# Reputation-Based Trust Approaches in Named Data Networking
## 3 Reputation-Based Approaches in NDN
### Reputation-Based Systems  
When a cache poisoning attack is detected, the compromised router should discard the forged content from its Content Store. NDN inherently supports no other way to flush content from router caches than cache replacement policies, for example LRU. However, those policies rely solely on eventual natural cache aging and are not useful for distinguishing valid and poisonous content. The authors of Reference [22] propose a reputation-based technique which is based on explicit exclusion filters to decrease the detected poisonous content in the caches. In particular, Interest packets include an optional field which is called \"Exclude\". This field contains information about name components that must not occur in the name of the returned content. The main concept of the proposed mechanism is that consumers, as they typically verify signatures, can detect invalid content and issue a new Interest to exclude certain content by referring to its hash (i.e., by exploiting the Exclude field). Routers rank the cached content based on the exclusion information provided by consumers, assigning a higher rank to valid content than to fake ones. The rank of a content object is based on the exclusion rate, the time freshness of the exclusions and the total number of interfaces which excluded this content and indicates how trusted the content is. Although this algorithm achieves efficient mitigation of cache poisoning and delivery of valid content to consumers, it is still susceptible to these attacks. On the one hand, malicious end-users can target a valid content object and collaborate to exclude it from caches. On the other hand, a group of malicious consumers can explicitly request fake content and not exclude it. Therefore, poisonous content will be prioritized by routers and is likely to serve subsequent interests, propagating into the network. Another drawback of this method is that every content object, either valid or fake, will be cached, increasing memory cost. The aforementioned vulnerabilities are considered important by Reference [32], whereby a different approach exploits excluding information, as well. The proposed reputation-based method assigns not only a trust value to each content object, but also a credibility value to each content provider. A user's credibility is computed based on the trust value of the content that was provided by the user. When a consumer issues an Interest excluding fake content, the content's trust value will be decreased, impacting the credibility of the sender, as well. Even though credibility values will be significantly decreased in case a poisonous content is detected, they will recover slowly by sending valid content. This technique aims at preventing on-off attacks, whereby adversaries send alternatively valid and invalid data to maintain a certain credibility value. The calculated trust values and the credibility values are used by routers as criteria to perform selective caching and Interest acceptance. More particularly, a router caches received content with a probability which is equal to its trust value. In addition, routers accept the incoming Interests with a probability which is equal to the credibility value of the consumer who sent the Interest. Authors argue that associating the probability that a consumer's Interests are satisfied with their credibility value, incentivize users to provide valid content. Nonetheless, it is important to note here that the exclusion functionality exploited by the above-described mechanisms is no longer available in NDN since version 0.3, rendering the previous methods infeasible. Cache poisoning attack mitigation is examined from a different angle in Router-Oriented Mitigation (ROM) [33]. ROM is based on the idea that content-oriented mitigation methods might be inadequate if the router itself tampers content passing through. In ROM, every router assigns a reputation value to each of its adjacent routers.