Computer Science - Conference Items
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- ItemReducing the cost of machine learning differential attacks using bit selection and a partial ML-distinguisher(Springer, 2023-04-01) Ebrahimi, Amirhossein; Regazzoni, Francesco; Palmieri, Paolo; Science Foundation IrelandIn a differential cryptanalysis attack, the attacker tries to observe a block cipher’s behavior under an input difference: if the system’s resulting output differences show any non-random behavior, a differential distinguisher is obtained. While differential cryptanlysis has been known for several decades, Gohr was the first to propose in 2019 the use of machine learning (ML) to build a distinguisher. In this paper, we present the first Partial Differential (PD) ML distinguisher, and demonstrate its effectiveness on cipher SPECK32/64. As a PD-ML-distinguisher is based on a selection of bits rather than all bits in a block, we also study if different selections of bits have different impact in the accuracy of the distinguisher, and we find that to be the case. More importantly, we also establish that certain bits have reliably higher effectiveness than others, through a series of independent experiments on different datasets, and we propose an algorithm for assigning an effectiveness score to each bit in the block. By selecting the highest scoring bits, we are able to train a partial ML-distinguisher over 8-bits that is almost as accurate as an equivalent ML-distinguisher over the entire 32 bits (68.8% against 72%), for six rounds of SPECK32/64. Furthermore, we demonstrate that our obtained machine can reduce the time complexity of the key-averaging algorithm for training a 7-round distinguisher by a factor of 25 at a cost of only 3% in the resulting machine’s accuracy. These results may therefore open the way to the application of (partial) ML-based distinguishers to ciphers whose block size has so far been considered too large.
- ItemA programmable Ethernet transport Packetponder using common compact form factor pluggable tunable transceivers to support novel DWDM architectures(Optica Publishing Group, 2023) Raulin, Julie; Davey, Gawen; Verbishchuk, Yuliya; Jeffries, Alexander; Sreenan, Cormac J.; Garcia Gunning, Fatima C.; Science Foundation IrelandWe introduce a packetponder comprising a programmable packet switch with P4 ASIC containing a mixture of “grey” and tunable DWDM pluggable transceivers that, combined with ROADMs, introduces novel possibilities for Ethernet transport architectures.
- ItemKnowns and unknowns: An experience report on discovering tacit knowledge of maritime surveyors(Springer Nature Switzerland AG, 2023-04-04) Sporsem, Tor; Hatling, Morten; Tkalich, Anastasiia; Stol, Klaas-Jan; Ferrari, Alessio; Penzenstadler, Birgit; Det Norske Veritas; Norges ForskningsrådContext: Requirements elicitation is an essential activity to ensure that systems provide the necessary functionality to users, and that they are fit for purpose. In addition to traditional ‘reductionist’ techniques, the use of observations and ethnography-style techniques have been proposed to identify requirements. Research Problem: One frequently heard issue with observational techniques is that they are costly to use, as developers who would partake, would lose considerable development time. Observation also does not guarantee that all essential requirements are identified, and so luck plays a role. Very few experience reports exist to evaluate observational techniques in practice, and for organizations it is difficult to assess whether observation is a worthwhile activity, given its associated cost. Results: This report presents experiences from DNV, a global leader providing maritime services who are renewing an information system to support its expert users. We draw on several data sources, covering insights from both developers and users. The data were collected through 9 interviews with users and developers, and over 80 h of observation of prospective users in the maritime domain. We capture ‘knowns’ and ‘unknowns’ from both developers and users, and highlight the importance of observational studies. Contribution: While observational techniques are costly to use, we conclude that essential information is uncovered, which is key for developers to understand system users and their concerns.
- ItemA programmable Ethernet transport Packetponder using common compact form factor pluggable tunable transceivers to support novel DWDM architectures(IEEE, 2023-03-07) Raulin, Julie; Davey, Gawen; Verbishchuk, Yulia; Sreenan, Cormac J.; Gunning, Fatima C. Gunnning; Science Foundation IrelandWe introduce a packetponder comprising a programmable packet switch with P4 ASIC containing a mixture of “grey” and tunable DWDM pluggable transceivers that, combined with ROADMs, introduces novel possibilities for Ethernet transport architectures.
- ItemDelay analysis of TSN based industrial networks with preemptive traffic using network calculus(Institute of Electrical and Electronics Engineers (IEEE), 2023-06) Seliem, Mohamed; Zahran, Ahmed; Pesch, Dirk; Science Foundation IrelandTime-Sensitive Networking (TSN) extends traditional Ethernet to support data traffic with ultra-reliability and time-critical requirements for a range of applications in industrial automation, automotive, and aerospace. The TSN standards present guidelines to integrate different types of data traffic over a single converged network. Therefore, it is becoming an enabling technology towards the Industry 4.0 vision of integrating information and operational technologies within future Industrial Internet of Things networks. In this paper, we develop a network calculus based framework to analyse TSN based industrial networks supporting a range of data traffic classes. We apply the framework to study and analyse a well-known industrial use case, Quality Checks After Production (QCAP), with four data traffic types with different requirements in terms of reliability and end-to-end latency. In our evaluation, we validate our framework with a computer simulation model and compare the tightness of the calculated delay bounds to a state-of-the-art approach. We then use our model to analyse the upper bounds on the worst-case delay of the different QCAP traffic types and assess the factors that impact end-to-end delay, e.g. flow offset and critical links. Finally, we compare various credit accumulation rates and their impact on the traffic delay bounds.