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Full-Text Articles in Computer Engineering

Comparative Study Of Deep Learning Models For Network Intrusion Detection, Brian Lee, Sandhya Amaresh, Clifford Green, Daniel Engels Apr 2018

Comparative Study Of Deep Learning Models For Network Intrusion Detection, Brian Lee, Sandhya Amaresh, Clifford Green, Daniel Engels

SMU Data Science Review

In this paper, we present a comparative evaluation of deep learning approaches to network intrusion detection. A Network Intrusion Detection System (NIDS) is a critical component of every Internet connected system due to likely attacks from both external and internal sources. A NIDS is used to detect network born attacks such as Denial of Service (DoS) attacks, malware replication, and intruders that are operating within the system. Multiple deep learning approaches have been proposed for intrusion detection systems. We evaluate three models, a vanilla deep neural net (DNN), self-taught learning (STL) approach, and Recurrent Neural Network (RNN) based Long Short ...


A Framework For Categorization Of Industrial Control System Cyber Training Environments, Evan G. Plumley Mar 2017

A Framework For Categorization Of Industrial Control System Cyber Training Environments, Evan G. Plumley

Theses and Dissertations

First responders and professionals in hazardous occupations undergo training and evaluations for the purpose of mitigating risk and damage. For example, helicopter pilots train with multiple categorized simulations that increase in complexity before flying a real aircraft. However in the industrial control cyber incident response domain, where incident response professionals help detect, respond and recover from cyber incidents, no official categorization of training environments exist. To address this gap, this thesis provides a categorization of industrial control training environments based on realism. Four levels of environments are proposed and mapped to Blooms Taxonomy. This categorization will help organizations determine which ...


Data Security And Privacy In Smart Grid, Yue Tong Aug 2015

Data Security And Privacy In Smart Grid, Yue Tong

Doctoral Dissertations

This dissertation explores novel data security and privacy problems in the emerging smart grid.

The need for data security and privacy spans the whole life cycle of the data in the smart grid, across the phases of data acquisition, local processing and archiving, collaborative processing, and finally sharing and archiving. The first two phases happen in the private domains of an individual utility company, where data are collected from the power system and processed at the local facilities. When data are being acquired and processed in the private domain, data security is the most critical concern. The key question is ...


Understanding The Methods Behind Cyber Terrorism, Maurice E. Dawson Jr., Marwan Omar, Jonathan Abramson Dec 2014

Understanding The Methods Behind Cyber Terrorism, Maurice E. Dawson Jr., Marwan Omar, Jonathan Abramson

Maurice Dawson

Cyber security has become a matter of national, international, economic, and societal importance that affects multiple nations (Walker, 2012). Since the 1990s users have exploited vulnerabilities to gain access to networks for malicious purposes. In recent years the number of attacks on U.S. networks has continued to grow at an exponential rate. This includes malicious embedded code, exploitation of backdoors, and more. These attacks can be initiated from anywhere in the world from behind a computer with a masked Internet Protocol (IP) address. This type of warfare, cyber warfare, changes the landscape of war itself (Beidleman, 2009). This type ...


The Future Of National And International Security On The Internet, Maurice Dawson, Marwan Omar, Jonathan Abramson, Dustin Bessette Dec 2013

The Future Of National And International Security On The Internet, Maurice Dawson, Marwan Omar, Jonathan Abramson, Dustin Bessette

Maurice Dawson

Hyperconnectivity is a growing trend that is driving cyber security experts to develop new security architectures for multiple platforms such as mobile devices, laptops, and even wearable displays. The futures of national and international security rely on complex countermeasures to ensure that a proper security posture is maintained during this state of hyperconnectivity. To protect these systems from exploitation of vulnerabilities it is essential to understand current and future threats to include the laws that drive their need to be secured. Examined within this chapter are the potential security-related threats with the use of social media, mobile devices, virtual worlds ...


Research In Progress-Defending Android Smartphones From Malware Attacks, Marwan Omar, Maurice E. Dawson Jr. Dec 2012

Research In Progress-Defending Android Smartphones From Malware Attacks, Marwan Omar, Maurice E. Dawson Jr.

Maurice Dawson

Smart phones are becoming enriched with confidential information due to their powerful computational capabilities and attractive communications features. The Android smart phone is one of the most widely used platforms by businesses and users alike. This is partially because Android smart phones use the free, open-source Linux as the underlying operating system, which allows development of applications by any software developer. This research study aims to explore security risks associated with the use of Android smart phones and the sensitive information they contain, the researcher devised a survey questionnaire to investigate and further understand security threats targeting Android smart phones ...


Cyber Profiling For Insider Threat Detection, Akaninyene Walter Udoeyop Aug 2010

Cyber Profiling For Insider Threat Detection, Akaninyene Walter Udoeyop

Masters Theses

Cyber attacks against companies and organizations can result in high impact losses that include damaged credibility, exposed vulnerability, and financial losses. Until the 21st century, insiders were often overlooked as suspects for these attacks. The 2010 CERT Cyber Security Watch Survey attributes 26 percent of cyber crimes to insiders. Numerous real insider attack scenarios suggest that during, or directly before the attack, the insider begins to behave abnormally. We introduce a method to detect abnormal behavior by profiling users. We utilize the k-means and kernel density estimation algorithms to learn a user’s normal behavior and establish normal user profiles ...