Demo Data from EDBT 2026 / reviewers in the wild / expert
MohammadAmin Lotfolahi
dblp:215/8297
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0002-3276-8992ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Authentication and access control · 44% Cryptographic primitives and cryptanalysis · 44% Cyber-physical and IoT security · 13% | |
| Computer networks
1 paper |
Vehicular, aerial and satellite networks · 50% Internet of things and sensor networks · 50% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks › iot security
batch authentication |
0.5 | 1 | 2021 | Messages Classification and Dynamic Batch Verification Scheme for VANETs · IEEE Trans. Mob. Comput. 2021 |
Vehicular, aerial and satellite networks
vehicular ad hoc networks |
0.5 | 1 | 2021 | Messages Classification and Dynamic Batch Verification Scheme for VANETs · IEEE Trans. Mob. Comput. 2021 |
Cryptographic primitives and cryptanalysis › public-key cryptography › digital signatures
batch verification |
0.5 | 1 | 2021 | Messages Classification and Dynamic Batch Verification Scheme for VANETs · IEEE Trans. Mob. Comput. 2021 |
Authentication and access control › authentication
message authentication |
0.5 | 1 | 2021 | Messages Classification and Dynamic Batch Verification Scheme for VANETs · IEEE Trans. Mob. Comput. 2021 |
Cyber-physical and IoT security
vehicular network security |
0.1 | 1 | 2021 | Messages Classification and Dynamic Batch Verification Scheme for VANETs · IEEE Trans. Mob. Comput. 2021 |
Methods — techniques the papers use, named apart from their topics
dynamic batch sizing · 1.0divide-and-conquer · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Messages Classification and Dynamic Batch Verification Scheme for VANETsabstractUnder a high-density traffic environment in a vehicular ad hoc network (VANET), many safety messages will not be verified in time and then get dropped. To touch such an issue appropriately, we aim at improving the efficiency of message verification and the number of verified safety messages. In our proposed scheme, messages are properly classified and prioritized first so that more important basic safety messages can be verified earlier. To improve batch verification, a dynamic batch verification scheme with an adjustable batch size is designed accordingly. The batch size is halved when failures of batch verification occur consecutively over a certain threshold to improve the efficiency of batch verification. On the contrary, the batch size is doubled when successes of batch verification occur consecutively over a certain threshold to increase the messages in a batch to be verified. For a failure of batch verification, a divide-and-conquer approach is utilized to find the illegitimate message(s). Via analysis, the superiority of our design over some closely related schemes in terms of verification delay and number of verified basic safety messages etc. is successfully demonstrated. By simulation, performance of our design and some closely related schemes is further investigated in realistic scenarios. Huei-Wen Ferng, Jia-Ying Chen, MohammadAmin Lotfolahi, Ying-Tsu Tseng |
IEEE Trans. Mob. Comput. | 3 |