Artificial intelligence in the cyber domain: Offense and defense

Artificial intelligence techniques have grown rapidly in recent years, and their applications in practice can be seen in many fields, ranging from facial recognition to image analysis. In the cybersecurity domain, AI-based techniques can provide better cyber defense tools and help adversaries improve methods of attack. However, malicious actors are aware of the new prospects too and will probably attempt to use them for nefarious purposes. This survey paper aims at providing an overview of how artificial intelligence can be used in the context of cybersecurity in both offense and defense.Web of Science123art. no. 41

Encapsulation of Soft Computing Approaches within Itemset Mining a A Survey

Data Mining discovers patterns and trends by extracting knowledge from large databases. Soft Computing techniques such as fuzzy logic, neural networks, genetic algorithms, rough sets, etc. aims to reveal the tolerance for imprecision and uncertainty for achieving tractability, robustness and low-cost solutions. Fuzzy Logic and Rough sets are suitable for handling different types of uncertainty. Neural networks provide good learning and generalization. Genetic algorithms provide efficient search algorithms for selecting a model, from mixed media data. Data mining refers to information extraction while soft computing is used for information processing. For effective knowledge discovery from large databases, both Soft Computing and Data Mining can be merged. Association rule mining (ARM) and Itemset mining focus on finding most frequent item sets and corresponding association rules, extracting rare itemsets including temporal and fuzzy concepts in discovered patterns. This survey paper explores the usage of soft computing approaches in itemset utility mining

A Survey on Attacks and Advances of Intrusion Detection Systems

Now day’s information of an organization floating over the internet that increases the traffic on the network as well as threats from attackers. To protect these sensitive material Intrusion Detection System (IDS) is situated in the scheme. It is an application software program or hardware mechanism that compacts with assaults by assembling information from a mixture of systems and network resources, then analyzing indications of defense dilemmas. Network Intrusion Detection (NID) is a method that efforts to determine unauthorized entrance to a network through analyzing traffic on the network. There are a variety of advances of intrusion detection, for instance Data Mining, Pattern Matching, Machine Learning and Measure Based Methods. This survey paper aims towards the proper learning of intrusion detection system with the intention that researchers could create employ of it and discover the new methods towards intrusions. Keywords: Intrusion Detection System, Data Mining, Pattern Matching, Anomaly detection, misuse detection, Machine Learning