Krishnan Kannoorpatti

Corrosion Behaviour of High-Chromium White Iron Hardfacing Alloys in an Alkaline Solution

Hardfacing alloys of high-chromium white irons (HCWI) deposited using welding are well known for their wear resistance. These materials are applied in conditions needing not only wear resistance but also corrosion. In this study, the HCWI alloys were exposed to alkaline solutions of pH 14. Anodic polarization technique was used to study the corrosion behaviour. The experimental results found that corrosion occurs on carbides in preference to the matrix. Pourbaix diagrams of carbides were found to be very useful in explaining the corrosion behaviour of the hardfacing alloys. The significance of carbide corrosion to the use of hardfacing alloys is discussed. Possible methods to mitigate corrosion are proposed.

A critical review of Bitcoins usage by cybercriminals

Bitcoin is a new form of global digital currency based on peer-to-peer network, enabling a new payment system, and also a completely decentralised cryptocurrency. The P2P network consists of a digital file listing transactions like a ledger, a copy of which is also maintained on every computer on the network, and the transactions are also broadcasted in the public ledger of the Bitcoin network. Anonymity is the core feature that makes Bitcoin popular among people around the world. This feature is attained through the Bitcoin addresses in the public ledger, which represents the users in the Bitcoin network. Because of the illicit use of Bitcoins, the level of anonymity has reduced even though the users are still using the anonymizers like TOR to keep the anonymity stronger to connect to the Bitcoin network. In this paper, we analyse the complete process of transaction of Bitcoins and the anonymity thatlies in that process. The study also focuses on finding the forensic artefacts and the investigative way of approach towards the Bitcoin using forensic tools. The forensic tools are used to analyse the web browser activities, local drive, hard disk image, cookies, downloads and session data related to Bitcoins. The attacker can relate the transaction of the users and can control the Bitcoin blocks by even delaying the transactions. This research will focus on the methods in which the memory and even mobile devices involved in the transaction could be captured and analysed.

Corrosion Behaviour of High Chromium White Iron Hardfacing Alloys in Acidic and Neutral Solutions

Hardfacing alloys of High Chromium White Irons (HCWI) were deposited on low carbon steel using Shielded Metal Arc Welding. Microstructure of HCWI consists of primary carbides, eutectic carbides and eutectic austenitic/martensitic matrix. This study investigated the corrosion behaviour of HCWI in both acid and neutral solutions. The corrosion behaviour of HCWI was evaluated using anodic polarisation technique. It was found that in acid solution at pH 1.5, corrosion occurs on eutectic austenite/martensitic matrix whereas at pH 2, the corrosion occurs on eutectic carbides. In the neutral environment at pH 7, corrosion of HCWI occurred in the eutectic austenite/martensite matrix in the presence of chloride ions, while in the buffered solution, corrosion occurred in the carbides. The results of this study show that the corrosion mechanism of HCWI for both acid and neutral environments was due to potential difference between carbides and eutectic austenite/martensitic matrix. The superimposed Pourbaix diagrams of chromium carbides with iron (Fe) and niobium carbide were useful in explaining the behaviour of HCWI in both acid and neutral solutions.

Development of an Artificial Neural Network Model for CO 2 Corrosion Prediction

Carbon dioxide corrosion (CO2) is responsible for a third of all corrosion-related failures in the oil and gas industry. Due to the fact that there are too many environmental and metallurgical factors with complex interactions, it has been difficult to effectively and accurately predict the rate of CO2 corrosion in any given situation. This work utilises artificial neural network (ANN) techniques to develop a model that can predict CO2 corrosion rates. An experimental and field database of CO2 corrosion of carbon steel was collated, analysed and then used to develop the model. Significance of the selected parameters influencing CO2 corrosion in the oil and gas industry was evaluated using principal component analysis. The final ANN model achieved a correlation coefficient of 0.964 with an accuracy of ±1.6 mm. A graphical user interface was also developed for the model to allow its deployment for further study of CO2 corrosion.

A Review of Ransomware Families and Detection Methods

Ransomware has become a significant problem and its impact is getting worse. It has now become a lucrative business as it is being offered as a service. Unlike other security issues, the effect of ransomware is irreversible and difficult to stop. This research has analysed existing ransomware classifications and its detection and prevention methods. Due to the difficulty in categorizing the steps none of the existing methods can stop ransomware. Ransomware families are identified and classified from the year 1989 to 2017 and surprisingly there are not much difference in the pattern. This paper concludes with a brief discussion about the findings and future work of this research.

