Threat of Covert Channel Attacks


  • Attackers can build various side channels to circumvent the logical isolation in cloud physical machines, and obtain sensitive information from co-resident VMs
    • Coarse-grained, e.g., workloads and web traffic rates
      • Since the cache utilization rate has a large impact on the execution time of the cache read operation, attackers can infer the victim’s cache usage and workload information, by applying the Prime+Probe technique. 
      • Similarly, they can estimate the victim’s web traffic rate, which also has a strong correlation with the execution time of cache operations. [2]
      • [1] demonstrate a clear correlation between a victim’s web traffic rate with the load sample. 
    • Fine-grained, e.g., cryptographic keys
      • Attackers can exploit shared hardware resources, such as the instruction cache, to extract cryptographic keys. Specifically, the following challenges are overcomed
        • Dealing with core migrations and determining if an observation is associated with the victim
        • Filtering out hardware and software noise, and regaining access to the target CPU core with sufficient frequency
  • For clever attackers, even seemingly innocuous information like workload statistics can be useful.
    • For example, such data can be used to identify when the system is most vulnerable, i.e., the time to launch further attacks, such as Denial of Service attacks. [9]
[2] Using Virtual Machine Allocation Policies to Defend against Co-resident Attacks in Cloud Computing, by Yi Han et al, in Transactions on Dependable and Secure Computing

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