# Using Blockchain for Data Collection in the Automotive Industry Sector: A Literature Review
## 3 Results
### Security Attacks  
Vehicles and other automotive products are packed with sensors, computer systems, network entities, and other electromechanical devices. Examples of such systems are found in References [28; 29; 30]. This may constitute a security breach with respect to the data collection by these systems. One of these systems is the black box. Various possible attacks on the black box, which is placed by the insurance company in the vehicle, can be made, such as signal sniffing, encrypting the data before sending them. In addition, malicious attacks can be avoided by using the fingerprint as a hash code [11]. However, those attacks are not all the possible security attacks that can lead to low security in the vehicle systems. In Reference [11], the authors did not consider other types of attacks involving data collection in a black box, meaning that their solution is not optimal from a security perspective. In addition, the authors of Reference [15] used a lightweight blockchain in their investigation of the black box, without taking into account the possible attacks it may receive, except that the memory that can be attacked, making it a worse option for data collection from a cyber-security perspective. On the other hand, in the case of Reference [16], active attacks on the vehicle or driver on data integrity are considered, and the system is safe against chosen-ciphertext attacks, as well as against k-collision attack algorithm (KCAA). However, the system must be protected against collusion [17]. Some reviewed articles take the solution from a cyber-attack scenario. For example, Reference [4] laid the foundation in this context: if data are not collected securely, accidents may occur to drivers and passengers. Another example is the linking attack, which is avoided by blockchain data encryption. When the attacker wants to perform an attack on the cloud software, the vehicle collects the data and identifies another hash that quickly detects the infiltrator. In addition, the distribution of fake software updates is considered by requiring the primary key from the real provider [4]. However, one of the key attacks is the Distributed Denial of Service (DDoS) attack; based on a key pair in a key list, the attacker transactions would not generate correspondence in the key list. As a result, it would drop without affecting the target node [4]. Reference [18] also studied this attack;the authors offered a broader view of data attacks, providing a comprehensive view on which the automotive industry can rely for its services. In addition, the solution of Reference [10] proposed a system for common attacks, such as Man-in-the-Middle (MITM) and DDoS, but without specifying the solution. However, the article has a full list of attacks and their requirements, such as injection, broken authentication, data exposure, using components with known vulnerabilities, or parameter attacks, among others [10]. This is a very comprehensive set that allows the automotive sector to spot a variety of threats. Cyber-attacks on connected cars are also a concern, as they can compromise physical security. The authors of Reference [13] were aware of this and described a blockchain approach based on security for data collection; it focused on the possibility of the driver, vehicle, driving, and traffic data being attacked by the previously mentioned attack methods. However, a specific applicable solution was recommended by the authors for future work. The solution proposed by Reference [9] did not offer any vision of security beyond that settled by the blockchain itself. However, data-collection solutions must consider offering the users a valuable verification method to collect data between cars. An example is the carpooling service solution that was proposed by Reference [19]. It seems, however, that data-sharing security is poorly studied [14], and it is included often as a future direction of research.