Cloud computing supports multitenancy to satisfy the users’demands for accessing resources and simultaneously it increases revenue for cloud providers.Cloud providers adapt multitenancy by virtualizing the resources,...Cloud computing supports multitenancy to satisfy the users’demands for accessing resources and simultaneously it increases revenue for cloud providers.Cloud providers adapt multitenancy by virtualizing the resources,like CPU,network interfaces,peripherals,hard drives and memory using hypervisor to fulfill the demand.In a virtualized environment,many virtual machines(VMs)can run on the same core with the help of the hypervisor by sharing the resources.The VMs running on the same core are the target for the malicious or abnormal attacks like side channel attacks.Among various side channel attacks in cloud computing,cache-based side channel attack is one that leaks private information of the users based on the shared resources.Here,as the shared resource is the cache,a process can utilize the cache usage of another by cache contention.Cache sharing provides a way for the attackers to gain considerable information so that the key used for encryption can be inferred.Discovering this side channel attack is a challenging task.This requires identification of a feature that influences the attack.Even though there are various techniques available in the literature to mitigate such attacks,an effective solution to reduce the cache-based side channel attack is still an issue.Therefore,a novel fuzzy rule-based mechanism is integrated to detect the cache side channel attackers by monitoring the cache data access(CDA).The factor that determines the attack is CDA in a log file created by the framework during authorization.The proposed framework also utilizes certain security properties including ECC and hashing for the privacy preservation and the decision is made with the aid of a fuzzy logic system.展开更多
Speculative execution attacks can leak arbitrary program data under malicious speculation,presenting a severe security threat.Based on two key observations,this paper presents a software-transparent defense mechanism ...Speculative execution attacks can leak arbitrary program data under malicious speculation,presenting a severe security threat.Based on two key observations,this paper presents a software-transparent defense mechanism called speculative secret flow tracking(SSFT),which is capable of defending against all cache-based speculative execution attacks with a low performance overhead.First,we observe that the attacker must use array or pointer variables in the victim code to access arbitrary memory data.Therefore,we propose a strict definition of secret data to reduce the amount of data to be protected.Second,if the load is not data-dependent and control-dependent on secrets,its speculative execution will not leak any secrets.Thus,this paper introduces the concept of speculative secret flow to analyze how secret data are obtained and propagated during speculative execution.By tracking speculative secret flow in hardware,SSFT can identify all unsafe speculative loads(USLs)that are dependent on secrets.Moreover,SSFT exploits three different methods to constrain USLs’speculative execution and prevent them from leaking secrets into the cache and translation lookaside buffer(TLB)states.This paper evaluates the performance of SSFT on the SPEC CPU 2006 workloads,and the results show that SSFT is effective and its performance overhead is very low.To defend against all speculative execution attack variants,SSFT only incurs an average slowdown of 4.5%(Delay USL-L1Miss)or 3.8%(Invisible USLs)compared to a non-secure processor.Our analysis also shows that SSFT maintains a low hardware overhead.展开更多
文摘Cloud computing supports multitenancy to satisfy the users’demands for accessing resources and simultaneously it increases revenue for cloud providers.Cloud providers adapt multitenancy by virtualizing the resources,like CPU,network interfaces,peripherals,hard drives and memory using hypervisor to fulfill the demand.In a virtualized environment,many virtual machines(VMs)can run on the same core with the help of the hypervisor by sharing the resources.The VMs running on the same core are the target for the malicious or abnormal attacks like side channel attacks.Among various side channel attacks in cloud computing,cache-based side channel attack is one that leaks private information of the users based on the shared resources.Here,as the shared resource is the cache,a process can utilize the cache usage of another by cache contention.Cache sharing provides a way for the attackers to gain considerable information so that the key used for encryption can be inferred.Discovering this side channel attack is a challenging task.This requires identification of a feature that influences the attack.Even though there are various techniques available in the literature to mitigate such attacks,an effective solution to reduce the cache-based side channel attack is still an issue.Therefore,a novel fuzzy rule-based mechanism is integrated to detect the cache side channel attackers by monitoring the cache data access(CDA).The factor that determines the attack is CDA in a log file created by the framework during authorization.The proposed framework also utilizes certain security properties including ECC and hashing for the privacy preservation and the decision is made with the aid of a fuzzy logic system.
基金supported by the Key-Area Research and Development Program of Guangdong Province of China under Grant No.2018B010115002.
文摘Speculative execution attacks can leak arbitrary program data under malicious speculation,presenting a severe security threat.Based on two key observations,this paper presents a software-transparent defense mechanism called speculative secret flow tracking(SSFT),which is capable of defending against all cache-based speculative execution attacks with a low performance overhead.First,we observe that the attacker must use array or pointer variables in the victim code to access arbitrary memory data.Therefore,we propose a strict definition of secret data to reduce the amount of data to be protected.Second,if the load is not data-dependent and control-dependent on secrets,its speculative execution will not leak any secrets.Thus,this paper introduces the concept of speculative secret flow to analyze how secret data are obtained and propagated during speculative execution.By tracking speculative secret flow in hardware,SSFT can identify all unsafe speculative loads(USLs)that are dependent on secrets.Moreover,SSFT exploits three different methods to constrain USLs’speculative execution and prevent them from leaking secrets into the cache and translation lookaside buffer(TLB)states.This paper evaluates the performance of SSFT on the SPEC CPU 2006 workloads,and the results show that SSFT is effective and its performance overhead is very low.To defend against all speculative execution attack variants,SSFT only incurs an average slowdown of 4.5%(Delay USL-L1Miss)or 3.8%(Invisible USLs)compared to a non-secure processor.Our analysis also shows that SSFT maintains a low hardware overhead.
