To read:

Game Economy

Metaverse

Industry 4.0 – Potentials for Predictive Maintenance, 2016
Predictive Maintenance and Intelligent Sensors in Smart Factory: Review
- Good review about physical sensor
- Classification of associated keywords
- Study of three time periods
Selecting Suitable Candidates for Predictive Maintenance
- Identify different points to consider in a PdM scheme
- Discuss about cost, and the cost of the PdM system.
- Technical feasibility in 7 steps:
  1. Data acquisition: what is relevant to capture
  2. Data processing: How to derive meaningful feature where anomalies are identifiable
  3. Detection: Which algorithm to detect anomalies ?
  4. Diagnostic: is the anomaly a true one or is it an issue of the detection system (i.e. bad algo)
  5. Prognostic: Remaining useful life (RUL) ? What is the state
  6. Decision analysis: Recommanded action .
  7. Presentation: How to display the results ?
- Benefit of a PdM
- What will break first ? The engine or the RMS itself ?
- Inventory / Out of stock prediction
- LSTM

Black-box: The attacker has access to the input and the output of an algorithm, and must decode the output.
Grey-box: Additionally, the attacker can analyze external factor such as electricity consumption, time to answer, electromagnetic radiation
White-box: The attacker can see what is happening within the box. Get access to the encryption / decryption software

Three types of attacks:

Triple DES

Four steps to analyse traces.

Attacks:

correlation power analyses (E. Brier, C. Clavier, and F. Olivier. Correlation power analysis with a leakage model. In M. Joye and J.-J. Quisquater, editors, CHES 2004, volume 3156 of LNCS, pages 16–29, Cambridge, Massachusetts, USA, Aug. 11–13, 2004. Springer, Heidelberg, Germany.)
template attack (S. Chari, J. R. Rao, and P. Rohatgi. Template attacks. In B. S. Kaliski Jr., C ̧ etin Kaya. Ko ̧c, and C. Paar, editors, CHES 2002, volume 2523 of LNCS, pages 13–28, Redwood Shores, CA, USA, Aug. 13–15, 2003. Springer, Heidelberg, German)
high order attack (. S. Messerges. Using second-order power analysis to attack DPA resistant soft- ware. In C ̧ etin Kaya. Ko ̧c and C. Paar, editors, CHES 2000, volume 1965 of LNCS, pages 238–251, Worcester, Massachusetts, USA, Aug. 17–18, 2000. Springer, Hei- delberg, Germany)