Charles Pak’s research while affiliated with Nova Southeastern University and other places

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Publications (3)


Risk forecast using hidden Markov models
  • Article

July 2010

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33 Reads

ACM SIGITE Newsletter

Charles Pak

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Today's fast moving technologies create innovative ideas, products, and services, but they also bring with them new security risks. The gap between new technologies and the security needed to keep them from opening up new risks in information systems (ISs) can be difficult to close completely. Changes in ISs are inevitable because computing environments, intentionally or unintentionally, are always changing. These changes bring with them vulnerabilities on new or existing ISs, which cause security states to move between mitigated, vulnerable, and compromised states. In previous work, we introduced the near real-time risk assessment using hidden Markov models (HMMs). This paper applies that theory to a prototype MatLab™ environment.


Asset priority risk assessment using hidden Markov models

October 2009

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39 Reads

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15 Citations

Conducting risk assessment on organizational assets can be time consuming, burdensome, and misleading in many cases because of the dynamically changing security states of assets. Risk assessments may present inaccurate or false data if the organizational assets change in their security postures. Each asset can change its security status from secure, mitigated, vulnerable, or compromised states. The secure state is only temporary and imaginary; it may never exist. Therefore, it is accurate to say that each asset changes its security state within its mitigated, vulnerable, or compromised, state. If we can predict each asset's security state prior to its actual state, we would have a good risk indicator for the organization's mission-critical assets. In this paper, we explore possible security states from the insider's perspective, as there are more security incidents initiated from inside than outside an organization. However, we are in a continuous loop of mitigating dynamically changing assets caused by both internal and external threats.


The near real time statistical asset priority driven (NRTSAPD) risk assessment methodology

October 2008

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20 Reads

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4 Citations

The NRTSAPD Risk Assessment methodology offers two key advantages over other risk assessments. The first advantage is that the NRTSAPD risk assessment methodology provides management with a simple, quick, and easy to use risk assessment methodology based on an organizational mission critical asset priority. The second advantage of using this NRTSAPD risk assessment is to integrate several organizational databases such as network helpdesk, asset management, Intrusion Detection System (IDS), Intrusion Prevention System (IPS), firewall and incident response report databases with the management's decision on the mission critical asset priorities. Having the most current asset management with the integrated security incident response databases, the management asset priority driven risk assessment would be answered in a near real time or as current as the asset management inventory; which can sometimes be scanned in real time. Consequently, it produces a realistic Information Systems (IS) production environment risk assessment report in a near real time manner.

Citations (2)


... Hidden Markov Model(HMM) [22], a statistical model, in which the system being modeled is assumed to be a Markov process with unobserved (hidden) states. The Markov process is the random process which fit for the Markov assumption, where Markov assumption is that the probability of one state S t depends only on the previous state S t−1 in a random process, denoted as P (S t |S 1 , S 2 , ..., S t−1 ) = P (S t |S t−1 ). ...

Reference:

An improved network security situation assessment approach in software defined networks
Asset priority risk assessment using hidden Markov models
  • Citing Conference Paper
  • October 2009

... Online risk assessment is very important in terms of minimizing the performance cost incurred. In the dynamic model, we can dynamically evaluate attack cost by propagating the impact of confidentiality, integrity and availability through dependencies model or attack graph [6][7][8][9][10][11][12]. (2) Offline: in Information security management system we use offline risk assessment. ...

The near real time statistical asset priority driven (NRTSAPD) risk assessment methodology
  • Citing Conference Paper
  • October 2008