Calculating costs for quality of security service

Spyropoulou, E.; Levin, Timothy E.; Irvine, Cynthia E.

doi:10.1109/acsac.2000.898888

Cited by 21 publications

(7 citation statements)

References 11 publications

(15 reference statements)

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“…Although the concept has existed more than a decade, it is not clearly known yet how to measure the quality of general security service. Spyropoulou et al [17] have proposed the notion of QoSS (Quality of Security Service). Ideally, a system administrator and a security officer can select an appropriate security scheme to optimize the cost-benefit relation, when a quantitative model showing the computational cost and benefit of a security service is given.…”

Section: Related Workmentioning

confidence: 99%

Towards security and QoS optimization in real-time embedded systems

Kang

Son

2006

SIGBED Rev.

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A number of real-time embedded systems (RTESs) are used to manage critical infrastructure such as electric grids or C 4 I systems. In these systems, it is essential to meet deadlines, for example, to avoid a power outage or loss of a life. The importance of security support is also increasing, because more RTESs are being networked. To securely transmit sensitive data, e.g., a battle field status, across the network, RTESs need to protect the data via cryptographic techniques. However, security support may cause deadline misses or unacceptable QoS degradation. As an initial effort to address this problem, we formulate the security support in RTESs as a QoS optimization problem. Also, we propose a novel adaptive approach for security support in which a RTES initially uses a relatively short cryptographic key to maximize the QoS, while increasing the key length when the security risk level is raised. In this way, we can make a possible cryptanalysis several orders of magnitude harder by requiring the attacker to search a larger key space, while meeting all deadlines by degrading the QoS in a controlled manner. To minimize the overhead, we derive the appropriate QoS levels for several key lengths via an offline polynomial time algorithm. When the risk level is raised online, a real-time task can use a longer key and adapt to the corresponding QoS level (derived offline) in O(1) time.

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Section: Related Workmentioning

confidence: 99%

Towards security and QoS optimization in real-time embedded systems

Kang

Son

2006

SIGBED Rev.

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“…Generally, the quality of security service can only be measured qualitatively unlike real-time performance. Spyropoulou et al [20] have proposed the notion of QoSS (Quality of Security Service). Ideally, a system administrator and a security officer can select an appropriate security scheme to optimize the cost-benefit relation, when a quantitative model showing the computational cost and benefit of a security service is given.…”

Section: Related Workmentioning

confidence: 99%

Systematic Security and Timeliness Tradeoffs in Real-Time Embedded Systems

Kang

Son

2006

12th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA'06)

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“…This approach for quantifying the costs related to a task's security requests (Spyropoulou, Levin, Irvine, 2000) refers to costs relative to every security service invoked by the task. Each service may access CPU time, memory, bandwidth, disk space, etc.…”

Section: Costingmentioning

confidence: 99%

“…One approach (described in detail in Spyropoulou, Agar, Levin, Irvine, 2002) is to use a trust management system (Blaze, Feigenbaum, Ioannidis, Keromytis, 1999) and an external dynamic parameter console to modulate the detailed IPsec security attributes. The dynamic parameter console interacts with the external environment, such as an administrator or an intrusion detection system, to receive the current selections for the network mode and security level, and to pass the selections to the trust management system.…”

Section: Examination Of Resource Modulationmentioning

confidence: 99%