Revisiting Leakage Abuse Attacks

Encrypted search algorithms (ESA) are cryptographic algorithms that support search over encrypted data. ESAs can be designed with various primitives including searchable/structured symmetric encryption (SSE/STE) and oblivious RAM (ORAM). Leakage abuse attacks attempt to recover client queries using knowledge of the client’s data. An important parameter for any leakage-abuse attack is its known-data rate; that is, the fraction of client data that must be known to the adversary. In this work, we revisit leakage abuse attacks in several ways. We first highlight some practical limitations and assumptions underlying the well-known IKK (Islam et al. NDSS ’12) and Count (Cash et al., CCS ’15) attacks. We then design four new leakage-abuse attacks that rely on much weaker assumptions. Three of these attacks are volumetric in the sense that they only exploit leakage related to document sizes. In particular, this means that they work not only on SSE/STE-based ESAs but also against ORAM-based solutions. We also introduce two volumetric injection attack which use adversarial file additions to recover queries even from ORAM-based solutions. As far as we know, these are the first attacks of their kind. We evaluated all our attacks empirically and considered many experimental settings including different data collections, query selectivities, known-data rates, query space size and composition. From our experiments, we observed that the only setting that resulted in reasonable recovery rates under practical assumptions was the case of high-selectivity queries with a leakage profile that includes the response identity pattern (i.e., the identifiers of the matching documents) and the volume pattern (i.e., the size of the matching documents). All other attack scenarios either failed or relied on unrealistic assumptions (e.g., very high known-data rates). For this specific setting, we propose several suggestions and countermeasures including the use of schemes like PBS (Kamara et al, CRYPTO ’18), VLH/AVLH (Kamara and Moataz, Eurocrypt ’19 ), or the use of padding techniques like the ones recently proposed by Bost and Fouque (Bost and Fouque, IACR ePrint 2017/1060)

An Examination of the Individual and Contextual Characteristics Associated with Active Shooter Events

In recent years, the US has experienced a substantial number of mass shooting incidents. This type of shooting incident has been termed “active shooter event” and encompasses shootings that occur in school settings as well as public settings and workplace venues. Much of the recent published literature addressing active shooter events appears to focus on tactical issues, such as training for and responding to this type of incident. Very little research, however, has examined the individual and contextual characteristics associated with active shooter events. In the current study we examine a number of factors related to 88 active shooting events involving 92 perpetrators. Our findings indicate a history of psychological and behavioral issues reported in more than 50% of the active shooters studied. In addition, 60% of shooters had evidence of additional stressors beyond those associated with psychological and behavioral issues. These findings highlight the need to continue to explore potential risk factors associated with this form of violence

Leakage-Abuse Attacks Against Forward and Backward Private Searchable Symmetric Encryption

Dynamic searchable symmetric encryption (DSSE) enables a server to efficiently search and update over encrypted files. To minimize the leakage during updates, a security notion named forward and backward privacy is expected for newly proposed DSSE schemes. Those schemes are generally constructed in a way to break the linkability across search and update queries to a given keyword. However, it remains underexplored whether forward and backward private DSSE is resilient against practical leakage-abuse attacks (LAAs), where an attacker attempts to recover query keywords from the leakage passively collected during queries. In this paper, we aim to be the first to answer this question firmly through two non-trivial efforts. First, we revisit the spectrum of forward and backward private DSSE schemes over the past few years, and unveil some inherent constructional limitations in most schemes. Those limitations allow attackers to exploit query equality and establish a guaranteed linkage among different (refreshed) query tokens surjective to a candidate keyword. Second, we refine volumetric leakage profiles of updates and queries by associating each with a specific operation. By further exploiting update volume and query response volume, we demonstrate that all forward and backward private DSSE schemes can leak the same volumetric information (e.g., insertion volume, deletion volume) as those without such security guarantees. To testify our findings, we realize two generic LAAs, i.e., frequency matching attack and volumetric inference attack, and we evaluate them over various experimental settings in the dynamic context. Finally, we call for new efficient schemes to protect query equality and volumetric information across search and update queries.Comment: A short version of this paper has been accepted to the 30th ACM Conference on Computer and Communications Security (CCS'23

