diff --git a/README.md b/README.md
index 460353825723ceca196e2c8a0b41dc483d87015e..1585d5c924697a357a6ecda812ede80d2749b637 100644
--- a/README.md
+++ b/README.md
@@ -11,17 +11,17 @@ Attacks are simulated in a part of the base data sets as described in the paper.
 The subfolders contain the data sets for different base cases. The emobpy case is split into private ([emobpy_home](emobpy_home/)) and (semi-)public ([emobpy_pub](emobpy_pub/)) cases for easier processing of the (relatively) large data. Re-combining both cases is straight forward, as they still consider the same Electric Vehicles (EVs) and timeframe.
 
 For all published base data sets, we provide normal and attack data sets, which are distinguished by file name:
-<case_name>\_base.gz for normal data and
-<case_name>\_attack\_<attack_id>\_<adv_num>\_<time_sync>.gz for attack data.
-For attack data sets, <attack_id> identifies the attack type, <adv_num> the number of adversary-comprised systems, and <time_sync> the strictness of time synchronization for synchronized attacks during high-stress grid times.
-Regarding <attack_id>: 1,2,4 implement False Data Injection (FDI) attacks (indicating less, more, and increasingly more load respectively) and 3,5,6 implement Manipulation of demand (Mad) attacks (preparation of a demand increasing attack with a prior load reduction, less, and more load respectively).
+`<case_name>_base.gz` for normal data and
+`<case_name>_attack_<attack_id>_<adv_num>_<time_sync>.gz` for attack data.
+For attack data sets, `<attack_id>` identifies the attack type, `<adv_num>` the number of adversary-comprised systems, and `<time_sync>` the strictness of time synchronization for synchronized attacks during high-stress grid times.
+Regarding `<attack_id>`: 1,2,4 implement False Data Injection (FDI) attacks (indicating less, more, and increasingly more load respectively) and 3,5,6 implement Manipulation of demand (Mad) attacks (preparation of a demand increasing attack with a prior load reduction, less, and more load respectively).
 
-All files are gzip-compressed. File contents are JSON-formatted as a list of: {"src":<IPv6.src>,"dst":<IPv6.dst>,"ocpp_payload":<OCPP_Data>}.
-<OCPP_Data> indicates the Open Charge Point Protocol (OCPP) messages, i.e., the data received by a Charge Point Operator (CPO).
+All files are gzip-compressed. File contents are JSON-formatted as a list of: `{"src":<IPv6.src>,"dst":<IPv6.dst>,"ocpp_payload":<OCPP_Data>}`.
+`<OCPP_Data> `indicates the Open Charge Point Protocol (OCPP) messages, i.e., the data received by a Charge Point Operator (CPO).
 Attacks are indicated via (OCPP-compliant) customData elements with a "SimData" vendorId, which should allow for a simple data processing with any standard-compliant OCPP library.
-The "SimData" customData elements include <ev_battery_capacity>\_<actual_energy_consumption>\_<energy_without_attack> values.
-For FDI attacks <actual_energy_consumption> <energy_without_attack> are the same but do not equal the reported consumption, for Mad attacks the values are different but <actual_energy_consumption> is equal to the reported consumption.
+The "SimData" customData elements include `<ev_battery_capacity>_<actual_energy_consumption>_<energy_without_attack>` values.
+For FDI attacks `<actual_energy_consumption>` and `<energy_without_attack>` are the same but do not equal the reported consumption, for Mad attacks the values are different but `<actual_energy_consumption>` is equal to the reported consumption.
 The "SimData" customData elements are intended to only be used in verifying the correctness of the IDS output and not as IDS input.
 
 
-[^fn1]: Z. Lee, T. Li, S. H. Low. ACN-Data: Analysis and Applications of an Open EV Charging Dataset, Proc. the Tenth International Conference on Future Energy Systems (e-Energy '19), June 2019
\ No newline at end of file
+[^fn1]: Z. Lee, T. Li, S. H. Low. ACN-Data: Analysis and Applications of an Open EV Charging Dataset, Proc. the Tenth International Conference on Future Energy Systems (e-Energy '19), June 2019