Journal of Computer Security

This paper addresses the inference problem in on-line analytical processing (OLAP) systems. The inference problem occurs when the exact values of sensitive attributes can be determined through answers to OLAP queries. Most existing inference control methods are computationally expensive for OLAP systems, because they ignore the special structures of OLAP queries. By exploiting such structures, we derive cardinality-based sufficient conditions for safe OLAP data cubes. Specifically, data cubes are safe from inferences if their core cuboids are dense enough, in the sense that the number of known values is under a tight bound. We then apply the sufficient conditions on the basis of a three-tier inference control model. The model introduces an aggregation tier between data and queries. The aggregation tier represents a collection of safe data cubes that are pre-computed over a partition of the data using the proposed sufficient conditions. The aggregation tier is then used to provide users with inference-free queries. Our approach mitigates the performance penalty of inference control, because partitioning the data yields smaller input to inference control algorithms, pre-computing the aggregation tier reduces on-line delay, and using cardinality-based conditions guarantees linear-time complexity.

This paper brings up a new concern regarding efficient re-keying of large groups with dynamic membership: minimizing the overall time it takes for the key server and the group members to process the re-keying message. Specifically, we concentrate on re-keying algorithms based on the Logical Key Hierarchy (LKH), and minimize the longest sequence of encryptions and decryptions that need to be done in a re-keying operation. We first prove a lower bound on the time required to perform a re-keying operation in this model, then we provide an optimal schedule of re-keying messages matching the above lower bound. In particular, we show that the optimal schedule can be found only when the ariety of the LKH key graph is chosen according to the available communication bandwidth and the users processing power. Our results show that key trees of ariety 3, commonly assumed to be optimal, are not optimal when used in high bandwidth networks, or networks of devices with low computational power like sensor networks.

Secret group communication can be achieved by encryption messages with a group key. Dynamic groups face the problem of changing the group key whenever members join or leave. One of the solutions to this problem is to send updated group keys to members via rekey messages in a secure manner. The recovery of lost group keys consequently becomes important because a member cannot decrypt the group data if she loses the rekey messages. Also, any rekey messages lost while a member is logged off cannot be recovered in real-time. Saving recent rekey messages and resending them by the key distribution center not only requires large storage space, but also can cause unnecessary transmission and decryption of keys. Furthermore, the keys in the unsaved rekey messages cannot be recovered. This paper analyzes the problem of rekey message loss and proposes an efficient scheme for recovering group keys based on a logical key hierarchy. The group key generation method used in the scheme makes it possible to recover group keys without transmission and decryption of useless keys.

The rollbackable automated intrusion response mechanism, a method whereby an intrusion response can be treated by in the context of the detection/response life-cycle. The idea derives from the observation that most intrusion responses have negative effects. To decrease the cumulative response cost, response rollback could be carried out at some suitable time, for example when the attack has terminated or the attack ‘detection’ is proved to be a false positive. Additionally, technologies supporting automated response are proposed, such as the structure of a response policy and the way the automated response might be implemented. A proposed implementation structure of rollbackable automated intrusion response system (RAIRS) is also given. With the quantified response cost, the result of our experiments shows that response rollback is promising as a way to decrease the expected cumulative intrusion response cost.

The number of computer attacks has been growing dramatically as the Internet has grown. Attackers currently have little or no disincentive to conducting attacks because they are able to hide their location effectively by creating a chain of connections through a series of hosts. This method is effective because most current host audit systems do not maintain enough information to allow association of incoming and outgoing network connections. In this paper, we introduce an inexpensive method that allows both on-line and forensic matching of incoming and outgoing network traffic. Our method makes small modifications to the operating system that associate origin information with each process in the system process table, and enhances the audit information by logging the origin and destination of network sockets. We present implementation results, show that our method can effectively record origin information about a variety of attacks, and describe the limitations of our approach.

This paper discusses the financial benefit of intrusion detection systems (IDS) deployment techniques and addresses the problems of bridging the gap between technical security solutions and the business need for it. This is an area of interest to both the research and the business community; most IDSes balance host and network monitoring, but the decision about how to adjust usage of each technique tends to be made in a rather ad-hoc way, or based upon effectiveness of detection only without regard to cost of technique. In practice, selections based on how well a strategy helps a company to perform are preferable and methodologies supporting a selection process of this type will assist an Information Technology officer to explain security mechanism selections more effectively to CEOs. In this context, the approach we propose could be applied when choosing one intrusion detection system over another based on which has a better or higher return on investment for the company.

Through a case study, we illustrate the benefits of a better IDS management that leads to a positive Return on Investment (ROI) for IDS deployment. We conceive strategies and approaches to support effective decision-making about which techniques are appropriate for the cost effective management of the IDS in a given environment. It is our intent that this research will serve as a foundation for the formal description of cost structures, analysis, and selection of effective implementation approaches to support the management of IDS deployments.