Jessie Walker

A layer based architecture for provenance in big data

Big data is a new technology wave that makes the world awash in data. Various organizations accumulate data that are difficult to exploit. Government databases, social media, healthcare databases etc. are the examples of that big data. Big data covers absorbing and analyzing huge amount of data that may have originated or processed outside of the organization. Data provenance can be defined as origin and process of data. It carries significant information of a system. It can be useful for debugging, auditing, measuring performance and trust in data. Data provenance in big data is relatively unexplored topic. It is necessary to appropriately track the creation and collection process of the data to provide context and reproducibility. This poster tries to address the challenges of capturing provenance data. Additionally, we propose an intuitive layer based architecture of provenance in big data that can handle the challenges.

Cyber security for emergency management

Cyber security continues to be an increasingly important topic when considering Homeland Security issues. This area however is often overlooked during a disaster or emergency situation. Emergency management within the US as it currently stands lacks any real cyber situational awareness with respect to the core activities of emergency management such as mitigation, preparedness, response and recovery. As a result critical cyberinfrastructure resources that emergency management personnel rely on is left on the sideline when planning, handling, and recovering from emergencies or natural disasters. As emergency management evolves within the US to handle dynamic man-made, and natural disasters such as terrorist attacks, hurricanes, and floods, these issues must be addressed to mitigate risks. This paper takes the first step in examining the issue of cyber situational awareness within emergency management and identifies several concerns for the emergency management community.

Visualization, modeling and predictive analysis of cyber security attacks against cyber infrastructure-oriented systems

Cyber security threats require rapid identification of imminent or potential attacks to support deterrence and protection. Thomas Friedman theorized that technology has leveled or “flattened” the global playing field that once existed. This flattening has happened as a result of what he calls the “triple convergence” of platform, process and people. However, there is a general lack of understanding about how to describe, assess the complex and dynamic nature of cyber security related information to improve overall cyber security task performance. Ever since the first computer virus traversed the Internet it has been apparent that attacks can spread rapidly across national boundaries. This paper presents research that utilize bioinformatics techniques, to forecast cyber security attacks by identifying emerging threats based on analysis of computer infection, and incursions models based on human disease models.

Cloud forensics challenges from a service model standpoint: IaaS, PaaS and SaaS

Cloud computing is a promising and expanding technology which could replace traditional IT systems. Cloud computing resembles a giant pool of resources which contains hardware, software and related applications, which can be accessed through web-based services on a pay-per-usage model. The main features of the cloud model are accessibility, availability and scalability, and it can be subdivided into three service models: Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). Cloud computing continues to transform how security challenges are addressed in closed and private networks. Given the advanced functionality offered by cloud computing, network monitoring and digital forensics efforts are potentially detectable and service-interruptive, which significantly impacts the effectiveness and thoroughness of digital forensic methods. This paper presents a general view of cloud computing, which aims to highlight the security issues and vulnerabilities associated with cloud service models. The technology is mainly based on virtualization, where data is always volatile and typically stored in a de-centralized architecture located across various countries and regions. This presents forensics investigators with legal challenges, due to the nature of multi-tenancy and distributed shared resources. This paper examines the three cloud service models and discusses the security challenges and issues involved with each service model along with potential solutions for each.

Scenario-based design for a cloud forensics portal

Cloud computing continues to transform how we address security challenges in closed and private networks. Given the advanced functionality offered by cloud computing, network monitoring and digital forensics efforts are potentially detectable and service interruptive which affects the effectiveness and thoroughness of digital forensic methods. Virtualization, the cost-effective delivery platform for clouds and data centers, provides an opportunity for Virtual Machine Introspection (VMI) through the hypervisor. VMI would be an environment to monitor the activity of a Virtual Machine (VM). In this paper, we propose a multi-phase scenario-based design concept within an open source virtualized environment to collect data to validate the hypervisors ability to provide a portal for threat monitoring that is effective, undetectable, and non-interruptive.

Plan recognition in intrusion detection systems using logic programming

In this paper we focus on logic programming based approach to plan recognition in intrusion detection systems. The goal of an intruder is to attack a computer or a network system for malicious reasons and the goal of the intrusion detection system is to detect the actions of the intruder and warn the network administrator of an impending attack. We show how an intrusion detection system can recognize the plans of the intruder by modeling the domain as a logic program and then reducing the plan recognition problem to computing models of the logic program. This methodology has been used widely for several planning problems and fits very naturally for plan recognition problems. We give an example scenario and show how to model it. Our results are quite satisfactory and we believe that our approach can lead to a generalized solution to plan recognition.

Open source cloud management platforms and hypervisor technologies: A review and comparison

Cloud computing continues to redefine the way in which organizations utilize information technology by providing increased flexibility, reduced cost of ownership and maintenance, massive scalability, and on-demand/pay-as-you-go services. Virtual and cloud technology replaces traditional IT products with services that can be purchased as-needed without the overhead of dedicated IT resources and staff. Public and private clouds are deployed using many different software platforms such as Eucalyptus, Xen, OpenStack, CloudStack and Amazon Web Services. This paper compares many popular cloud deployment platforms and related hypervisor technologies for implementing effective cloud-based computing services.

Historically black colleges and university libraries’ utilization of Twitter for patron engagement: an exploratory study

African American millennials form the largest demographic of Twitter users. Historically Black College and University (HBCU) libraries have incorporated the micro-blogging service Twitter into their information services as a strategy to market and inform library users. However, there is little in the literature on assessment; do we know if users are interacting with libraries via social media? This study examined followers of HBCU libraries, and measures their engagement with library-generated content on Twitter. This study utilizes social analytics techniques, specifically propagation and sentiment analysis to measure the state of engagement among library Twitter followers, within a one-year period. Dispute an active presence on Twitter; libraries in this investigation had a relativity small footprint in the Twitter universe. Results indicate little engagement with followers and neutral emotional responses to library-generated tweets.

Cyber Security Concerns for Ubiquitous/Pervasive Computing Environments

The computing paradigm of ubiquitous/pervasive computing has changed the way in which nomadic computer users interact with computer devices and network systems. Modern ubiquitous computing devices have enabled nomadic computer users to interact with computer and network systems anywhere and at anytime. Although the issue of cyber security has been overlooked by many within the community, these devices provide users with a rich set of context-relevant information including location, usage data, and even the location/state of similar devices within the reach. Cyber Security has become a matter of national, economic, and societal importance. Present-day attacks on the nations computer systems do not simply damage an isolated machine or disrupt a single enterprise system. Instead, modern attacks target infrastructure that is integral to the economy, and daily life. Computer networks have joined food, water, transportation, and energy as critical resources for the functioning of the national economy. As a result of our interconnected world no device is an island, and security still remains a significant obstacle for ubiquitous and pervasive environments, partially in terms intrusions. This paper examines intrusion detection within ubiquitous and pervasive environments within the context of plan recognition as means to classify attacks both quantitatively and qualitatively.