An improved face recognition method using Local Binary Pattern method

Security system based on biometrics is becoming more popular everyday as a part of safety and security measurement against all kind of crimes. Among several kinds of biometric security systems, face recognition is one of the most popular one. It is one of the most accurate, mostly used recognition methods in modern world. In this paper, two most popular face recognition methods have been discussed and compared using average image on Yale database. To reduce calculation complexity, all training and test images are converted into gray scale images. The whole face recognition process can be divided into two parts face detection and face identification. For face detection part, Viola Jones face detection method has been used out of several face detection methods. After face detection, face is cropped from the actual image to remove the background and the resolution is set as 150×150 pixels. Eigenfaces and fisherfaces methods have been used for face identification part. Average images of subjects have been used as training set to improve the accuracy of identification. Both methods are investigated using MATLAB to find the better performance under average image condition. Accuracy and time consumption has been calculated using MATLAB code on Yale image database. In future, this paper will be helpful for further research on comparison of different face recognition methods using average images on different database.

A theoretical review of social media usage by cyber-criminals

Social media plays an integral part in individuals everyday lives as well as for companies. Social media brings numerous benefits in peoples lives such as to keep in touch with close ones and specially with relatives who are overseas, to make new friends, buy products, share information and much more. Unfortunately, several threats also accompany the countless advantages of social media. The rapid growth of the online social networking sites provides more scope for criminals and cyber-criminals to carry out their illegal activities. Hackers have found different ways of exploiting these platform for their malicious gains. This research englobes some of the common threats on social media such as spam, malware, Trojan horse, cross-site scripting, industry espionage, cyber-bullying, cyber-stalking, social engineering attacks. The main purpose of the study to elaborates on phishing, malware and click-jacking attacks. The main purpose of the research, there is no particular research available on the forensic investigation for Facebook. There is no particular forensic investigation methodology and forensic tools available which can follow on the Facebook. There are several tools available to extract digital data but its not properly tested for Facebook. Forensics investigation tool is used to extract evidence to determine what, when, where, who is responsible. This information is required to ensure that the sufficient evidence to take legal action against criminals.

A Novel Approach for Steganography App in Android OS

The process of hiding information in a scientific and artistic way is known as Steganography. The information hidden cannot be easily retrieved or accessed and is unidentifiable. In this research, some of the existing methods for image steganography has been explained. These are LSB (Least Significant Bits) substitution method, DCT (Discrete Cosine Transform) and DWT (Discrete Wavelet Transform). A comparative analysis of these techniques depicted that LSB is the easiest and most efficient way of hiding information. But this technique can be easily attacked and targeted by attackers as it changes the image resolution. Using LSB technique an application was created for image steganography because it hides the secret message in binary coding. To overcome this problem a RSA algorithm was used in the least significant bits of pixels of image. Additionally, a QR code was generated in the encryption process to make it more secure and allow the quality of the image to remain as intact, as it was before the encryption. PNG and JPEG formats were used as the cover image in the app and findings also indicated the data was fully recovered.

An Efficient Method for Detecting Fraudulent Transactions Using Classification Algorithms on an Anonymized Credit Card Data Set

Credit card fraudulent transactions are causing businesses and banks to lose time and money. Detecting fraudulent transactions before a transaction is finalized will help businesses and banks to save resources. This research aims to compare the fraud detection accuracy of different sampling techniques and classification algorithms. An efficient method of detecting fraud using machine learning is proposed. Anonymized data set from Kaggle was used for detecting fraudulent transactions. Each transaction has been labeled as either a fraudulent transaction or not. The severe imbalance between fraud and non-fraudulent data caused the algorithms to under-perform. This was addressed with the application of sampling techniques. The combination of undersampling and SMOTE raised the recall accuracy of the classification algorithm. k-NN algorithm showed the highest recall accuracy compared to the other algorithms.

Heuristic systematic model based guidelines for phishing victims

The purpose of this research is to identify factors of phishing victim based on the Heuristic Systematic Model and propose phishing awareness guidelines. In this research, the explanatory sequential mixed method is chosen. Therefore, survey and interview method been applied for data collection purpose. In summary, this research concluded that the major factors that influence user becomes a phishing victim based on the Heuristic Systematic Model are argument quality, source credibility, genre conformity, need for cognition, time pressure, pre-texting, less damage, knowledge and trust. On the other hand, the phishing awareness guidelines are proposed based on previous studies and also feedback from interviewees. Moreover, the proposed phishing awareness guidelines are expected to educate Internet users to identify phishing tricks and prevent phishing attacks in the future.