Sami Azam

An acquisition method for the MLR of auditory evoked potentials

The study is focused on the recording of the auditory evoked potential to stimuli that result in binaural (two-ear) interaction. The auditory evoked potential is derived from small bioelectric potentials recorded from the scalp. The AEP is categorized on the basis of the latency of the response following the auditory stimulus. For example, the auditory brainstem response (ABR) occurs in the first 20 ms after the stimulus, the middle latency response (MLR) from 20 to 70 ms, and the slow vertex response (SVR) up to 500 ms after stimulation. The study of auditory evoked potentials may provide insight in the mechanism of auditory processing in the brain. The study presents a methodology to measure AEP related to binaural hearing.

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.

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.

A New Approach Correlating Binaural Hearing and the Brain’s Response

Normal binaural hearing allows the auditory system to determine the direction and distance of sound sources and to detect certain sounds at much lower intensity levels. Different stimuli may have different impact on binaural processing and may generate different brain responses. The mechanism by which this occurs is poorly understood. Time averaged EEG responses of normal hearing subjects to repeated stimuli were analyzed. The stimuli, 500 Hz Blackman windowed pure tones, were presented as homophasic or anti-phasic and were also mixed with various noise conditions. Auditory evoked potentials (AEP) were obtained by averaging 500 trials of in-phase and 500 trials of outphase of each EEG epoch. The results show that the amplitude of the dominant frequency component in the 20 50 Hz range of the middle latency response of the AEP was larger for the anti-phasic condition than for the homo-phasic condition. The normalised amplitude differences were larger when the stimuli were embedded in noise resulting in a higher mean value of the normalized amplitude difference than for noise free stimuli. These results are likely to relate to binaural masking level difference which finds that the detection of a signal in a background noise is easier when the signal has a different inter-aural phase difference than the noise.

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.

Cost effective analysis of web based transmission

This paper examines the techniques for passing information from one web site to another, the methodologies that have been developed and the advances in technology that has occurred in relation to these techniques. This paper then utilises one of these technologies to develop an environment where the major techniques (Polling and Push) can be tested. This papers research finds that Polling uses substantially more resources than Push, particularly in regard to server usage. In situations where this is an issue the use of Push can reduce server cost by at least a factor of 5 and possibly more in a real world application. The reduction in network cost is more difficult to determine using the tools in this paper but here the indications are that the reduction in cost may be by a factor of 3. Finally this paper presents the view that the techniques are complementary and both should be used within most real world application.

Effect of stimulus phase reversal on the 20–35 Hz frequency component of the AEP

Auditory evoked potentials (AEP) have been recorded to investigate the effect of phase reversal of the stimulus presentation. Acquisition of the Middle Latency Response (MLR) for both homophasic and antiphasic cases was obtained by epoch averaging 500 trials of in-phase and 500 trials of out-phase EEG. An epoch was defined as the EEG data between 20 ms to 100 ms after the presentation of stimuli. The MLR was segmented by a trigger signal synchronized to the onset of the stimuli. The homophasic stimulus was a 1000 Hz Blackman windowed pure tone with a duration of 18 ms followed by 200 ms silence. The antiphasic stimulus was identical except for the phase of the stimulus. The stimuli were presented as blocks of 10 antiphasic tones followed by 10 homophasic tones for a total of 1000 tones. The comparison of the MLR responses upon presentation of homophasic and antiphasic stimuli showed there is electrophysiological evidence of binaural processing in the 20–35 Hz dominant frequency component.