Efficient Synthesis of Sensor Deception Attacks Using Observation Equivalence-Based Abstraction

This paper investigates the synthesis of successful sensor deception attack functions in supervisory control using abstraction methods to reduce computational complexity. In sensor deception attacks, an attacker hijacks a subset of the sensors of the plant and feeds incorrect information to the supervisor with the intent on causing damage to the supervised system. The attacker is successful if its attack causes damage to the system and it is not identified by an intrusion detection module. The existence test and the synthesis method of successful sensor deception attack functions are computationally expensive, specifically in partially observed systems. For this reason, we leverage results on abstraction methods to reduce the computational effort in solving these problems. Namely, we introduce an equivalence relation called restricted observation equivalence, that is used to abstract the original system before calculating attack functions. Based on this equivalence relation we prove that the existence of successful attack functions in the abstracted supervised system guarantees the existence of successful attack functions in the unabstracted supervised system and vice versa. Moreover, successful attack functions synthesized from the abstracted system can be exactly mapped to successful attack functions on the unabstracted system, thereby providing a complete solution to the attack synthesis problem

Supervisory Control for Behavior Composition

We relate behavior composition, a synthesis task studied in AI, to supervisory control theory from the discrete event systems field. In particular, we show that realizing (i.e., implementing) a target behavior module (e.g., a house surveillance system) by suitably coordinating a collection of available behaviors (e.g., automatic blinds, doors, lights, cameras, etc.) amounts to imposing a supervisor onto a special discrete event system. Such a link allows us to leverage on the solid foundations and extensive work on discrete event systems, including borrowing tools and ideas from that field. As evidence of that we show how simple it is to introduce preferences in the mapped framework

Critical assessment issues in work-integrated learning

Assessment has long been a contentious issue in work-integrated learning (WIL) and cooperative education. Despite assessment being central to the integrity and accountability of a university and long-standing theories around best practice in assessment, enacting quality assessment practices has proven to be more difficult. Authors in this special issue on assessment highlight the need for balanced assessment approaches that reflect the highly variable experiences students encounter, and the need to keep validity and reliability paramount when constructing assessment structures. Increasingly quality and standards policies driven by more regulatory university environments are impacting on the design of assessment profiles. The value of workplace supervisors’ feedback in WIL contexts is discussed and the challenges of measuring the nuances of unpredictable, context-dependent WIL outcomes are explored. The benefits of ePorftolios are advocated and the use of these platforms as assessment tools that enable a creative way for students to provide evidence of employability capabilities highlighted