A look ahead approach to secure multi-party protocols

Secure multi-party protocols have been proposed to enable non-colluding parties to cooperate without a trusted server. Even though such protocols prevent information disclosure other than the objective function, they are quite costly in computation and communication. Therefore, the high overhead makes it necessary for parties to estimate the utility that can be achieved as a result of the protocol beforehand. In this paper, we propose a look ahead approach, specifically for secure multi-party protocols to achieve distributed k-anonymity, which helps parties to decide if the utility benefit from the protocol is within an acceptable range before initiating the protocol. Look ahead operation is highly localized and its accuracy depends on the amount of information the parties are willing to share. Experimental results show the effectiveness of the proposed methods

Sharing Computer Network Logs for Security and Privacy: A Motivation for New Methodologies of Anonymization

Logs are one of the most fundamental resources to any security professional. It is widely recognized by the government and industry that it is both beneficial and desirable to share logs for the purpose of security research. However, the sharing is not happening or not to the degree or magnitude that is desired. Organizations are reluctant to share logs because of the risk of exposing sensitive information to potential attackers. We believe this reluctance remains high because current anonymization techniques are weak and one-size-fits-all--or better put, one size tries to fit all. We must develop standards and make anonymization available at varying levels, striking a balance between privacy and utility. Organizations have different needs and trust other organizations to different degrees. They must be able to map multiple anonymization levels with defined risks to the trust levels they share with (would-be) receivers. It is not until there are industry standards for multiple levels of anonymization that we will be able to move forward and achieve the goal of widespread sharing of logs for security researchers.Comment: 17 pages, 1 figur

Assessing Data Usefulness for Failure Analysis in Anonymized System Logs

System logs are a valuable source of information for the analysis and understanding of systems behavior for the purpose of improving their performance. Such logs contain various types of information, including sensitive information. Information deemed sensitive can either directly be extracted from system log entries by correlation of several log entries, or can be inferred from the combination of the (non-sensitive) information contained within system logs with other logs and/or additional datasets. The analysis of system logs containing sensitive information compromises data privacy. Therefore, various anonymization techniques, such as generalization and suppression have been employed, over the years, by data and computing centers to protect the privacy of their users, their data, and the system as a whole. Privacy-preserving data resulting from anonymization via generalization and suppression may lead to significantly decreased data usefulness, thus, hindering the intended analysis for understanding the system behavior. Maintaining a balance between data usefulness and privacy preservation, therefore, remains an open and important challenge. Irreversible encoding of system logs using collision-resistant hashing algorithms, such as SHAKE-128, is a novel approach previously introduced by the authors to mitigate data privacy concerns. The present work describes a study of the applicability of the encoding approach from earlier work on the system logs of a production high performance computing system. Moreover, a metric is introduced to assess the data usefulness of the anonymized system logs to detect and identify the failures encountered in the system.Comment: 11 pages, 3 figures, submitted to 17th IEEE International Symposium on Parallel and Distributed Computin

Techniques for the dynamic randomization of network attributes

Critical infrastructure control systems continue to foster predictable communication paths and static configurations that allow easy access to our networked critical infrastructure around the world. This makes them attractive and easy targets for cyber-attack. We have developed technologies that address these attack vectors by automatically reconfiguring network settings. Applying these protective measures will convert control systems into «moving targets» that proactively defend themselves against attack. This «Moving Target Defense» (MTD) revolves about the movement of network reconfiguration, securely communicating reconfiguration specifications to other network nodes as required, and ensuring that connectivity between nodes is uninterrupted. Software-defined Networking (SDN) is leveraged to meet many of these goals. Our MTD approach eliminates adversaries targeting known static attributes of network devices and systems, and consists of the following three techniques: (1) Network Randomization for TCP/UDP Ports; (2) Network Randomization for IP Addresses; (3) Network Randomization for Network Paths In this paper, we describe the implementation of the aforementioned technologies. We also discuss the individual and collective successes for the techniques, challenges for deployment, constraints and assumptions, and the performance implications for each technique