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Security, Robustness, and Trust in Artificial Intelligence and Distributed Architectures
3 April - 7 April
Security, Robustness, and Trust in Artificial Intelligence and Distributed Architectures will focus on novel AI technologies and enabling capabilities for distributed operations. This conference is looking for your innovative ideas and projects to showcase as the next profound advancement in the Artificial Intelligence & Distributed Architectures domain. Some examples of these include: autonomous systems and autonomy enablers, blockchain inspired architectures and distributed leger technologies, software defined networking, advanced hardware architectures, quantum information sciences, and more!
Blockchain technologies, distributed ledger systems, and other decentralized applications (DAPPs) have applicability across m any domains. Building on the foundational concepts of smart contracts, game theoretics, and cryptography; these technologies offer unprecedented capability to democratize distributed systems, ensure proof of trust and verifiability of message traffic across numerous information eco- systems. This conference seeks novel applications of these technologies to both the government and commercial sectors.
Advances in autonomous systems over the next five years will be significant across a global community. Creative solutions which cover the full spectrum of autonomy will be considered; from human augmentation and human guided learning to fully autonomous system design which is functionally independent from human interference. Assured communications between these systems is essential and capabilities which enable natural language software agents will be transformative enablers as we see these technologies transition into operational environments.
Distributed platforms and the operation frameworks that integrate these capabilities together will unify military, intelligence based, and law enforcement operations. We encourage submission of work on unifying data integration and fusion concepts which will significantly improve the efficiency of computing platforms in both distributed or resource constrained environments.
Edge computing brings computation and data storage closer to the location where it is needed to improve speed of response. These capabilities will also be essential components of a successful distributed architecture. However, today’s systems are limited by both processing power and energy demands. Advanced computing architectures like neuromorphic computing, ternary, and quantum computing will enable processing speeds exponentially faster than traditional systems of today. With the growing number of sensing capabilities and explosive growth of data collection tools, rapid software execution will allow us to shift through more data than ever thought possible. In addition to the hardware architectures, software based advanced analytics are of high interest as transformative necessities in future years.
Softwarization is key to new innovations in networking, computing and storage technologies. It will lead to the realization of Software Defined Everything (SDx) which will replace the hard-coded static intelligence from hardware and network systems with software based programmable and hardware agnostic intelligent control plane agents. These technologies are rapidly being adopted in the industry and government enabling new control functions, abstractions and decision-making algorithms specific to networks, storage and computational environments. SDx makes it easy for integration of additional emerging hardware architectures, like quantum computers and heterogeneous Internet of Things (IOT) ecosystems.
This conference also seeks to cover the implications of these technologies on computer security. For example, the increased computation speeds of quantum architectures will vastly improve the ability to break encryption schemes making today’s legacy systems vulnerable and insecure. Counter Artificial Intelligence and Adversarial Machine Learning techniques are evolving. These are techniques employed in the field of machine learning which attempt to fool models through malicious input or by exploiting model failure points. This technique can be applied for a variety of reasons, the most common being to attack or cause a malfunction in standard machine learning models. Data poisoning strategies expose insecurities in our machine learning algorithms and allow adversarial machine learning strategies to create distrust in the much needed autonomous capabilities of the future. Submissions which explore trusted AI architectures will be welcomed.
Finally, there will be a growing need for advanced security schemes, sensors, data storage, and resilient systems which have inherent security mechanisms as communications between these sensors and sensing systems becomes faster and more complex. This complexity will result in the realized growth of novel advancements in technologies like cryptographically secured distributed cloud architectures which subvert an adversary or ill-intended user from targeting a single source vulnerability.
This conference is the place where we will look to the future to discover the technologies that will be game changers when considering the next generation of distributed architectures.