ret2spec: Speculative Execution Using Return Stack Buffers

Speculative execution is an optimization technique that has been part of CPUs for over a decade. It predicts the outcome and target of branch instructions to avoid stalling the execution pipeline. However, until recently, the security implications of speculative code execution have not been studied. In this paper, we investigate a special type of branch predictor that is responsible for predicting return addresses. To the best of our knowledge, we are the first to study return address predictors and their consequences for the security of modern software. In our work, we show how return stack buffers (RSBs), the core unit of return address predictors, can be used to trigger misspeculations. Based on this knowledge, we propose two new attack variants using RSBs that give attackers similar capabilities as the documented Spectre attacks. We show how local attackers can gain arbitrary speculative code execution across processes, e.g., to leak passwords another user enters on a shared system. Our evaluation showed that the recent Spectre countermeasures deployed in operating systems can also cover such RSB-based cross-process attacks. Yet we then demonstrate that attackers can trigger misspeculation in JIT environments in order to leak arbitrary memory content of browser processes. Reading outside the sandboxed memory region with JIT-compiled code is still possible with 80\% accuracy on average.Comment: Updating to the cam-ready version and adding reference to the original pape

Revisiting Shared Data Protection Against Key Exposure

This paper puts a new light on secure data storage inside distributed systems. Specifically, it revisits computational secret sharing in a situation where the encryption key is exposed to an attacker. It comes with several contributions: First, it defines a security model for encryption schemes, where we ask for additional resilience against exposure of the encryption key. Precisely we ask for (1) indistinguishability of plaintexts under full ciphertext knowledge, (2) indistinguishability for an adversary who learns: the encryption key, plus all but one share of the ciphertext. (2) relaxes the "all-or-nothing" property to a more realistic setting, where the ciphertext is transformed into a number of shares, such that the adversary can't access one of them. (1) asks that, unless the user's key is disclosed, noone else than the user can retrieve information about the plaintext. Second, it introduces a new computationally secure encryption-then-sharing scheme, that protects the data in the previously defined attacker model. It consists in data encryption followed by a linear transformation of the ciphertext, then its fragmentation into shares, along with secret sharing of the randomness used for encryption. The computational overhead in addition to data encryption is reduced by half with respect to state of the art. Third, it provides for the first time cryptographic proofs in this context of key exposure. It emphasizes that the security of our scheme relies only on a simple cryptanalysis resilience assumption for blockciphers in public key mode: indistinguishability from random, of the sequence of diferentials of a random value. Fourth, it provides an alternative scheme relying on the more theoretical random permutation model. It consists in encrypting with sponge functions in duplex mode then, as before, secret-sharing the randomness

OnionBots: Subverting Privacy Infrastructure for Cyber Attacks

Over the last decade botnets survived by adopting a sequence of increasingly sophisticated strategies to evade detection and take overs, and to monetize their infrastructure. At the same time, the success of privacy infrastructures such as Tor opened the door to illegal activities, including botnets, ransomware, and a marketplace for drugs and contraband. We contend that the next waves of botnets will extensively subvert privacy infrastructure and cryptographic mechanisms. In this work we propose to preemptively investigate the design and mitigation of such botnets. We first, introduce OnionBots, what we believe will be the next generation of resilient, stealthy botnets. OnionBots use privacy infrastructures for cyber attacks by completely decoupling their operation from the infected host IP address and by carrying traffic that does not leak information about its source, destination, and nature. Such bots live symbiotically within the privacy infrastructures to evade detection, measurement, scale estimation, observation, and in general all IP-based current mitigation techniques. Furthermore, we show that with an adequate self-healing network maintenance scheme, that is simple to implement, OnionBots achieve a low diameter and a low degree and are robust to partitioning under node deletions. We developed a mitigation technique, called SOAP, that neutralizes the nodes of the basic OnionBots. We also outline and discuss a set of techniques that can enable subsequent waves of Super OnionBots. In light of the potential of such botnets, we believe that the research community should proactively develop detection and mitigation methods to thwart OnionBots, potentially making adjustments to privacy infrastructure.Comment: 12 pages, 8 figure