© 2019 JETIR May 2019, Volume 6, Issue 5 www.jetir.org (ISSN-2349-5162) JETIR1905R02 Journal of Emerging Technologies and Innovative Research (JETIR) www.jetir.org 8 Intrusion Detection System with Deep Learning and Machine Learning Techniques Yawar Rasool Mir Navneet Kaur Sandhu Department of Computer Science & Engineering Department of Computer Science & Engineering Desh Bhagat University Desh Bhagat University Punjab, India Punjab, India Abstract: Contrasted with past, developments in computer and communication technologies have provided extensive and advanced changes. The use of new advances give incredible advantages to people, organizations, and governments, in any case, it causes a few issues against them. For example, the protection of significant data, security of put away information stages, accessibility of learning and so on. Contingent upon these issues, digital fear based oppression is a standout amongst the most significant issues in this world. Cyber fear, which made a ton of issues people and establishments, has achieved a dimension that could undermine open and nation security by different gatherings, for example, criminal associations, proficient people and digital activists. Hence, Intrusion Detection Systems (IDS) have been created to maintain a strategic distance from digital assaults. In this examination, Artificial Neural Network, Random Forest (RF) and Support vector machine (SVM), calculations were utilized to recognize port scan attempts dependent on the new CICIDS2017 dataset and 98.87%, 99.20%, 72.19% precision rates were achieved respectively. IndexTerms — IDS, Cyber Terror, ANN, SVM, RF, CICIDS2017 I. INTRODUCTION Computer crime’s keeps on expanding throughout the years. They are not just limited to unimportant acts, for example, evaluating the login qualifications of a framework yet additionally they are substantially more hazardous. Data security is the way towards shielding data from unapproved get to, utilization, revelation, devastation, alteration or harm. The terms" Information security" "PC security" and "information protection" are regularly used interchangeably. These areas are related to each other and have common goals to provide availability, confidentiality, and integrity of information. Studies show that the first step of an attack is discovery [1]. Reconnaissance is made in order to get information about the system in this stage. Finding a list of open ports in a system provides very critical information for an attacker. For this reason, there are a lot of tools to identify open ports [2] such as antivirus and IDS. In this work, deep learning, RF and SVM machine learning algorithms were applied to create IDS models to identify port scan attempts. The models were exhibited relatively arranged different pieces of the paper as: a literature review was presented an explanation of used material and methods. Experimental results of the classification algorithms and estimations were presented in Section 4. Segment 5 gave end and future works. II. LITERATURE REVIEW: Data security concepts consist of human, period, strategy, information, framework and innovation as is shown in Figure 1. Privacy, integrity, and availability must be give secure system. In the first place, the privacy of the data implies permitting access just to the individual who needs to get to that data. Second, the respectability of the data is guaranteeing that the data is ensured without bending and the first structure is unblemished. At last, the availability of data is the capacity to access and utilize data at the ideal time.