Dec'21
The IUP Journal of Information Technology
Focus
A malware is a malicious software that gets activated when the user clicks a link or opens an attachment. A Denial of Service (DoS) attack or a Distributed Denial of Service (DDoS) attack disrupts a service and makes it unavailable for legitimate users by flooding false service requests. A phishing attack uses fraudulent messages pretending to be sent by a trusted person or organization. It steals sensitive data like credit card information and login passwords. In a man-in-the-middle attack, the attacker intercepts the communication channel between the user's client computer and the server computer system to steal sensitive information or selectively modify the messages constituting the communication.
There has been a huge increase in cyber security threats during the Covid-19 pandemic. According to the McAfee Enterprises' survey report, "Cybercrime in a Pandemic World: The Impact of Covid-19", around 81% of the organizations worldwide experienced cyber threats in the pandemic period. During this global health emergency, employees were allowed to work from home, and it triggered a massive increase in cyber criminal activities. Since people work from home using their own computers and network devices that may lack the necessary security protections, which leads to security risks and cyber attacks.
Appropriate cyber security measures need to be in place to protect sensitive data from attacks and make the online systems safe. These measures should prevent security risks resulting from malware, user-related weakness like weak passwords, software vulnerabilities and subvert systems. The security measures can be technical and nontechnical that include organizational policies, regulations and practices. Protecting individuals and businesses from cyber attacks is a continuing effort since there is no end to the menace. Thus cyber security practices will continue to evolve as the Internet applications and cyber attacks change from time to time.
The paper, "Detection of Phishing Activities Using Optimized Neurofuzzy System", by Agwi Uche Celestine, Imhanlahimi R E and Bernard Olorunfemi Paul, proposes a dynamic system for identifying and predicting phishing websites and activities using machine learning approach. The system makes use of adaptive neuro-fuzzy inference system and particle swarm optimization techniques and provides encouraging results.
The next paper, "Structural Coexistence of Organization's Line of Control and Line of Transformation to Sustain Rapid Culture Change in Digital Age: A Review", by Satish Talikota, presents a review of the control aspects and the transformational aspects of an organization. The author concludes that the organization needs to focus on balancing the two aspects so that it can derive competitive advantage.
Consulting Editor
Detection of Phishing Activities Using Optimized Neurofuzzy System
Phishing is common with websites pertaining to scholarships, grants, recruitment, auction and online payment platforms. The attackers create fake websites that replicate the legitimate ones by cloning or by editing the html codes of the target legitimate websites. When victius seek resources available on these websites they are possibly redirected to the phishing websites to obtain their sensitive information either for financial benefits or to completely disrupt and halt the information processing system. To tackle such problems, an optimized adaptive machine learning system for detection and classification of phishing websites using feature-based phishing detection approach was implemented. A combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Particle Swarm Optimization (PSO) algorithms coined as PSO-ANFIS technique was used. The PSO searches the massive online dataset and real-time network packets to extract features and identify optimal solution (feature selection) for training ANFIS, while Case Base Reasoning (CBR) approach was used to match new instances against instances in the knowledge base. The PSO-ANFIS model was tested using real-time network packet features and dataset available in University of California, Irvine (UCI) data repository. Performance was measured using Root Mean Square Error (RMSE), Precision, Recall and Accuracy and compared with Artificial Neural Network (ANN) and ANFIS. The result from PSO-ANFIS showed significant improvements in prediction capabilities compared to ANN and ANFIS without optimization algorithm. This shows that optimized machine learning such as PSO-ANFIS can address problems of bias, features selection and curse of dimensionality facing existing ML techniques.
Structural Coexistence of Organization's Line of Control and Line of Transformation to Sustain Rapid Culture Change in Digital Age: A Review
The paper shows the importance of insourcing of human resource, learning and development in the organization through a contextual review of the articles on internal efficiency (control) and external effectiveness (transformation) to coexist in the form of Line of Control (LOC) and Line of Transformation (LOT), respectively. The focus is towards the protection of intellectual property of the organization. About five relevant applied papers for 10 LOC and 10 LOT topics were chosen which align with the theme of control and transformation. The findings show that the 10 proven LOC concepts which were considered as organizational transformation essentials until recently, are however, more internal control concepts today. On the other hand, the 10 LOT concepts have emerged as disruptive concepts for organizations to take note, embed in organizational structure and coexist with LOC. The findings recommend organizations to strike a balance between LOC and LOT in the areas such as organizational resource, knowledge, skills and attitude.