Reduce Information Security and HR risks created by inappropriate staff behaviour on collaboration platforms

COVID-19加速了现有的“在家工作”和“随时随地工作”的趋势。协作平台的采用在一定程度上缓解了这种转变，但同时也使组织面临信息安全、人力资源和合规性方面的新威胁，这些威胁基于员工的行为，工作人员和承包商。很少有工具可以用来解决这种增加的“人员风险”，这种风险延伸到欺诈或种族和性骚扰，性别偏见或其他违反政策的行为。协作平台上的大量动态和未经审核的内容意味着，如果没有合适的工具，向WFH和WFA的转变会给许多组织带来“定时炸弹”。** IT数据风险 ** 在受控的办公室环境之外，员工更有可能丢失、意外泄露数据、知识产权或打开安全漏洞，并最终造成无法弥补的损害。例如，可能会在Slack中交换凭据，在公共渠道中共享机密信息等。虽然软件和硬件解决方案可以保护“静态”或“动态”数据，由于员工“在任何地方工作”，并与“任何人”接触，因此，自愿或意外泄漏的人为风险大开。**使用案例：内部威胁 * 信息安全盗窃和数据泄露 * 知识产权泄露 * 交换敏感或PI数据 * 安全漏洞 ** 人力资源风险 ** 在办公室中识别的行为模式可能未被发现，并隐藏骚扰、欺诈、心理健康和其他人力资源问题。随着COVID，从过渡到在办公室外工作，不同群体的个人反应不同，有些人患有心理健康问题，或者只是每天远离远程工作而挣扎这也将解决远程虚拟环境中的多样性、平等和包容等核心问题。**使用案例：不受欢迎的行为 * 骚扰，歧视，欺凌 * 对平等，包容和多样性的影响-性别歧视和种族主义仇恨言论的识别，与MeToo和Black Lives Matter运动有关。技术可以让员工在对话中拥有平等的地位。*不受欢迎的行为和有毒语言，有意或无意（非语言暗示）* 遵守行业法规（例如，反贿赂、串通等）*趋势分析反映虚拟工作场所的士气和文化变化 ** 创新 ** 尽管存在保护组织的解决方案，但它们仅限于基本的关键字匹配或消息级别规则，通常逐个消息操作“边缘”，并且不考虑支撑更广泛问题的行为模式。因此，骚扰的特征，在办公室中被同事发现的欺凌或其他行为在协作平台上将不会被注意到。以类似的方式，活动的异常模式将无法与公司机密事件、新产品发布、IP泄露。拟议的解决方案侧重于通过Slack和MS Teams等协作平台分析行为，以主动检测异常行为、偏离基线和趋势。它基于经过训练的人工智能模型，以识别行为模式和文本分析，旨在识别PI、实体、情绪、毒性、情感等。

COVID-19 has accelerated existing trends to both 'work from home' and 'work anywhere'.The adoption of collaboration platforms has eased the shift to a certain extent, but simultaneously exposed organisations to new threats to information security, HR and regulatory compliance, based on the behaviour of employees, staff and contractors.Few tools are available to tackle this increased level of 'people risk' that extends to fraud or racial and sexual harassment, gender bias or other policy violations.The very large volumes of dynamic and unmoderated content on collaboration platforms mean that without the right tools in place, the shift to WFH and WFA creates a "ticking time bomb" for many organisations.**IT Data risk**Outside of the controlled environment of the office, employees are more likely to lose, accidentally give away data, Intellectual property or open-up security vulnerabilities and ultimately create irreparable damage.For example, credentials may be exchanged in Slack, confidential information shared in public channels, etc.Whilst software and hardware solutions secure the data 'at rest' or 'in-flight', the human risk of a voluntary or accidental leak is left wide open as the employees 'work anywhere' and are in contact with 'anyone'.**Use cases: Insider threats*** Information Security theft and data leak* Intellectual property leak* Sensitive or PI data exchanged* Security breach**HR Risk**Patterns of behaviours that would have been identified in an office could go undetected and hide cases of harassment, fraud, mental health and other HR issues.With COVID, groups of individuals react differently from the transition to working outside the office and some suffer from mental health issues or simply struggle with remote working away from the day to day contact with colleagues.This will also address core issues of diversity, equality and inclusion in a remote virtual environment.**Use cases: Undesired behaviours*** Harassment, discrimination, bullying* Impact on equality, inclusion and diversity-identification of sexist and racist hate speech, relevant with MeToo and Black Lives Matter mouvements. Technology can give employees an equal footing in conversations.* Undesired behaviours and toxic language, intentional or unintentional (non verbal cues)* Compliance with industry regulations (e.g., anti-bribery, collusion, etc.)* Trend analysis reflecting morale and cultural changes in virtual workplaces**Innovation**Although solutions exist to protect organisations lie Data Loss Prevention or to monitor conversations for compliance, they are restricted to basic keyword matching or message level rules, usually operate "on the edge" message by message and do not consider patterns of behaviours that underpin the broader issues.Consequently, the characteristics of harassment, bullying or other behaviours that would have been picked up by colleagues in an office would go unnoticed on a collaboration platform.In a similar way, abnormal patterns of activity would fail to be correlated to a confidential company event, new product launch, IP disclosure.The proposed solution focuses on analysis of behaviours through collaboration platforms such as Slack and MS Teams to proactively detect abnormal behaviours, deviations from baseline and trends.It is based on AI models trained to recognise patterns of behaviour and text analytics designed to identify PI, entities, sentiment, toxicity, emotion, etc.