AIDA researchers presented paper at ISCC 2021 The AIDA project partners presented a paper at the 26th IEEE Symposium on Computers and Communications (ISCC 2021), which took place online, between September 5-8. Moving Target Defense (MTD) appears as a game-changer in the cybersecurity landscape. While the usual defensive mechanisms are reactive, MTD applies proactive techniques to thwart or defend against attacks. Virtual Machine (VM) migration is preferred among other MTD strategies in cloud computing because it is easy to apply and widely available.  The article entitled “VM Migration Scheduling as Moving Target Defense Against Memory DoS Attacks: An Empirical Study” have […]

AIDA, an effective solution to manage risk management in companies and improve corporate performance AIDA is a CMU Collaborative Large Scale project launched in 2020 with the main goal to improve the RAID platform used by Mobileum for integrated risk management in companies. To achieve this objective, the Portuguese ICT Company that is currently the leading provider of Telecom analytics for roaming, security and risk management joined INESC TEC, Universidade de Coimbra and the Computer Science Department at Carnegie Mellon University (CMU) to apply to the  CMU Portugal Call for Large Scale Collaborative Research Projects (LSCRPs).   After a thorough […]

AIDA researchers presented Horus paper at DSN 2021 The AIDA project consortium has published and presented a paper at the 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2021), which took place online, between June 21 and 24. The article entitled “Horus: Non-Intrusive Causal Analysis of Distributed Systems Logs” presents Horus, a system that collects, organizes and enables the refinement of distributed system logs in a causally-consistent and scalable fashion. Horus leverages kernel-level probing to capture events for tracking causality between application-level logs from multiple sources. The events are then encoded as a directed acyclic graph and […]

AIDA researcher gave a keynote talk David Garlan, a member from CMU, gave a keynote talk to JSEET’21 – Joint Track on Software Engineering Education and Training at International Conference on Software Engineering (ICSE).  The talk is entitled “Reflections on the Role of Software Architecture in Software Engineering Education” and took place online, on May 27, 2021. This talks aims to reflect on his experience over the past three decades in attempting to find effective ways to teach “architecture thinking” – specifically considering questions such as: What is worth teaching? Who needs to understand software architecture? How can architectural principles and techniques be […]

The AIDA paper introduces an efficient and secure distributed K-Means algorithm The AIDA project consortium has published a paper at the 19th Symposium on Intelligent Data Analysis (IDA 2021), which took place online, between April 26 and 28. The article is entitled “Efficient Privacy Preserving Distributed K-Means for Non-IID Data” and it introduces an efficient and secure distributed K-Means algorithm, that is robust to non-IID data. The base idea of our proposal consists in each client computing the K-Means algorithm locally, with a variable number of clusters. The server will use the resultant centroids to apply the K-Means algorithm again, discovering […]

AIDA researchers presented a paper at PaPoC Workshop 2021 Researchers from the AIDA project presented a new paper at the 8th Workshop on Principles and Practice of Consistency for Distributed Data, which took place online, on April 26, together with EuroSys 2021. The article is entitled “Totally-Ordered Prefix Parallel Snapshot Isolation” and it provides transactional SQL semantics (i.e., NewSQL) in novel database systems, facilitating the migration of applications. TOPSI is a new algorithm for transaction isolation that avoids waiting for remote updates or using a stale snapshot. This is particularly useful in distributed cloud/edge database systems where wide-area communication or transient […]

The AIDA paper contributes to the trustworthiness of deep learning models The AIDA project consortium has published a paper at the 19th Symposium on Intelligent Data Analysis (IDA 2021), which took place online, between April 26 and 28. The article is entitled “Partially Monotonic Learning for Neural Networks” and it shows that it is possible to encode monotonic relations between variables in complex neural networks without significantly losing model accuracy. For example, when increasing the price of some goods or services, while all other variables remaining equal, real world knowledge indicates that sales will drop (or at least not increase). […]

AIDA researchers presented a paper at ACM SAC 2021 The AIDA project consortium has published a paper at the 2021 ACM/SIGAPP Symposium on Applied Computing (ACM SAC 2021), which took place online, between March 22 and 26. The article is entitled “Analysis of VM Migration Scheduling as Moving Target Defense against insider attacks”; the paper aims to study the security benefit of shuffling the attacker position in the environment through Moving Target Defense based on Virtual Machine migration (VM-MTD). The results show a significant reduction in the attack success probability when applying VM-MTD. It also presents a comparison between different […]

AIDA interview with COMPETE2020 AIDA’s research manager, Carlos Martins (Mobileum), was interviewed by COMPETE 2020 about the mission and objectives of the project. The interview is in Portuguese and available here. 

CMU Team received awards and distinctions Over the past weeks, the partners from the Carnegie Mellon University received scientific awards in the fields related to AIDA. Fredkin Professorship in Artificial Intelligence     Christos Faloutsos, in charge of leading the CMU collaboration with the AIDA project, and professor in the Computer Science Department of CMU, received the Fredkin Professorship in Artificial Intelligence during an online event on Thursday, Oct. 22.  His interests include large-scale data mining with an emphasis on graphs and time sequences, anomaly detection, tensors, and fractals. An Association for Computing Machinery (ACM) fellow and an Amazon Scholar, […]