This paper presents research from the field of cybersecurity, addressing the problem of data transmission over DNS-based covert channels in restricted network environments. The study investigates the impact of request timing on the performance of such tunnels, with a focus on identifying the relationship between throughput, latency, and polling strategies. Existing tools such as dnstt, TUNS, and iodine, were evaluated and compared through benchmarks using synthetic data. The results indicate that performance can be significantly improved by employing a dynamically adjusting mechanism that adapts the timing between requests based on real-time server-side feedback. This approach achieves better jitter and latency metrics, particularly in bidirectional and high-throughput scenarios. While the current solution uses a static adjustment strategy, the findings indicate that this mechanism is well-suited for further integration with intelligent systems capable of traffic pattern recognition and adaptive control. These insights direct the future research towards the development of adaptive and intelligent DNS tunneling systems that can optimize performance in real-world network conditions.

We analyze in this paper the design architecture of a web-based personalized query suggestion system usable in information retrieval contexts. Our system comes in the form of a transparent proxy for the Google search engine (although it can work with other search engines too, with minimal code changes) that is able to personalize the list of query suggestions provided by Google, based on the recent user web browsing history. The most important design choices are presented with a special focus on the integration with the Google search engine. The integration analysis is directed by the well known application integration criteria. We have made our system transparent to the user when searching information on Google and we have shown through performance tests that our system has very small computational costs for the user experience.

International audience

We introduce in this paper a bandwidth aggregation routing solution for multihoming sites. Our routing solution interconnects two distinct multihomed network sites (i.e. network sites that have two or more uplinks to the Internet) and routes local flows between these two network sites. It routes local flows dynamically through several outgoing network paths/links depending on the load (i.e. congestion level) on each path. If a network path/uplink becomes more congested, fewer local flows are routed through it. We detail two path load estimation strategies: one based on RTT measurements and the other based on throughput measurements, both implying passive network measurements. Our multihoming solution outperforms the ECMP-based (i.e. Equal-Cost Multipath) solution in terms of total aggregated throughput and inter-flow fairness.

Powerlists are recursive data structures that together with their associated algebraic theories could offer both a methodology to design parallel algorithms and parallel programming abstractions to ease the development of parallel applications This has been also proved by a concrete development of such a framework that allows easy, efficient, and reliable implementation of Java parallel programs on shared memory systems. The paper presents a highly scalable version of this framework by extending it to distributed memory systems based on an MPI implementation. Through this extension we may use the framework to develop Java parallel programs also on distributed memory systems such as clusters. The design of the framework enables flexibility in defining the appropriate execution type depending on the execution system and its characteristics. Therefore, it is possible to choose MPI execution (that also could be combined with multithreading) if the available system includes an MPI platform, or simple multithreading execution. Examples are given and performance experiments are conducted. The performance analysis of these applications emphasises the utility and the efficiency of this framework extension.

Parallel programs based on the Divide&Conquer paradigm could be successfully defined in a simple way using powerlists. These parallel recursive data structures and their algebraic theories offer both a methodology to design parallel algorithms and parallel programming abstractions to ease the development of parallel applications. The paper presents how programs based on powerlists can be implemented in Java using the JPLF framework we developed. The design of this framework is based on powerlists theory, but in the same time follows the object-oriented design principles that provide flexibility and maintainability. Examples are given and performance experiments are conducted. The results emphasize the utility and the efficiency of the framework.