% Cr and 1%Cr, whereas the 3%Cr sample shows no sign of localized attack due to initial pre-passivation and the ability to rebuild the protective scale.

Research paper thumbnail of Kapil gupta Et

this presentation is persenal

Research paper thumbnail of User Session Modeling for Effective Application Intrusion Detection

IFIP – The International Federation for Information Processing

With the number of data breaches on a rise, effective and efficient detection of anomalous activi... more With the number of data breaches on a rise, effective and efficient detection of anomalous activities in applications which manages data is critical. In this paper, we introduce a novel approach to improve attack detection at application layer by modeling user sessions as a sequence of events instead of analyzing every single event in isolation. We also argue that combining application access logs and the corresponding data access logs to generate unified logs eliminates the need to analyze them separately thereby resulting in an efficient and accurate system. We evaluate various methods such as conditional random fields, support vector machines, decision trees and naive Bayes, and experimental results show that our approach based on conditional random fields is feasible and can detect attacks at an early stage even when they are disguised within normal events.

Research paper thumbnail of Layered Approach Using Conditional Random Fields for Intrusion Detection

IEEE Transactions on Dependable and Secure Computing, 2010

Intrusion detection faces a number of challenges; an intrusion detection system must reliably det... more Intrusion detection faces a number of challenges; an intrusion detection system must reliably detect malicious activities in a network and must perform efficiently to cope with the large amount of network traffic. In this paper, we address these two issues of Accuracy and Efficiency using Conditional Random Fields and Layered Approach. We demonstrate that high attack detection accuracy can be achieved by using Conditional Random Fields and high efficiency by implementing the Layered Approach. Experimental results on the benchmark KDD '99 intrusion data set show that our proposed system based on Layered Conditional Random Fields outperforms other well-known methods such as the decision trees and the naive Bayes. The improvement in attack detection accuracy is very high, particularly, for the U2R attacks (34.8 percent improvement) and the R2L attacks (34.5 percent improvement). Statistical Tests also demonstrate higher confidence in detection accuracy for our method. Finally, we show that our system is robust and is able to handle noisy data without compromising performance.

Research paper thumbnail of The impact of minor Cr additions in low alloy steel on corrosion behavior in simulated well environment

npj Materials Degradation

Low alloy steel samples with different Cr content (0‒3 wt%) have been exposed to simulated well e... more Low alloy steel samples with different Cr content (0‒3 wt%) have been exposed to simulated well environment. It is revealed that the 3%Cr sample initially has the highest corrosion resistance. However, due to faster formation of a FexCayCO3 protective scale in the 0%Cr sample, this sample demonstrates the highest corrosion resistance after 2 days of exposure. While the FexCayCO3 scale is also formed in the 1%Cr sample, the scale is weakly adhered and porous, which does not enable good corrosion resistance. Although the scale formation is delayed in a sample with 3 wt%Cr, once it is formed, the presence of Cr-rich phase in this scale provides greater long-term corrosion protection. Localized corrosion attack is observed in the samples with 0% Cr and 1%Cr, whereas the 3%Cr sample shows no sign of localized attack due to initial pre-passivation and the ability to rebuild the protective scale.