Data Manipulation Attack and Its Operating Techniques

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INTRODUCTION

Data manipulation attack is a type of cyberattack in which an attacker either changes or removes information with the intention of bringing a service down, spreading false information, or performing malicious activity. These types of attacks do not concern the confidentiality or the availability of the data but the integrity of the information, which can have an adverse effect on organizations that rely on precise information such as banks or infrastructures

These attacks do not utilize physical means to bring down a target but instead seek to overthrow it from within through very innovative and complex means. Data manipulation attacks, unlike denial of service (DoS) attacks, which aim at simply making a system unoperational, are more lethal. Analysis of the threat confirms this as these kinds of attacks are normally very tricky to do and thus develop caution as one does not trigger the alarm system either manually or invisibly. This makes these attacks very fatal especially in cases where accurate information is frequently required.

In the context of a blockchain, data manipulation is even more worrisome because this is a decentralized system. A person who modifies the goal transaction’s details or some transactions’ records would make the system unattractive to the users. Knowing the operation techniques of these attacks assists in preventing or reducing their effects.

• MAN-IN-THE-MIDDLE (MITM) MANIPULATION:

A data manipulation attack carried out through a man-in-the-middle (MITM) attack is one of the easiest to carry. The attacker here acts as a proxy and captures the message sent by one of the parties, modifies it, and sends it to the other concerned party without the knowledge of any of the parties that the message has been changed.

The manipulation using MITM can have shocking repercussions especially in monetary transactions or the executions of smart contracts and decentralized applications. The aggressor can change the loan amounts or the terms of the contracts before sending such data to the targeted user, leading to abuse or erroneous execution of contracts.

To avert TAC based manipulation, strong encryption solutions must be put in place such as end-to-end encryption and ensuring that both parties in the exchange have the means to check the validity of the validity of information before any actions are taken on such information.

• TIME-OF-CHECK TO TIME-OF-USE (TOCTOU) EXPLOITATION:

In TOCTOU attacks, the adversary seeks for a window of opportunity between a system's data being checked (time of check) and the time of the same data being operated on (time of use). It is during this opportunity that the attacker alters the data in a manner that the system employs the corrupt data unnoticed.

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This class of attack can be especially lethal in the case of blockchain smart contracts. A smart contract is executed when the data has been validated, however a hacker knows this, and due to the time lapse between validation & execution of the smart contract, the hacker sneaks in and alters data and as a result the contract gets executed when it should not, hence loss of money or fraudulent transactions.

To avert the TOCTOU attacks, one should strive to reduce the ‘time interval’ between the data being verified and put into use, there is use of atomicity where possible and there are comprehensive controls towards the integrity of data at several points.

• FALSE DATA INJECTION (FDI):

Data Fabrication, which can also be referred to as false data injection, can also be referred to as data manipulation attack where in the attacker inserts imaginary data or wrong data on a system. Such form of manipulation becomes a security threat to systems such as the ones used for power grid systems or even financial trading systems due to reliance on live data.

Within the frameworks of blockchain networks, the injection of false data does not restrict to the addition of transactions only but also includes alteration of the existing ones. Such acts could either mislead the network users or result in a split of the blockchain, taking for example injecting wrong entries in the networks. Other examples are use of unrealistic price injected in a DeFi platform causing the users to make wrong trades resulting in loss.

For the organization to be able to avoid FDI attacks in the first place, it would be necessary to introduce such mechanisms for validation of the precise data, such as triangulation with several data sources, and/or use of centralized or decentralized systems of oracles which carry the least risk of manipulative data injection.

• DATA REPLAY ATTACK:

In a data replay attack, the attacker captures valid data transmitted in a network and replays it at a later time in order to deceive the system into taking actions based on wrong or outdated data. Such situations are awful since they can lead to unauthorized transactions or even a system collapse.

In blockchain networks, replay attacks can make users approve the same transactions more that once without their knowledge which would make it possible for double spending or execution of contracts that are not intended. Such attacks can be costly to users and businesses operating within the networks.

As for the measures against replay attacks, they include the use of transaction IDs and time stamps which prevent the system from accepting repeated transactions of the same data. The described countermeasures can minimize the losses affecting either cash flow or business activities as a result of such replay attacks.

CONCLUSION

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The act of data manipulation abuse is a devastating threat looming all over all digital systems particularly in the instances where accurate data is required for the business to function. Awareness of the different techniques that can be deployed such as ‘man in the middle’ manipulation, ‘time of check to time of use’ exploitation, data falsification, and replaying attacks helps organizations in coming up with better protection schemes. Defending against these kinds of assaults involves a multifaceted approach that includes encryption, data validation, and real time surveillance to make sure that the data stays correct and untainted during its life cycle.